Hello and welcome everyone. My name is Eric Fransen, stepping in today for Shannon Kemp, who is on vacation this week. We would like to thank you for joining us for this month's installment of the Monthly DEMA International Webinar Series. The Webinar Series is designed to give our Enterprise Data World Conference attendees educational opportunities year-round. We are excited about the upcoming Enterprise Data World 2016 event, which will be held in San Diego, California, April 17th through 22nd. Registration is open for that event, so be sure to check out the details at EnterpriseDataWorld.com. Today's Webinar will be presented by DEMA Publications Director, Laura Sebastian Coleman, and she will be discussing big and little data quality. A couple of points to get us started. Due to the very large number of people that attend these sessions, you will be muted during the Webinar. If you would like to chat with us or with each other, we certainly encourage you to do so. Just click the chat icon in the upper right-hand corner of the screen to enable that feature. For questions, we will be collecting them via the Q&A section, which is different than chat. That you will find in the bottom right-hand corner of your screen, or if you like to tweet, we encourage you to share highlights or questions via Twitter using hashtag DAMA. As always, we will send a follow-up email within two business days containing links to these slides, the recording of this session, and any additional information that may come up during the Webinar. And now a few words about our speaker. Laura Sebastian Coleman is data quality and data standard center of excellence lead at Cigna. She has worked on data quality in large healthcare analytic data warehouses since 2003. She has implemented data quality metrics and reporting, launched and facilitated data quality working groups, contributed to data consumer training programs, and led efforts to establish data standards and to manage metadata for large analytic data warehouses. In 2009, she led a group of analysts at Optum in developing the original data quality assessment framework, which is the basis for her book Measuring Data Quality for Ongoing Improvement. That was a Morgan Kaufman publication. An active professional, Laura, is Dama Publications Director. In 2015, she received IAIDQ's Distinguished Member Award for her contributions to the International Association for Information and Data Quality. And with that, I will turn things over to Laura to start the presentation. Laura, hello, and welcome. Thank you, Eric. I appreciate the introduction. And thanks to everyone who's attending. I know that all of us are busy, and so making a decision to take an hour out of your day to attend a webinar like this is not always easy. I appreciate your being here. I want to just add to the notes that Eric shared in the introduction that a couple of influences on how I think about data quality, and these will come into play in the presentation. So my thinking on data quality has been influenced very strongly by the basic challenge of how to measure the quality of data. And the concept of measurement itself has led me to think about data in a different way from how I used to think about it. Problems of measurement are microcosms of problems of data definition and collection. So the other thing that's influenced me has been the demands of data warehousing and particularly the challenges of data integration, where we have data defined in diverse ways and we need to bring it together so that data consumers can understand it in a similar way. I think as we move into the world of big data, the challenges are changing, but they are evolving in ways that we can, in some cases, anticipate and plan for, particularly when we talk about integration. So with that, I'd like to get started on the content. And hang on one moment. Here we go. So I want to review the problem that we're going to be talking about today. We know that we live in a world of intense technical innovation, and we can capture a tremendous amount of data in an incredibly short time with great speed through instruments that will tell us something about the content of that data. More importantly, we really want to use that data. We want to get value from the data. However, we still face some of the basic challenges that have been around since people recognized the impact of processes on the creation of high or poor quality data. So we have not mastered those fundamental changes. Now, within healthcare, despite the fact that we have technological advances, much of the data that's collected is still collected through person-to-person contact. And when we talk about this data, it's not big data at all. It's little data. So I'm going to be walking you guys through ways to think about data in old and new ways, and I hope that this will improve your approach to how to improve the quality of data in your organizations, regardless of whether you're dealing with big data quality or little data quality. So first I'm going to walk through some of the challenges within healthcare, so what we really want to get out of big data and what obstacles are in the way to getting there. Then I want to step back from that for a moment with that context in mind and talk about the concepts of data and data quality to shed light on how to solve these problems. And then I'm going to make a couple of suggestions of things that I think can happen within healthcare to make good on the promises that big data implies. So when we talk about data in healthcare, as in other areas, we are developing ways of both collecting and using data that are brand new and that change virtually on a daily basis. One of the big developments is that there are tons of applications, mobile apps and the like, that are aimed at helping people manage their health. And these applications make big promises. They promise better decision-making, higher levels of engagement, better levels of compliance. They offer ways to actually change how we live, how we manage our lifestyle choices, and therefore they imply that they can improve our health. They can prepare us to manage illnesses and help us manage those illnesses. And then for the system overall, they also promise that we can do things like manage demand. So if you're headed for an emergency room that is already full, you might be redirected to an emergency room a few miles away that could help where you would get care faster. In making these promises, there's the implication that we can actually transform healthcare. And many of the articles on this subject imply that the train is already rolling along and that we must get on it. So Pricewaterhouse Coopers has published a very interesting white paper on healthcare delivery in the future. And they talk about the fundamental imperative to have digitally enabled care. This imperative and the availability of data, the ability to collect it, have created major changes in how healthcare is being delivered and how it can be delivered. And this sounds almost like science fiction when writers say that digital technology bridges time, distance, and the expectation gap between consumers and clinicians. So that's a pretty big promise. However, the reality of healthcare is that oftentimes the system is not working the way that we want it to and there are big obstacles in the way. So about six months ago there was an insurance summit in Hartford and healthcare executives were trying to understand why innovation in healthcare leads to higher costs. So in other areas we have technological innovation and that becomes a means of saving costs, but in healthcare it often leads to higher costs. One of the executives estimated that about 30% of healthcare costs were due to inefficiencies. So we think about technology as a means of gaining efficiencies, but if we are spending 30% of our money in an inefficient way, then we are not realizing the benefits associated with innovation. So another one of them lamented that many of the applications and drivers are encouraging people to take better care of their health, but it's easy to say that people should take care of their health, but it is not easy to actually make them take care of their health. So healthcare has the possibility of being transformed by bigger data and technological innovation through healthcare analytics, but there are a lot of obstacles in the way. So the promise is based on the assumption that high quality data is available and that it is truly high quality, that it does represent the interactions between providers and patients in a meaningful way. What are some of the technological limitations on the healthcare system right now? One is legacy systems. So most of the large healthcare companies have been around for decades, and they work based on older systems. These systems can differ widely within organizations, and they certainly differ between organizations. A second driver is that the medical profession, providers, your doctors and such are still not very technologically enabled. So when we look at how we're trying to transition away from paper, we realize that this has been a slow process. Much of healthcare is still paper driven. And we look at in 2008, which was only a few years back, only 4% of providers had electronic health records systems, had a full electronic health record, and only 13% had a basic system. So when we think about that, we realize it's a slow transition to actually get the providers out in the field to be doing things in an electronic way. I was at the doctor just last week, and I found myself filling out paper forms that were exactly the same paper forms that I'd filled out the year before. So other factors that have influenced the challenges with healthcare data quality is a lack of standards. Now, there are plenty of standard codes. There are plenty of directives for standardization, but people have applied these inconsistently or they haven't had enough information to apply them in a way that improves the overall quality of the data. And there haven't been any standards actually directed at data quality itself. There are standards for other aspects of healthcare. I want to give an example of this and talk about a group called Academy Health. So about a year and a half ago, I was involved with a meeting run by Academy Health, who is a group of academics who are looking to improve information around the quality of data that is gathered in nonclinical settings. So what they want to do is understand if they are using this data to understand a phenomenon within the healthcare system or to understand the details of a disease, how much confidence should they have in the data. And they recognize that as more data is collected and is made available through research data warehouses, they could potentially have a rich source of data that they could use to do analyses that do not necessarily require clinical trials. So clinical trials are expensive and they want to understand how to get at some questions through other means. So because academics and researchers are using these sources of data, most of which come from large commercial payers in the healthcare system, they're trying to develop standards where they can numerically express the quality of data. What they found is that there are a number of factors that can cause a misrepresentation of certain clinical events. And these include systems that are inflexible in their design, so you cannot capture the events consistently. Coding practices within hospitals and other provider settings where people would make different choices about how to represent those events and then gaps in the standards themselves. So they gave an example of screaming for high blood pressure in children. Clinicians were directed to screaming for high blood pressure, so that meant they actually were taking the blood pressure of children and trying to understand whether there was any risk of the children getting high blood pressure. And they were asked after the initial screaming to continue to monitor the children. After this data had been collected for a period of time and researchers looked at it, what they found was it appeared that children were increasingly at risk for high blood pressure and they were surprised by this finding. But when they actually went back and did a records review, they showed that it wasn't that children were actually at higher risk, but that there was a misuse of the hypertension high blood pressure diagnosis code. Because there was not a diagnosis code for considering hypertension, the doctors were unable to record what they were actually doing and the data appeared to show that something different was happening from what was actually taking place. So this was just one example of the kinds of gaps that can evolve when we do not have the standards or when the choices in how to collect data are influenced by factors that may lead to confusion. So we'll think about healthcare. Healthcare is about taking care of people. Those people who are in healthcare are driven by their concern for other people. So we have a lot of room for interpretation. And those interpretive factors may influence how symptoms are read and how we represent them. And as those choices are made, we might reach different conclusions about what story the data is actually telling us. So I'm going to go back. I'm going to step back from having set up the problem and talk about characteristics of data that we might be able to use to improve the situation. So most of us assume we know what data is, but it's always good to start with definitions because when we explore them, we can see other facets of the topics that we're thinking about. So when we go back to the beginning, data has a Latin root. It is the past participle of to give. And if you guys are in math or engineering, you recognize that data is equivalent to your givens. In modern parlance, we talk about data as facts and statistics. And we think of them as used for analysis or used for reference. So data has a level of objectivity to it. Of all these definitions, my preferred one is the ITO definition because it also acknowledges the level to which we rely on information technology and systems when we start to think about how data is created. So ITO defines data as, quote, reinterpretable representation of information in a formalized manner, suitable for communication, interpretation, or processing. I realize that's a mouthful, but it is really worth thinking about each word. So data needs to be interpreted. It is representing something. It has a formal structure. And the reason for it having a formal structure is so that it can be used to communicate, so people can interpret it in a consistent manner, and also so it can be processed. It can move from system to system. When we think about data conceptually, we understand that it's trying to tell the truth about the world, but we also should understand that in order to get to that truth, we have to make a set of decisions about creating that data. So we choose what characteristics to represent. We choose the form in which we will represent them, and we need to be very clear in what those choices are so that other people can understand the data itself and what it represents. We also know that the driver of collecting all this data is so that people can use it, and especially in this day and age, as people realize how reliant we are on data itself to run our businesses and to learn more about our world. So the uses of data also imply a set of expectations about what conditions the data should be in and therefore about its quality. We also should keep in mind that in today's world, we call practically everything data, and we do not create data with usage in mind, and that becomes a problem. So if we think about the history of measurement and the historical context of data, we realize that our ideas about data are driven by two different places where data is created and used. So in science, we create data, and in commerce, we create data. So we have different goals and different approaches. So we think about science. Science is focusing largely on measurement and observation as a means to create knowledge and advance knowledge.  That's the foundation of science. So it's always testing and retesting. In science, data is truly a product, a product of the process, so the process needs to ensure the quality of the data. Otherwise, you lose credibility. Commerce, on the other hand, creates measurements to achieve goals. So if you are the baker in town and you want to sell your bread at a fair price and make a profit, you need to know how big a loaf you're going to sell at a fair price and you need to know what your competitor is going to sell for. So when commerce is using measurement and creating data, it's less planned and more accidental. The goal is to sell and make a profit, and the data supports that goal. So in that sense, data is a byproduct of commerce. Historically, the quality of data has not been an end in itself when we think about data in commerce, whereas the opposite is true in science. So if you try to visualize the differences, we realize that a scientific approach is both more fluid in terms of what it's going to look at, but then ultimately more strict once it has reached its conclusion, whereas commerce assumes that data is fixed and it doesn't actually want to do the work to make it fixed. So most of us are in organizations that take much more of a commercial view of data than a scientific view of data. That said, our ideas about data are usually based on our scientific notion that we are somehow collecting facts about the real world and that in doing that, we have a connection to reality that should be stable and should be reliable in which we should be confident. So we get frustrated when data is of low quality because we assume it should be of better quality. When we think about how we create data, there's this cyclical process. We create data because we're observing the world in one way or another and we make choices to capture those observations and represent the world. That results in data, a condensed form of our knowledge about the world. We then want to use that data and we assume that it should be fixed for our purposes of use. Why do we assume that? Because if the data represents the world, if we know that we're taking measurements of the mileage between cities or the temperature of the water, we assume that our process for representing those things is defective. And in many cases, it is because we can all agree on what a temperature is or what a mile is. The challenge is coming if we're missing some of the pieces. So if we know what the temperature is but we don't know what scale it's in, then we have a data quality problem. If we know the distance, if we have a number associated with the distance, but it's not a unit of measure and we misunderstand what unit of measure is used, then we have a data quality problem. We can also make bad choices about representation or the knowledge of those choices might be lost. In all those cases, we run into a conflict between what we expect and what we actually have. So this problem becomes more complicated when we start to talk about big data. And even in science, people are struggling with inconsistencies in data, unexpected inconsistencies. So about a year ago, Science News reported the challenges that researchers, scientific researchers were having with using big data. And they reported, among other things, that just tracking the data is challenging. And then sharing the data is challenging because oftentimes people don't know the origin of the data or the ways in which the data was collected. Now, in science, this is fundamental to the process because if you do not know where your data came from then you cannot replicate your own, you cannot replicate your results. One of the things that I found most interesting in this article was it recognized that even the way we look at data will influence the ability to replicate results. So the scientists reported that the tools that are used to analyze complex data sets are as important as the data themselves. And choosing one computer program over another may in fact end up bringing about different results and different conclusions, which is even more to the point. So the inability to reproduce results has been a challenge in science. And scientists have begun studying the factors that influence reproducibility. And they talked about what they call the butterfly effect, which if any of you are familiar with this concept, it basically says that you can have very small changes in your beginning conditions, and those changes may have very large influences on the resulting conclusions. So for example, the story that's always told to illustrate the butterfly effect and why it's called the butterfly effect is that if a butterfly flaps its wings in Brazil on a Tuesday, this could cause a hurricane in France on a Wednesday. So it's that idea. Small changes can have big effects. So researchers have been looking at the doctor-patient relationship and tried to understand how this butterfly effect works on that relationship. So earlier I said any doctor-patient interaction is a series of interpretations and recording those interpretations. They looked at 12 different factors that can influence clinical decision-making. They're listed on this slide. I won't go through them in detail, but you can see that they fall into these four categories of decision features, situational factors, characteristics of the decision-maker, and individual differences. So within each of these, you can have different initial conditions. When they looked across these, they saw that there were over 20,000 combinations that could represent the initial conditions of an experiment or an interaction. So that's a huge number. That's a huge number. And if we think about that, then the problem of accuracy becomes totally different because when we're creating data within the healthcare system, there are essentially thousands of opportunities to influence the process of decision-making and how to treat the patient. And if we have that combined with older technology that doesn't adapt to new protocols or conditions, or for which we don't actually have clear standards or those standards are applied inconsistently, then there's a lot of room for variation within the system. And when we have variation within the system, we have different levels of quality and different levels of reliability for the data. So how do we move beyond this? I'd like to propose three different facets of an approach. And I'll talk in depth on each of these. But the first is recognizing that there is variation and that it may be possible to use this variation to improve the system. The second is to think about how do we reduce variation within the system, variation that causes noise or actually interferes with our ability to act in our own best interest. And then finally, I'll come back to one of the fundamentals of data quality, and that is to recognize data quality as a product of the system and take steps to plan for higher quality data throughout the system. So the first one, recognizing variation. So usually when we talk about variation within the system, our urge is to say, oh, we must get rid of the variation in order for the system to run smoothly. However, based on what we look at with respect to how clinicians look at patients, some of that variation may actually be good. If we have two doctors and each of them brings a different perspective to a problem, then they can learn from each other, and they may together be able to come up with a better solution than either one of them could come up with individually. So variation may have meaning. It may add to our ability to understand the situation. And if it does, and we can gain knowledge through those differences, then that becomes a mechanism by which to provide feedback to the system and therefore thereby improve the system. When we think about why we want to take advantage of healthcare analytics and evidence-based medicine, this is exactly what we want to do. We can see if we look at large numbers of claims, medical claims related to the same diseases or conditions, and we can understand how the different kinds of treatments produce outcomes, then we might be able to find within those various approaches, we might be able to find which ones work best and which ones do not work as well. And that can become a very good way of improving treatments overall. So variation itself may be helpful and can be a starting point for improving how we do treatments. That said, there are also reasons when we can understand variation, there are reasons then to reduce variation. And in areas where variation may cause a quality problem, we would want to take those steps. So one of those steps is enforcing data quality standards within healthcare. As I alluded to earlier with the example of Academy Health, their exploration of large sets of claim data has shown that there are significant differences in the way that we record events and significant differences in the way we process claims and the like. So it's hard to tell, given all of those things, how good the data is. And we could and we can improve it. So when we think about this in relation to big data, we see that one of the advantages is that more data can be collected through instruments rather than relying on human interpretation for things that can be objectively measured. So if we think about things like snippets or other devices that allow us to collect healthcare biometric data, and if we know the device itself and if the device is well calibrated, then we can reduce the ambiguity of the data collection. We can collect it in a much more consistent way. And despite the fact that in many respects healthcare needs to be more technologically adept, the provider's offices could up the game and the like, there's certainly been a movement for the use of apps and the use of devices to collect biometric data that is really improving the collection of that data. So for example, in Pricewaterhouse, Coopers reported that 28% of consumers have at least one health-related application on their tablets or smartphones. So people are engaging with these applications and that had increased, you know, more than doubled in three years. And I'd be interested to know even now, you know, a year later what the statistics on that are. As importantly, about two-thirds of doctors said they would be willing to prescribe an app. So that means they would scrutinize what they think, you know, the best app is to provide guidance to their patients and they would be willing to prescribe that. If we can be collecting this data and then integrating it into the electronic medical records, then we have a big opportunity to have reliable, well-defined data focused on particular patient needs included in those electronic health records, which then could move from physician to physician as people look for different kinds of care or different kinds of treatments. So this process and these kinds of devices enable feedback about the data from both providers and patients. This is another advantage. So if you are looking at a paper medical record and everything's written down and you don't have your own copy, you're not going to be able to find errors. But if you have your own electronic medical record and you see an error, if you see a problem or something missing, then you have the ability to provide that feedback. So that can reduce errors within records and can also enable consumers to have a better view of their health. So these are some of the things that will allow us to reduce variation where variation is causing problems and also will be truly taking advantage of these new means of managing data, collecting data. My final point is, again, harkens back to some fundamentals of data quality. So in 1996, Richard Lang published an article on data quality in which he said, we should treat data as a product of processes. And that rallying cry is still important. We have to recognize that if we're going to take advantage of data to learn more, then we have to have trustworthy and reliable data. And particularly within healthcare, data is not a secondary thing. If we don't have data, we give up the opportunity to improve outcomes. So we really need to rethink the system and focus on ensuring that throughout the healthcare process we collect accurate, complete data. Whether that data is our standard healthcare data when you go to the physician's office or whether it is biometric data that's collected through some device. And we do have an understanding of what we mean by high quality data. It is clearly defined. We know what the data represents. It represents unambiguously that characteristic of the real world. It's consistently collected through reliable processes. So if we have a device to collect the data, then that device is well calibrated and it is sending data at the proper frequency and the like. If we have a process, a more manual process, then the people who execute that process are well trained. They understand how to apply standards and the like. And then the standards themselves are comprehensible and usable. So the processes and systems that we build to create healthcare data need to be designed from the beginning with the data itself in mind. And the industry needs to recognize that even though it is a people-to-people industry in many ways, the people on both sides of that equation are relying on the information that they exchange to get to the place where they want to be, which is to help people lead better lives, to be healthier, and to have a greater sense of security. So that's my pitch for better data quality. Within the slides, I've also included a set of references to some of the articles that influenced my thinking here. I would like to draw your attention, especially for those in the healthcare industry, to the Place Waterhouse Cooper's white paper on the healthcare industry, and also to the Consumer Reports article on healthcare and how consumer choices are influencing healthcare. So with that, Eric, I'll bring it to a close, and I'd be glad to start on the Q&A portion of the webinar. Well, Laura, thank you so much, and thank you for the thorough presentation. And while we wait for some more questions to come in, I do want to remind everyone, please use the Q&A box, that's the lower right portion of your screen, rather than the chat window. Also, if you're madly trying to write down all of those URLs in front of you, please know that we will post those in a clickable format on the DataVersity.net website when we post the recording of this session and the slides, which is a good opportunity to remind everyone, we will be posting the recorded webinar and slides to DataVersity.net within two business days, and all of the registrants of today's webinar will receive a follow-up email to let you know how to access that material and when it's been posted. Also, just a quick reminder that you will be able to meet Laura in person at Enterprise DataWorld 2016, which will be held in San Diego, California, April 17th through 22nd. Registration is open for that event, and details are available at enterprisedataworld.com. All right, so let's see if we have any questions coming in yet. Not yet. All right. You've thoroughly filled everyone's brains, Laura. Wow. Here we go. Here's a question. Quality data depends upon the participation of medical personnel. Given competing priorities on their time, how can data collection become more streamlined? Yeah, that is a very good question. And part of what I see as an opportunity is to collect more data through devices. I'll give an example. When I was in my 20s, I had my first EKG, and the process of setting up the EKG took, it felt like, about 15 minutes, and then, of course, the process of getting off of the EKG was equally burdensome. I had an EKG earlier this month, and the improvement in the way that that is administered is largely a technological improvement. The device is smaller, the process for setting it up is much quicker setting it up and taking it down, and the results themselves are much more reliable. So when we talk about certain kinds of measurements, I think the opportunity is for better technology to collect data. And I think many of you who have gone through the doctor had measurement procedures. You probably can cite examples in your own lives where that's the case. On the downside is the danger of our physicians being overworked in some cases and having very high demand, and not only the physicians themselves, but many people who are part of the provider offices and the like are under pressure to do a lot in a short period of time, and this raises challenges. I think the only way to overcome that problem is first to recognize, again, that the data that we're collecting is extremely important to improving the system and changing the orientation from data as something that you collect in order to submit a claim to data as something that has a life beyond just paying that claim. I don't know exactly how to solve that problem because I don't work in a medical office, but I do know that we need, in a sense, to turn that ship. And it may be that getting a different kind of participation from the medical community may come about from within that community themselves if they can make the connection between the data that they create and the ways in which that data can be used. So I don't have the answer, but I do think it's a custom worth exploring. Yeah. Next question. Can you speak a little bit to the maturity of the healthcare area in general in using big data to get useful insights to improve people's health? Is there any country already advanced in this area? So I think overall there is a good deal of maturity in using big data to get insights. I know about five or six years ago when people first started talking about big data and data lakes and these different ways of pulling together disparate data in order to understand, in order to gain different insights about the healthcare system, that was five or six years ago people were kind of struggling to figure out how to do that. But now most of the healthcare payers have teams of data scientists who are looking at big data. There are university programs in data science with the healthcare specialty. So there's been a good deal of movement in this direction. I think the challenges of actually having confidence in the quality of the data are being overcome somewhat. Again, when we have data that is collected by devices and the definition of what it represents is very clear, you can really dive into that data. When we look at medical claim data that is collected in more traditional ways, then it needs to be used with caution. So I've seen changes within the field. I'm not directly doing healthcare analytics myself, but I've seen changes within the field of healthcare analytics that are very exciting. The data itself, I think we still need to work on, especially the data that's collected in more traditional ways. Part of the question is, is there one country doing more of this than others? I can't speak to that, but I do know that there's a lot of international conversation about how to use this data. So for example, the Academy Health Reference that I talked about, the folks that are part of that are engaged in conversation, not only within the U.S., but across international borders. So I think there's a lot to be gained, and people are truly trying to take a scientific approach to it. Okay. Are you aware of specific organizations that are developing data quality standards for healthcare? The questioner is looking for industry guidance on how we can confirm that we have quality data or surface data quality issues. Yeah, so the Academy Health example that I gave is the one that I'm most familiar with from a healthcare perspective. And there's an organization called Type 4, I believe, and I'll follow up and make sure I've got that right, who are part of driving that forward. So, and I'm not going to remember the individual's names, but I will look them up. I know one of our IAIDQ members is very active in this process. So I can send that to you, Eric, that information, and have you maybe share it when you share the rest of the webinar materials? Sure. Sure. Are you aware of any efforts to create a data model for healthcare? The questioner says, in any area, a data model can be a foundation upon which to build the analytics and also serves as a way of seeing which data are available or not and helps think of getting the missing data, etc. Are you aware of any efforts like that? Yeah, so I know several of the warehouse vendors have created industry standard models. So, for example, CARA Data has an industry standard healthcare model. Within the two organizations for which I've worked in healthcare, Optum and Cigna, each of those organizations has created an overall model. What I'm not familiar with is a vendor-neutral healthcare model. And I think I agree with the person who asked the question that a data model is a really good beginning point for establishing expectations for quality and establishing data quality standards. I'm a firm believer in having a data model as a way to have the conversations and then also as a way of capturing the results of those conversations about quality expectations. So, while there isn't, to my knowledge, a vendor-neutral industry standard, I think anybody working in this space should have a working data model if they want to improve the quality of their data. Earlier, you mentioned high-quality data. From your perspective, what are the thresholds of describing data sets as high-quality? So, I could talk for another hour on this question. No doubt. So, I'll talk a little bit, I'll talk about two things. One, my definition of what it means for data to be of high quality and then my thoughts on thresholds. So, high-quality data, and I'm going to just go back to my slide on, representational effectiveness and fitness for purpose. So, most discussions of data quality start with fitness for purpose and they say, you know, the quality of data is judged by the consumer of the data and whether the data is fit for the purpose the consumer wants it for. That's been a kind of standard way of talking about data quality that comes from Richard Lang and Tom Redman and Larry English, other thought leaders in data quality. And I think that is the place where the quality of data gets judged. But I also think that we need to talk about, we need to consider representational effectiveness. And for those of you who are familiar with thoughts on this, Malcolm Pauly talks about this concept of representational effectiveness. So, why are they connected? They're connected because if you're going to use data, you're probably going to use it because you want to explore what it represents. So, if you're going to study global warming, if you want to reach conclusions about global warming, then you need data about the temperature of the earth and changes in weather patterns and all of those things in order to do an analysis of global warming. If you want to improve the treatment of diabetes, then you need data about the treatments that have been used and the outcomes that have been derived from those treatments in order to do your analysis. So, there's a direct relationship between these two things. And our expectations of fitness for purpose are directly related to what the data represents. So, when we talk about then measuring that, we need to understand both pieces. We need to understand how well the data represents the thing it's supposed to represent. And then we can say, ah, it's fit for my purpose. There can be many different purposes for the same data. The classic example is address data. If you have all of your customers' addresses and you want to do a physical mailing, then those addresses need to be accurate at that time. If you have all your customers' addresses and you want to do trend analysis on, you know, your sales five years ago and your sales six years ago, then you need not only the addresses as they are today, but you may need the historical address. So, when we start to think about that, we get in this conversation about what do you expect from the data? What are you using it for? And then you can set standards for levels of completeness, levels of validity, levels of accuracy, however you want to approach that from a dimensional point of view. So, when I think about high-quality data, I think about data that you've had a conversation with your customers about what they are using that data for. You have objective measures for the data, and you can share those measurements with your data consumers so they can then judge whether they can use the data or not or whether it's fit for their purpose. So, you need a lot of pieces in order to get to a threshold. There isn't just one threshold. You need, in a sense, knowledge about the use, knowledge about what the data represents. All right. Laura, thank you so much. It is now the end of the hour. I'm afraid that is all the time we have. Thank you all for your questions, for tuning in today. I hope you all have a wonderful day. And hopefully we will see many of you at Enterprise Data World in April. We look forward to seeing you there and online at dataversity.net and in future webinars. Thank you so much. Thank you, Eric.


When fighters are preparing for a fight, MMA, boxing, probably Jiu Jitsu, whatever, they go to camp. A camp is where they have a training cycle and it's usually 12 to 16 weeks somewhere in there. The goal of camp is through certain work and rest cycles to physically peak during the time of the fight. So they work on technique and strength and conditioning and all this stuff so that right as the fight's happening, they are hitting their physical peak. And they do that with a whole team of coaches through certain prescribed work and rest cycles and whatever. Which is why it's a super big deal when fighters drop out of fights, right? Or take a fight on short notice because they haven't been in camp and they're not hitting that physical peak. Now imagine that you have a fight coming and you don't know when it is and you don't know who it's against and you just have to maintain camp all the time. Hey everyone, Dylan Schumacher, Citadel Defense and I've been thinking recently about the idea of constant readiness. There are certain military units around the world that have to maintain a state of constant readiness. Firefighters, probably paramedics, EMS. Like there are certain people in the world who do have to maintain this state of constant readiness. And in case you didn't know, you're one of them. Being just an average Joe Schmo person, you have to maintain the state of constant readiness because if your day is gonna come or when it's gonna come or when it's gonna be, you don't necessarily know. It could be today, it could be tomorrow, it could be in 45 years from now, it could be never. You just don't know.   Injuries are part of the deal of lifting heavy weights, right? That's gonna happen. You gotta work through your injuries. And I think that there are kind of two different ways you could go with that when you get injured of any kind.  And at that point, you can decide to not recover and move back into a state of constant readiness or you can work through the injury, right? You see this all the time with people who blew out their back 25 years ago and just never did anything. And at this point are so atrophied and in so much pain that the idea of them to physically moving, of course, is just daunting. You also see this of course in people that just don't prepare at all and aren't in any kind of state of readiness whatsoever. So I'm making this video to encourage you to be in that constant state of readiness. That doesn't necessarily mean that you're just going to hit the gym for four hours every day, seven days a week all the time. Although I do have friends who do that. You know who you are. I'm saying that you need to have a long term view of constant readiness. That you are always doing something to be better prepared if your day ever were to come. I think that at minimum means some kind of strength and conditioning program. Do what you want. This isn't a workout channel. I'm a big fan of starting strength. That also means some kind of consistent dry fire regimen. Because we all know that if you want to get better at shooting, dry fire is how you're going to do it. The best shooters in the world dry fire all the time. That's how you get better at shooting. And in life there are just different seasons. There are seasons where you have lots of time.  And then there are other seasons where you just don't have the time right now and it's going to take a decrease and you're not going to be able to get to it as much as you'd like. The important part is that when those seasons come you're not using that as an excuse to do nothing. Because of course if you do nothing long enough that just becomes habit. And then you are always saying I'll get back to it and five years later you wake up and your day is here and you aren't prepared. So I would highly encourage you to maintain your state of constant readiness. And that can be daunting but when you look at it in the term of just normal day in day out life rhythms, life cycles you're trying to pack away a little bit more skill, a little bit more strength each day. Over the long haul that's going to add up significantly. I understand that we're all busy and we have lives and wives and jobs and the whole nine yards. However, take some time and prepare yourself so that you maintain your state of constant readiness so that if your day ever comes you aren't found lacking.


This video is brought to you by CuriosityStream. If you sign up to CuriosityStream with the link in the description, you'll also get access to Nebula, where you can watch all of my videos early and ad-free, and you can be among the first to watch my new project, Wish You Were Here, an album companion, which is available in full on Nebula right now. More on that after the video, and if you think I'm cool and or interesting, you should maybe subscribe, I guess. I've got to admit that for a long time I was confused by the cover of Yeses Close to the Edge. The album itself is one of the most expansive pieces of music ever recorded. It's musically profound, stretching rock to its limits with the trio of technically grueling songs that soar and dive through a half-dozen emotional states. Lyrically, it's surreal and esoteric, pulling from Herman Hesse's philosophical novel Siddhartha and bringing up broad questions about the very nature of humanity. To me, the calm green wash of the album cover never quite seemed to capture this feeling, especially as compared to a lot of Yeses' other album covers. But then I realized that there is a piece of artwork that does fully capture the magnificence of Close to the Edge. It's just not on the front of the packaging. Welcome to cover stories. I think that those of us who grew up and found music in the age of CDs, iTunes, and streaming have a fundamentally different conception of album artwork. In the digital world, album artwork lives as a single image confined to two dimensions. But in the age of vinyl, the packaging was a living artifact meant to be held as you listen to the music inspected for its every detail and passed around to friends. And the packaging reflected this, including liner notes or extra photos of the band. As rock music grew more elaborate and decadent in the 60s and 70s, so too did its packaging. Some of the best designs of this era consist of panoramic artwork that spreads across the sleeves. And sometimes they would even include interactive components or inserts inside the packaging. When these artworks are condensed down to a single digital image, a lot of their punch is lost. And that brings us back to Close to the Edge. The cover artwork that we all see when we stream yes on our phones is only half the story. Because Close to the Edge had gatefold packaging. And so the true genius of the album artwork is hidden behind a page turn. Like cracking open a classic sci-fi novel, turning the gatefold of Close to the Edge immerses you into a new and strange world. And this world completely captures the profundity and expansiveness of yes. This astounding gatefold was done by Roger Dean, who worked closely with yes throughout their career and even designed the iconic logo that made its debut on the front of Close to the Edge. Dean's artwork is distinct. It's surreal and utopian, depicting cinematic dreamscapes of alien worlds or imagined futures for a united humanity. Dean is a master craftsman. His works drip with stunning detail and pop with magnificent color. They're a perfect depiction of how it feels to listen to the strange cosmic sounds of progressive rock. Throughout the 70s and 80s, his artwork became forever linked with that genre thanks to his work with groups like Yes, Asia, and Gentle Giant. And his distinct style has impacts beyond music as well. His artwork was no doubt an influence on many of the surreal landscapes that adorn the basic lands of Magic the Gathering. And the planet Pandora from James Cameron's avatar shares some serious resemblance to Dean's work. In fact, Dean even tried to sue James Cameron over that fact. And that avatar influence is pretty clear looking at Close to the Edge. I really believe that Close to the Edge is one of the finest artworks from a truly singular visual artist. In designing the cover, Dean was inspired by hiking journeys in the Scottish Highlands as well as the panoramic views of England's Lake District. But Dean expands these images into something wider, more surreal. It's a piece of artwork that encourages participation, calling you in to explore its every detail. Dean explained to Louder Sound, I was painting landscapes to look real, and in the most literal sense of the word, enticing. I wanted them to pull you in and make people want to imagine what it would be like getting on a boat to the island. If that was the goal Dean knocked it out of the park. The longer you look at Close to the Edge, the more details there are to appreciate. The pristine lake spills over lush cliff sides into endless waterfall. An impossible bridge leads you into the artwork, inviting you to explore this world. And buried deep in the photo, almost as an afterthought, we see something that might be a human dwelling. It's a reminder of how small we all are, and how magnificent the universe around us is. A perfect visual expression of what yes, we're doing musically. And this works in concert with the minimal exterior cover. The act of opening close to the edge can feel like finding enlightenment, peering beyond something that seems impenetrable to find sublime beauty. This entire experience is lost in the translation of art across mediums. In fact, when Close to the Edge was first printed as a CD, the gatefold was left out of the packaging entirely. To me, that is a travesty. Listening to Close to the Edge with this as your visualization is a fundamentally different experience than listening to Close to the Edge with this as your visualization. And Close to the Edge is far from the only case where digital representation has undercut the sleeve designer's vision. Look at Miles Davis' Bitches Brew. What we get is definitely more representative of the album sound than the cover of Close to the Edge, but when you look at the front and back together, you get an astounding Yin and Yang panorama. Or how about Black Moses, where the record unfolds into a full portrait of Isaac Hayes shaped like a cross, hammering home the messianic imagery of the album. On Cream's Wheel of Fire, a black and white cover opens into an astounding psychedelic gatefold. And I could go on. There's so much incredible album packaging out there that is completely undermined by the way it's presented digitally. But that shouldn't have to be the case. Surely with the seemingly boundless capabilities of digital technology, we can come up with a better way of doing this, a way that honors the intent of the artists and designers that made these records so spectacular to begin with. I don't know, maybe that vision is too optimistic, but I think that at the very least, we should start giving Close to the Edge its due as some of the greatest album artwork ever made. Another one of my favorite pieces of album artwork ever made is Pink Floyd's Wish You Were Here. In fact, that album is one of my favorite albums ever made, period, so I created a new project to celebrate it. If you go to Nebula right now, you can watch the entirety of Wish You Were Here, an album companion. That's a video that plays in real time alongside the entirety of Wish You Were Here and explores the story of how the album was made and why it's still relevant today. It even includes a section on the iconic packaging if you're hungry for more cover stories. That project will be coming to YouTube in multiple videos eventually, but the only place that you'll ever be able to watch it in full as I envisioned it is Nebula. And if you've watched my stuff, chances are you already know that a great way to get started with Nebula is by signing up to CuriosityStream. If you go to curiositystream.com slash polyphonic, you can get 26% off an annual plan, which means less than 15 bucks for a whole year of great documentary content and early ad-free access to my videos. That means that as well as watching my Wish You Were Here companion, you can also watch All I Can Say, an intimate documentary on the tragic life of Blind Melons Shannon Hoon. That documentary assembles camcorder footage shot by Hoon himself to create a raw portrait of his life. So for all that and more, head on over to curiositystream.com slash polyphonic. Make sure to use the link in the description to get the best deal and to let them know that I sent you. And hey, thanks for watching. You're cool.


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Hey GubCon Giants family your host Eric Coffey here of the number one podcast teaching you government contracting for all Teaching everyday people how to win extraordinary contracts helping the small guys compete with the big boys Again, we're called GubCon Giants for a reason because we grow like Jack the beanstalk family So listen stay tuned today's episode. We are doing our famous bid Opportunities on beta dot Sam. I know I know what you're saying Eric I don't see contracts posted on beta dot Sam and for that very reason the first thing I want you to do if you have not already watched this video hidden contracts Make sure to watch that video. It says these contracts are not posted on beta dot Sam or unison Where do you find them? So again before we get started with our famous beta dot Sam bid opportunities Weekly listing. Okay. I just wanted to make sure that all of you watch that video That's a really important video out here because again there's a lot of noise and the Environment out there and the stratosphere you're getting information from conferences and events and people on clubhouse and people in IG chats and DMs and so I'm trying to help you eliminate from listening to all of that outside noise, right and only focus on factual actual information provided by documentation provided by SBA documents DOD documents paper forms things of that sort not what somebody's thinking not someone uncles radical ideas so again Before we get started if you have not already watched this video Make sure to go over and take a look as to again. Where are the hidden contracts? But today we are looking at bid opportunities and beta dot Sam and again when I say bid opportunities It's really social sawts and RF eyes. So again, don't mistake what I'm saying It's really social sawts or vice we call them bid opportunities Why because part of our trifecta to achieving success in the federal arena is RF eyes and source of thought responses It is a necessary necessary must do for all small businesses out here Even if it's not for your particular company share this information with others out there so that they can start doing these things So again, we want to run through Our beta dot Sam Information and yes, I know my lighting is down. I turned it down intentionally By the way, if you have not already picked up your copy of gupcon launch book or the billionaire playbook 2020 revised edition Do so at Amazon store. So again, let's jump into it bid opportunities. So here. I'm on beta dot Sam dot gov in Ordered to do this in order to make this work. You have to be logged in So you've got to go through you've got to set up your login that gov account in order to log into beta dot Sam So in order to do exactly what I'm doing on this video, you must must must Should I say another month must Be logged in. All right, so we're logged in And what we want to do is go to contract opportunities click search and you will see the search results Again, remember for we call it bid opportunities because that's the only way for some people out here that they will be Attracted to even doing these techniques because a lot of times we are under the false narrative that if we bid a job That's faster than helping the government do their market research to determine If there's any qualified small business out here that are competent and capable of doing this work And if I set it too fast, that's because I'm excited. So I repeat myself a Lot of times we are then I'm gonna go to the big screen a lot of times We're under the impression that if we just bid a project that that is a faster approach a faster attempt at securing your first government contract rather than responding to RFIs and source of thought and so many people Out here are under that assumption pre-sumption because I'm pretty sure no one ever told you that And my experiences Respond to RFIs and sources saw it's a much quicker pathway to actually going from Zero Knowledge or zero contract with this particular agency to having my first opportunity with the agency. Why is that? The reason why I found it's easier for me in terms of or faster is because I'm not necessarily Expecting them to award me the or or give me an opportunity to bid the sources sought that I'm attacking or that I'm pursuing But what happens is it's one way again remember three pillars of success. It's one way in which we can Become acknowledged by that agency Increase their awareness of us have an opportunity to talk to them about other potential opportunities Build brand awareness. It's a form of marketing ourselves. So again People are looking for They're have solved they have problems that need to solve so the agency has a problem they need to solve They don't know who to turn to to solve it. They are essentially expressing their concerns Saying hey, we have this issue and we need help It's for anyone out here who can help us and even though you may not be able to help them on that They get to learn about your business learn about your company and realize that you could be a potential problem solver In another arena and so again, they have on their side, right? They've got their book let's say But all their opportunities and all the things are coming out and but again, they don't have anyone They don't have a go-to person. And so now you Submit a response to their market research and now they're saying to themselves. Hey, maybe potentially I have someone here who could be my go-to person Okay, and then that gives you the opportunity to talk to them have further conversation engage again if they allow it so Again, one of our pillars of success is definitely respond to sources sought Respond to RFI's and that's why we call it bid opportunities because it is an opportunity to eventually again We're playing the long game here, right? to have a sole source or simplified acquisition or Bid something that's not publicly listed Alright, just want to clear that up. So again going back to beta dot Sam You must be logged in in order to take advantage of this and once you're logged in We got a type of notices called sources sought and then I like to go back and look at a Weeks worth of data.  I Found on average about 500 results weekly there's five hundred forty three and The next step is really important because beta dot Sam is not efficient at all Which you want to do is you want to click download to actually download it and I don't do PDFs I do it in CSV. So that way I can manipulate the data And so I click CSV and click download and then it starts to download Right now once it's downloaded And again, I'm like that chef in the kitchen, right? Once it's downloaded What you will see is a spreadsheet that looks a lot like this and once you have that spreadsheet up Then you will see and you'll be able to easily scroll through all 500 opportunities as you can see I can scroll with my finger and a few seconds through all five hundred and forty three opportunities and ultimately That's the kind of power that you want to have and until beta dot Sam Fix their system. This is the best way that I found to be able to easily go through at least once a week and look at RFI's We have a another platform that we're using that we're beta testing now That will hopefully make it easier for all people or persons But for today, this is the most efficient way that I found to do it and then really we just start scrolling down and looking at the opportunities and What I like to do is I go like to go through a couple examples and show people out here what the stuff looks like because So many people are confused. So many people are unsure I'm gonna say this When you're looking at this and you see something that you like Make sure that you qualify if you do not qualify if you don't meet all the prerequisites it's not worth responding because They're looking for people who actually qualify to do the work. So Even though this is something that I highly suggest or recommend. I don't want people responding aimlessly That don't necessarily qualify if in fact you qualify You should respond if you don't qualify and maybe you can find a teaming partner To bring along to help you be able to qualify But again, just want to stress that if you don't qualify don't respond. Let's run through a few of these And see if we see anything that makes sense Design bill for a truck repair at a golf course in New Mexico Let's see social saw unit breakers Bonneville dam or a control system for radar attack or the radiation system US Army Corps of Engineers Sacramento's got some quality assessment testing BPA. Hold on. Let me pull this up Hey, I've got some people that do QA testing This might be good. I've got two people in my group that do QA testing. So what we want to do I normally will grab this I flip back to the other screen and then here on a key words I Copy and paste pull it up and then we take a look at this opportunity Quality assurance laboratory field testing services for the Corps of Engineers sources, so All right, and then here click on it pulls up the documents This is plugging it sending it to All right, and this is a source of an announcement tells you US Army Corps of Engineers Sacramento's looking for quality assurance testing personnel facilities equipment transportation materials the quality assurance laboratory field testing services We know a lot of people I know Three people at least in our group that does this And So here this is what they're asking to submit your business name and address Right. So these are the things that they're asking to submit This name address name recovery was in the title type of business cage code any contract vehicles That you may be on that potentially and then it says This information market research only does not preclude your company from responding to this notice So again, even if you're not on any of these vehicles That's not they're not saying for you not to respond. Let me kind of get out the way here You see this So it says here you should information interested businesses should submit a brief capability statement package addressing these questions no more than five pages So here they're telling you exactly what they need they're telling what they want And this is all of the information that you need to put together for this response. So Why should we do this because again All of this information you have you know your business, you know the address, you know your company You know you can't go so the only thing really that you have to Add on there is if you're in a contract vehicle and if you are you know that as well. So This is a very easy way to get in front of agencies to get in front of contracting officers To let them know that you're out here and you can provide services I'm gonna highlight this because I do have people in my group that I believe qualify for this opportunity. Let's keep going Rule-reparant installation of a tensile tester Mercy hazardous materials instant response Transportation vessel for personnel in stores at Pearl Harbor IT strategic plans Pre-solicitation bill for space munitions warehouse and office facilities general turtle services Let's see Something that stands out some more inspections to services This is for overhead hoist and mobile cranes leasing of office base. We see that every week Let's see what else is out here. They're doing something in the Middle East So it's Jordan We're building some lights Coast Guard in Puerto Rico Center for information technology wide area network optical services Quite similar facility barge IDIQ I Know someone as barges And yeah, I don't have time to go through all 500, but I just want to show you some examples A lot of time people actually use my videos just to watch and see If there's anything on her that makes sense to them. So I'll go slow Multi-family housing construction inspection services, I know people that do construction inspection services I could think of a couple offhand Renovate the Rosen control hangar up their net before Launcher and fry cleaning aerial demonstration. Oh, that's pretty cool. I see overhead ambulance services known as removal services COVID-19 sanitation and no it ships and Alaska ports by local companies gun mounts batteries Airbus hangars. I mean the government buy a ton of stuff transportation services. Let's see. Where's this transportation services at? Let's take a look at this trip JAA transportation services is that we always have people that are in that space Look over here. This is the fuels division. This is DLA trucking long distance All my trucking people, you know folks always ask me about this stuff By transportation services for turbine fuel aviation. This is Kona's work So you're gonna be providing fuel from designated defense fuel support point to designate it For its support basis via tank truck into tactical bags trucks are in tanks with content within the Continental United States as described so again This is something that I know we have people out there that could do it Back to our database medical regions in Okinawa, Japan parking and traffic control plans Davis for air show training support IDI cube Dean post. I'm not sure dimples is I'm sure there's some people out here that know what dimples training is. Let's see It's funny training help that support for TMM as software. If you know TMS as software The government's looking for training and help that support I'm telling you Lisa temporary dormitory dormitory and Sir AFS Alaska Probably doesn't fit a lot of people's needs. They're still looking for N95s out here Discipline feasible feasibility study Architect of the capital second kind of a perform a feasibility study to determine whether all ASC employees discipline All right, if you do feasibility studies discipline feasibility studies, this is for you HUD office renovation Brickle Plaza federal building Miami. Oh That looks like me me me me me We can do that. Call me. Where you at? In fact, I'm gonna send this over to my guy today. We're gonna go after this riot gear Another three by here to provide right here smart license SAP intelligent enterprise sweet transformation chemical analysis of biological samples for organic contaminants Generator of services at Twin Lake Data warehousing All right, we're approaching 20 minutes. I'm gonna kind of skip through and you guys get the idea I have a lot of fun doing this. Trust me. I really do like doing this because again Look stock order beds and mattresses. I have a mattress guy.  So and people that could do them. So when I see this stuff, it's like I've matched together Look, there's a man may talk for geotechnical services may talk for design build services And various construction projects for us fishing wildlife Another may talk for construction. So I'm gonna go back and send some of this stuff to my people These things don't make sense to me Purchase of aircraft going 737 700. I know people I know how to buy aircrafts So armored car services in Portland and Vancouver Window upgrades rental rental of portable shower trailers. I Think I I really believe that we should all be digging through this list once a week at the very legs It doesn't take long to do it. I could scroll through this list in about 10 minutes And I think it's a much more efficient effective use of your time than looking at jobs for bid And that's so I tell all of my gup on edu students to take a look at this RFI's list and respond and Time after time they get calls back. They get invitations to bid and they follow up With the office of the agency and set up with the small business offices Capabilities briefing. So this is a strategy that I encourage everyone to employ And put it inside their arsenal along with whatever else they're doing Integrated education delivery contract. Oh, we're looking at this one Definitely good this one integrate education delivery contract The GI bill and immediately procurement associate RFI has been cancelled. Ah, okay All right, so the digital form of the GI bill has been cancelled. You never know. I just again, you're checking to see what's going on All right satellite services microscopes Cylinders plumbing vocational training services we I've done HVAC vocational training services before So again this I mean You'd be surprised out here People that that have this ability to do these things that are not actually taking advantage of this We need more good contractors out there. I can never say it enough. We need more good contractors out there market-servey homesteader for space market-servey renovate buildings of a force for construction Market-servey is being determined to renovate some buildings 704 705 Let me take a look at that because again homes to the Air Force base is where I started my attorney Ungovernment contracting. So let me see if there's anything exciting here And again, you get to see What I do, I mean, this is This is what I do. I do the same thing that I tell you to do. Let's take a look Market-servey is being deducted to determine reasonable number of interest in small businesses to set this future product aside So the renovation is 2,700 square feet One to five million definitely Stuff we're gonna respond to so yeah, this is Definitely something we want to respond to right off the gate. So let's Let's get our letter of interest together. Let's get our Documents together so that we can respond. Let's keep going and we will finish up shortly like this my people combat and capability development command So they're looking for laboratory support VIS N5 Autodesk training. I know there's been none of these Autodesk I looked at all desk a long time ago There's some folks out there that are experts at this that can provide and help the government bring their training to the table Geospatial predictive analysis. I know people here that do stuff like that There's some lodging needs For hotels and motels Let's take a look at that and we will wrap up with the lodging needs today So over here, let's take a look at the lodging needs and we will close out with that Happy new year to everyone by the way. Hope you're having a wonderful new year I hope that 2021 is treating you well thus far And I'm hoping also that we can take you know I can help provide some encouragement and support the folks out there Along the way of their path and their journey of going government contracts. I love sharing success stories We have so many in fact one of our students yesterday announced in our Tuesday calls that he was awarded a A multi-year contract to provide the state of Georgia with electrostatic Planing services throughout the entire state one of 15 companies so congratulations to them for receiving that announcement yesterday Following up this last opportunity cover telecom case to put my services representation. I thought we're looking at log Okay, I pulled down the wrong PDF you guys. Let me put on wrong. You know I was trying to do two things at once talking to you about the student and then reading this. All right Here we go. All right. So the look there's a blanket purchase agreement BPA. That's an IDV We've learned about IDVs if you don't remember IDVs We've got a video on that The government could be awarding task borders against this BPA The call limit is 10,000 VP limits to 49. So it's really not that big but great to start off with The contrary to supremacy combinations in the Virgin Islands National Guard rental bases Candice we just spoke yesterday and we talked about Virgin Islands and having opportunities. This is perfect for you I'm gonna send it over you're in the Virgin Islands and we just spoke last night and I talked about how many Opportunities that I see for the Virgin Islands. So hey guys listen. Thank you so much I hope you enjoyed that video today. Welcome back to a new 2021 Make sure again visit our website go con giants comm so that you can be part of our email list it's very easy go to our website sign up and Join the 8,000 so other persons that are on our list Learning engaging and finding about any and all opportunities that exist in the federal arena We want you to be a part of this journey We want to be a part of your journey and we want to help you succeed So again, when you get a chance visit our website right there on the screen sign up for our newsletter Join a number one online community federal contractors. I'll see you in a couple days


National Association of Town Watch's 2015 National Night Out promotes crime prevention in communities around the world. In the case of Naval Air Station Siganella, it demonstrates the working relationship between U.S. and Italian security forces. Chief Master at Arms Troy Papito, Nishimi Security-leading Chief Petty Officer, says the event helps to build teamwork so that the community can feel safe on and off base. We come together to build a bond on anything to build relationships and awareness about crime prevention, security, any other types of events that go on within the community itself. The event showcased canine units, mounted patrols, explosive ordnance units, and demonstrated how well they all work together in unity. Papito encourages everyone to attend events like these and to get to know those who protect them. They can meet the people that they're calling. It kind of puts a face with the name. It builds familiarity, so it builds that friendship, that hand to reach out and shake. Coming from Naval Air Station Siganella, I'm Petty Officer Rebecca Sunderland.


Hey, what is up everyone? Happy Wednesday, May 10th, 2023. Nice green day today, plus $7.79 on four trades. Start off with a volume runner. Netflix actually wouldn't have been a volume runner if I would have waited a little bit longer, but it was kind of a weird situation. You don't see very often. I'll show you that in a second. Minus $2.20. Nice little drawback there. Then got into BABA volume runner, plus $200. Got into a nice Amazon trade, Amazon Osme plus $5.88. I'll show you that one. And then Roku. Amazon and Roku were both continuation runners, plus $2.11. Thought I might get more out of Roku, but it started coming down. Plus $7.79 on four trades. Start off here, Netflix. Netflix had this big bar. This bar here was green the whole time. Literally, there was 30 seconds left and it had pulled back to right here. I went ahead and got long. Then in the last 15 seconds, it dropped and turned into a red bar. I don't see that very often where it has this big push up and it's pretty much holding right there. Everything is pretty strong. Then it just dropped and turned red. When it pushed down here, it came up a little bit. I just got out because it obviously was not an upside volume runner. It ended up pushing up, but since gone down through loads of day. That was that kind of a, you just don't see that very often right there. So minus $2.20. Then Bobba. I think somebody mentioned this in the chat. Bar as big as the first. It pulled back and then I got, so I got long on this pullback here and then it started to come up and I got out a half on the push up and it started to come back down. I just got out of it. I was like, yeah, it's not really acting like a volume runner. Thank goodness it ended up having these two nice pushes here. It got me out a half and then I just ended up getting out of everything at the same price I got out of half ads. So then Amazon continuation runner. So push up. It was really holding. It was holding like right here. So I got, I jumped, I jumped in quickly, got, got long right here and I positioned myself so that if it comes down more, I can add to it. And so it came down. I added to it right here and I was going to cut it loose if it gotten down anymore. Then all of a sudden it pushed up and I just started scaling out as it came up and then it got this mighty 90 here. So when it started to come pull back and then I just bailed on it right here. So nice plus five 88 and then Roku little continuation runner as well. So I got long right about here.  I got long here and it came down here and I added to it right here and it ended up pushing up. I got out of half. I got out of a quarter and then it's just started to come down here. I wanted to see it stay above this pivot. As soon as it pushed through the pivot, I exited and you can see that was a good exit. So plus two 11 thanks to this ad. But man, if that would have taken off right there, it could have been a monster, but looks like we're getting a little flush right here. So probably a good thing. I ended up getting out of everything, but so that's my four trades. Hope you learned from them plus seven 79 and I will see everybody back here next week. The next two days will be Steve will be doing the zero DTE trades. So everybody have a great rest of your week. Great weekend and I will see you next week. Peace.


The Palestinian Islamist movement Hamas launched the biggest attack on Israel in years on October 7, in a surprise assault that combined gunmen crossing the border with a heavy barrage of rockets fired from the Gaza Strip.A video obtained by Reuters showed Palestinians taking out what appears to be a dead body of an Israeli soldier from a tank. While Palestinians cheering on the borders between Gaza and Israel.AS warning sirens sounded across southern and central Israel, including in Jerusalem, Israel's military said it was on a war footing as Prime Minister Benjamin Netanyahu called an emergency meeting of security officials.Saturday's incident marked an unprecedented infiltration by Hamas gunmen into Israel from Gaza, and was the most serious escalation since Israel and Hamas fought a 10-day war in 2021.


Myself, P. V. Ekhande, working as an assistant professor in Department of Mechanical Engineering at Vulture Institute of Technology, Solapur. Today, we will go through the problems related to the projections of planes where the strike and dip of the plane is given and we will be completing the projections of the plane from the given data and certain part of the figure will be also given to us. At the end of this session, students will be able to draw the problems of projections of planes related to strike and dip of the plane. Let us see this problem where the top view of the plane is given in which P H, Q H and R H these are the three corners of the triangular plane P Q R and P F point is known to us. For this, the question is like this, draw front view of the triangle ABC rather we will consider here as a triangle P Q R because the points given are P Q R having strike south, 60 west and dip angle is 45 degrees and dip direction is north, westerly and for this figure which is given to us is top view of the P Q R and front view of the point P F is given and we are going to complete the front view of the triangular plane P Q R with the known strike, known dip angle and known dip direction. Now the first step is to draw the strike line of the plane in the top view. You know that the strike line is always to be obtained or always obtained in the top view only where this strike line has got the angle 60 in between west south and west direction because strike given is south 60 degrees west. So this direction is south direction, this direction is west direction and the angle given is 60 degrees angle. So the angle 60 degrees with respect to P is to be considered. Now this angle 60 degrees will consider with respect to pH. Now this pH point with respect to this, the angle 60 degrees with vertical line is to be considered because the angle is from south to west. So this south to west direction angle will represent strike line of the plane. So this is strike line of the plane which is nothing but the horizontal line from the plane or true length of the line which is called as a horizontal line which will be having the parallelity with respect to ground or with respect to HRP and this line is called as a strike line. Now to this strike line we have to consider plane perpendicular for obtaining its auxiliary view where we can get the edge view of the plane. You know that the edge view of the plane is obtained when we are considering the true length line from the plane to which we are taking the auxiliary plane. Here the auxiliary plane is H1 and this auxiliary plane is perpendicular to this strike line and strike line is nothing but true length line of the plane which is a horizontal line. To this when we take the plane perpendicular we will get edge view of the plane on this side. Now to obtain this edge view of the plane, first we have to locate the point Pf which is to be transferred from xy line or fh line. Now this point is at 21 mm distance above HRP. This point will mark on the line drawn with respect to pH and this is a position of point P in the auxiliary plane number 1 so we will call that point as a P1. Now with respect to this P1 point now where to complete the dip of the plane. Now for completing the dip of the plane where to first consider the dip direction. Now the dip direction given is north westerly means from north direction towards west direction the plane is having inclination. So this dip direction where to represent in the top view as a line perpendicular to strike line which can be represented at this position with respect to P point or we can represent the dip direction anywhere with respect to strike line as a line perpendicular. So this line is representing dip direction. So this dip direction in this direction the plane should have a downward inclination. What is mean by downward inclination if we consider the man standing on this plane when the position of man is considered on this plane which is the horizontal plane and one plane intersection if the man is standing on the horizontal plane his position on this side can be also obtained in this way because we are transferring the points on this side towards the auxiliary plane or from auxiliary plane we can transfer the point on the front view side. Now when you consider the man standing on the horizontal plane this is the head of the man, foots are on the bottom side which are touching to the horizontal plane the same thing when we transfer from this side towards this side the foots are touching to HRP the man is having the head on the top side. So this way we have to consider the position in the downward direction for the line for the AG of the plane which is nothing but the line observed over here as a line having the inclination towards the HRP or towards the ground. Now this angle is 45 degrees now this 45 degrees is to be considered with respect to horizontal line where to always consider the angle with respect to horizontal. In this case it is 45 so with respect to this when we consider 45 degrees it will have the 45 on the opposite side also that is a vertical line but when the line AG angle is suppose deep angle is 60 degrees in that case this 60 degrees angle should be considered with respect to this horizontal line means the line will have the 60 degrees angle with respect to this line from this will take the angle 60 if the angle is 60 if the 30 in that case we have to consider 30 degrees angle in this case it is 45 degrees so we will draw the line at 45 degrees angle with respect to this so this line is the AG of the plane. Now this line is representing AG of the plane now this AG of the plane is making angle 45 degrees with respect to ground so this angle is 45 or at this location also when you consider that angle is 45 degrees so this 45 degrees angle is a deep angle deep direction is a north westerly and that is why we are taken downward inclination on this side if the deep direction is suppose south easterly in that case the south towards east that will have the perpendicular line and this direction is the direction in which we have to consider the downward inclination means the plane AG will be drawn in this way in that case it will have the downward inclination on this side with respect to the man in this case with respect to that man were considered inclination in this side inclination is considered in this direction because it is north westerly if it is south easterly in that case it will have the direction in this way and in this direction the angle is to be completed for the AG of the plane. Now once we complete the AG of the plane over here with respect to this AG of the plane with on this AG of the plane will get the remaining two points and for obtaining remaining two points were to draw the projector from these points this point is a point RH from which we have taken the projector the intersection over here will have the point R1 similarly when we consider the projector from Q the projectors are always 90 degrees to reference line so these are the three projectors which are completed at 90 degrees now on this projector the intersection is over here so this intersection is Q1 point now the point R1 to Q1 that is AG of the plane so this much length that is from R1 to Q1 is AG of the plane so this AG is auxiliary view now were to locate RF and QF point in the front view by transferring these distances now first were to draw the projector of RF on the projector of RF sorry RH will get the position of RF on the projector of this were to now transfer the distance of R1 now R1 has got distance 10 millimeter 10 point 11 millimeter so this 11 millimeter distance when we transfer on this side will get the position of RF now this transfer of the distance were to consider with respect to with the help of compass with the help of compass were to mark the distance on this side similarly for the another point Q will have the projector from this side now on this projector will transfer the distance of Q1 with compass or we can take the scale now the distance is 50 millimeter so this 50 millimeter distance will transfer on this side now this is the position of QF point now once we connect these three points that gives us front view of the plane PRF or PQR so this is completion of front view of the plane top view is already done already given to us so with the known data like this we can complete the projection of plane and in the other way also we can go for the projections means the front view will be given to us a point in the top view will be known to us were to complete the top view with the given strike and dip of the plane have you understood how to complete the projections when the strike and dip is given and one of the view and one point is given in the adjacent view for this the reference which has been taken is from the engineering graphics book by a professor Deshpande which is a book of the Mahap Lakshmi publications thank you.


I know that they are right. So, make time for each other.  Make that normal, right?  I know that there's social norms and that's okay. But so, you know, not not only should that be displayed amongst before your kids that they can see that that's something healthy to look forward to, but that's a very important touch point for you and your spouse.   Do that once a day as much as it is possible. Try to have that five, 10, 15, 20 minutes of having tea together, actually talking something beyond the bills and who should have done what and how come you didn't do the dishes and look at the trash that's outside and you still didn't fix the leaky pipe. What's wrong with you, right? Beyond all of that, connect, connect, connect. Then when you're, when, when, when, when troubles happen as they will do as Suhail mentioned, and as you mentioned, it's natural. Those fights are going to be less caustic, C-A-U-S-T-I-C, right?   We don't want to be mudslinging. We don't want to be nasty towards each other, name calling. So the more we can connect with each other in a loving way, build that friendship, spend time together, ask each other questions, like get to know each other, always there's things that are changing. As human beings, we change all the time. The nature of our relationship will change all the time. So keep up to date with, you know, what they like, what they don't like. Try to facilitate that both husband and wife, right? Speak the love language that your spouse speaks. And that can really, really strengthen foundation so that when tough times fall, as they will, it doesn't really crumble the house, inshallah. Allah swt says, that we have taken from you, O men, a weighty, heavy covenant as it regards to your women. And so marriage is a serious matter, right? And it's not something to be taken lightly. We don't, at the slightest, you know, at the slightest difficulties, just, you know, overdramatize and catastrophize what's taking place in marriage. And to make marriage work, there's a nice saying. They say that marriage is not about getting what you want, but marriage is about wanting what you get. And what that means is, everybody's mind is spinning. What does that mean? Marriage is not about getting what you want. You can't mold your spouse into the person that you want them to be. But it's about getting what you want, meaning wanting what you get, even I did. It's about making the best of what you have in your relationship, learning your spouse, understanding them, loving them for who they are, not who you dream them to be, and putting your energy into that, accepting their shortcomings. The Prophet, he told us that a believing man, a husband, should not despise their wife in kariha minha khuluqan radia minha akhar. If there's something that you don't like about her, then there's other things that you like about her. Focus on the positive, right? And marriage is so much of that, just focusing on the positive, accepting them for who they are, loving them for who they are, and may Allah Almighty bless you all.


What I got from Genesis and Exodus is that God is a narcissistic, egotistical, that does whatever he can to make sure everyone knows his name and knows how scary he is, and big and scary, and evil, and he has so much power. Hey man, can I share something with you?  I've heard others accuse him of being prideful or self-centered, but let's think about it for a second. When you're prideful, egotistical, narcissistic, self-centered, why is that a bad thing? Well, one aspect is that the attention and praise that you're pouring on yourself is misguided. You are not the most important thing in the universe, therefore the hyperattention on yourself is not justified. But God literally is the most important being in the universe. He is the Alpha and Omega, the beginning and the end, the Almighty Creator. So when God tries to get our attention, it's not only right, but it's also a blessing to us because he's pulling our attention, he's reorienting our attention off of lesser things onto him who is the best thing. Our gaze reorients onto his glory, his beauty. When we try to get the attention for ourselves, we're revealed as a fraud when our flaws are exposed. However, when God demands our attention, we are met with an all-consuming love that does not disappoint. Follow for more.


The good, the bad, and the algae, presented by science at NASA. Algae are complicated. The little plants can be both good and bad. Single-celled algae called phytoplankton are a main source of food for fish and other aquatic life, and account for half of the photosynthetic activity on Earth. That's good. But certain varieties, such as some cyanobacteria, produce toxins that can harm humans, fish, and other animals. Under certain conditions, algae populations can grow explosively, a spectacle known as an algal bloom, which can cover hundreds of square kilometers. For example, in August 2014, a cyanobacteria outbreak in Lake Erie prompted Toledo, Ohio officials to ban the use of drinking water supplied to more than 400,000 residents. In the United States alone, freshwater degradation from bad algae costs the economy about $64 million a year. NASA, the U.S. Environmental Protection Agency, National Oceanic and Atmospheric Administration, and U.S. Geological Survey are doing something about it. NASA has long used Earth-observing satellites to locate algal bloom outbreaks in the ocean. But now, this unique satellite data will be routinely produced in a form that helps U.S. water quality managers monitor our fresh water. Water quality managers will soon, with a peek at their cell phones, have an answer to, How's the water? The four agencies are working on a joint project, sponsored by NASA, to transform satellite data into an indicator of cyanobacteria outbreaks in our freshwater supply. The data will be integrated into an EPA Android smartphone application so environmental officials can see, at a glance, the condition of a specific water body. With our app, you can view water quality on the scale of the U.S. and zoom in to get near real-time data for a local lake, explains the EPA's Blake Schaefer, principal investigator for the project. When we start pushing this data to smartphone apps, we will have achieved something that's never been done, provide water quality satellite data like weather data. People will be able to check the amount of algae bloom like they would check the temperature. Here's how it works. A harmful species of cyanobacteria emits chlorophyll and fluorescent light at various points in their life cycles. Landsat and NASA's Moderate Resolution Imaging Spectroradiometer, or MODIS, can detect these ocean color signals, which reveal the location and abundance of cyanobacteria. The project team will collect this data for freshwater bodies and convert it into a form accessible through web portals and the EPA mobile app. In addition to MODIS, they'll draw data from the European Space Agency's Sentinel-2 and Sentinel-3. With early warning about a developing bloom, officials at water treatment plants will be better able to determine when, where, and how much to treat the water to keep consumers safe. That means unnecessary and expensive over-treatment may be avoided. The data will also help park managers alert swimmers, boaters, and other recreational users to hazardous conditions. Says NASA Administrator Charles Bolden, we're excited to be putting NASA's expertise in space and scientific exploration to work protecting public health and safety. The project will also help scientists understand why bad algae outbreaks occur. By comparing the color data with land cover change data, they'll learn more about environmental factors that spur algal growth. The result? Better forecasts of bloom events, so we'll know when an algae bloom is safe or harmful. For more news about complicated microbes, on Earth and possibly beyond, stay tuned to science.nasa.gov.