Here we go. Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Officer of DataVersity. We would like to thank you for joining this DataVersity webinar, Optimizing Solution Value, Dynamic Data Quality, Governance, and MDM, sponsored today by Precisely. Just a couple of points to get us started. Due to the large number of people that attend these sessions, you will be muted during the webinar. For questions, we will be collecting them by the Q&A. Or if you'd like to tweet, we encourage you to share your questions via Twitter using hashtag DataVersity. And if you'd like to chat with us or with each other, we certainly encourage you to do so. And just to note, Zoom defaults the chat to send to just the panelists, but you may absolutely change it to network with everyone. And to find the Q&A or the chat panels, you may click on those icons found in the bottom middle of your screen for those features. And as always, we will send a follow-up email within two business days containing links to the slides, the recording of the session, and additional information requested throughout the webinar. Now let me introduce to you our speakers for today, Chuck Kane and Sue Pollock. Chuck is the Vice President and Product Management at Precisely and is a 20-plus year veteran of the IT industry, having worked across multiple industries, such as commercial banking, insurance, manufacturing, government, and consulting. Chuck has led multiple data consulting practices, delivering high-value client engagements, leveraging IBM, MDM, Initiate, and Informatica being most recently at Tata Consulting Services before joining Precisely in 2014. Sue is the Senior Manager of Product Marketing at Precisely. She has over 15 years of experience coordinating marketing strategies that unite teams behind value-driven solutions. Sue is passionate about creating messages that is not full of jargon and techno babble but easily understood by business and technical users alike. And with that, I will give the floor to Chuck and Sue to get today's webinar started. Hello and welcome. Hello, and thank you so much. I am going to share my presentation real quick. Just make sure I have the right presentation up. Looks good. And I do believe I do? Yes. All right, great. Thank you. And thank you, Shannon. And thank you to the audience for attending today's session. We do have a lot to cover. And we hope that what you see today and what you hear is engaging and informative. So let me make sure I get on the right screen here. As you know, as is introduced, I'm Chuck Cain, Vice President of Product Management for the Verify Portfolio. And I'm going to be joined here with Sue Pollock, who is the senior manager of our product marketing. And Sue and I work really well together almost on a day-to-day basis. So organizations rely on trusted data to make good business decisions. As they drive towards being a more data-driven organization, there are some trends that we see and some key business initiatives that evolve around the transformation of customer experiences. We see applying AI, artificial intelligence, to proven business cases, to support driving new insights and increasing efficiency. We see the power of leveraging location to be able to solve new business problems. And we also see that the business, to make sure that the business is securing a plan and that the data is actually being managed most effectively. And each of these initiatives heavily depend on an integrated, clean, accurate approach to contextualize and enrich information in order to be able to drive maximum benefit into the organization. So data is definitely fueling if you will allow the various different decision making that we make today. Now, one of the things that we look at is historically data problems were addressed by point solutions that solve specific data challenges. These types of solutions address data quality, master data management and data governance, sometimes together, but oftentimes in isolation or in pockets within the organization. The main issue with point solutions consists of a couple of main problems. One is not all solutions work well together. So you might not have a good data quality solution that maps to a data governance solution or to a data governance solution that maps to a master data management solution. And so oftentimes they work in these silos and don't deliver on a complete and accurate picture. And the quality and understanding of the context of around that data ends up being somewhat of a challenge. And so what we really are looking at driving is more of a business-focused, a business value focus where each organization has data that should be used as a positive earning asset to support increased revenue and support accurate decision making and alignment around the strategic initiatives. But often we see that not having a fully integrated data quality, master data management, and data governance program does lead to challenges where there is money left on the table. And what we mean by that is the costs are really high to be able to achieve the results. The decisions that come out of those solutions are not fully aligned to the business initiatives. And you end up having top talent and subject matter experts aren't always engaged on each and every of these projects to help with some of the data stories or some of the interpretation around that. And so what when I was talking about earlier is this evolved approach around business value focus. As a whole, the industry is beginning to transform from being a more point solution focus to driving more towards the value drivers around the business. And not only in driving data across organization but driving them out of silos. So this evolution is important because business value is expects solutions with integrated capabilities that account for both agility and flexibility. So in this session, what we're going to be talking about is various views of business goals that our customers and we have seen that are driving the evolution of data quality, master data management, data governance in what we consider today's business operating environments. Key areas that we'll see as part of this evolution is around the data modernization, around key initiatives that are powering customers to leverage their data as an asset. We're going to talk a little bit more about the single view of a customer, which is that intersection between data quality and master data management along with data governance in support of a single view of the enterprise capability. And when I say single view of the enterprise it's really beyond just the single view of a customer, single view of a location, single view of a product or services, it's really how do we tie all these things together to better drive out enterprise decision making. Customers are also evolving their approaches around data on the move to increase the trust around the data and data transformation projects around mergers and acquisitions. And as well to system to system data movements all of these around the operational and evolving operational value with more automated, robust and certainly if you think about it existing data quality solutions that increase operational efficiencies. So in this first segment, let me make sure I get this to the next slide. In this first segment, we're going to discuss how an integrated approach supports the evolving nature of data monetization. So what I would like to do now is I would like to introduce our next speaker, Sue. As we talk about Sue, Sue has extensive experience on positioning multiple data monetization programs that leverage the intersection between data quality and data governance. So Sue over to you. Thanks, Chuck. As Chuck just said, data-driven organizations are increasingly seeking to leverage their own data as an asset to generate measurable economic benefits or monetize the value of their data. In a recent study, data professionals speak trends in data governance and data quality. It was reported that improved data quality is the leading benefit of data governance initiatives. And that does mirror what we're hearing from our customers that data quality that's deeply integrated with data governance works together to deliver business data that they can find, understand, and more importantly, trust. This enables confident decision-making, operational improvements and taking action to comply with or even leverage regulatory and regulatory requirements to improve their bottom line. Looking at an example of one of our customers and independent wealth fund was looking for a significant improvement in the way that they source, manage, and use data to better inform their investment-making decisions. They created an office of data to improve the effectiveness of the management of their operational data. But then they quickly realized that for them, data governance, data quality, and even data reconciliation were the key building blocks for increasing maturity of their data program to increase data literacy and monetize those data assets. We partnered with them to provide data quality and governance capabilities, allowing users to find data quickly, understand the context and the quality of their data, and then ensure that their data is managed as a strategic asset for the organization. Additionally, partnering with them to build a measurable strategic plan, leveraging our strategic services made sure that they were achieving their goals. And this was an integral part of their initiative, tracking those KPIs and those goals. Currently, they're also exploring data observability. This is capability to proactively uncover data anomalies and take action before they become costly downstream issues. In another instance, one of our consumer packaged goods customers was struggling to find ESG data that was useful, well understood, and accurate. ESG, as you probably know, stands for environmental, social, and governance factors that determine the sustainability and ethical impact of a company. Very, very hot topic. But this could describe any initiative around any regulatory requirement. We work with this company to design an ESG governance framework that measures the availability, usability, and the integrity of their sustainability data. To accomplish this, they needed the capability to discover, catalog, measure the quality of, and then identify the supply chain of their critical ESG assets. They also needed to build an automated organizational workflow model to ensure the business accountability. So ownership and execution around that data was important to track. Ultimately, we delivered cataloging and governance capabilities, allowing full visibility into the context of the data, that is like the policies, stewardship, lineage, history, and data quality results around all of their sustainability data. And from there, they were able to increase the accuracy and frequency of their sustainability reporting. And additionally, we're able to improve the visibility of ESG information for the leaders and decision makers across the business for better and more timely business benefits and insights. Chuck, back to you. Thank you, Sue. And what I would like to do now is transition to the intersection, as I was discussing earlier, of data quality and master data management, along with data governance and support of the single view of the enterprise. So this next one is a bit of a build out where we're really referring to here as the initial capabilities and or support of where you really have this initial intersection between data quality and master data management. In fact, I often have you data quality and master data management as two sides of the same coin. In order to be able to get to a true golden record of entity, I first must solve for the problem of applying good data quality techniques to master data. These data quality rules are often defined and governed by the data, such as matching and consolidation. But we also need to be able to start to think about how we actually tie these entities together across the enterprise in support of these various personas and these personas describe the relationships that an individual might have or how they might interact with you. So for an example in financial services, we see many different use cases where business owners also have personal accounts and vice versa. And so what we wanna understand is the persona and the interactions around those personas so that we can fully describe, if you will, the relationship and those interactions across the organization. And really why we wanna be able to do that is it helps us to be able to drive out these customer centric insights. So together we take all of this data to support and optimize the overall experience and provide insights that are both predictive and accurate. And so when we think about this single view of data, we think about the single view of enterprise or a single view of an individual and organization. This is one example where we looked at a, we have an example of a single view of a merchant. So as we move forward with this first example, I'd like to talk a little bit more about this for financial services. So as is the case with any business, especially large companies who have collected data over long duration and say, you know, decades, we find that the value of data is locked in these various different data silos I was referring to earlier of information and these data silos, when we are able to break them down and start to connect them, help us to better understand these insights, help us to better understand the outcomes. And so within this use case, we're able to unlock those silos and support a better understanding of merchants and the locations in which those merchants were actually operating in. And by doing so, we're able to transform these data assets or transform data into assets that drive business decisions and unlock, if you will, further sales, sales opportunities and growth across the organization. Really what we're looking at here is also a solution that includes not just data quality with single view capabilities such as a matching capabilities, but looking at that location, understanding the specifics of that location and enriching information based on that location. And further is to be able to support both on-premise. So there was capabilities that were required from an on-prem with a traditional data warehouse to also scalability inside the cloud. And so as Sue was talking about earlier with some of our data integrity suite, we've actually been innovating and bringing technologies into the marketplace that enable us to run not just the data profiling, data observability, but also looking at where we do geo-addressing location, if you will, enrichment and be able to drive that operational value across the entire enterprise. In the next use case, what we're gonna talk about more is about a multinational oil and gas company. So this is one of the world's largest providers of chemical and as well other types of investments across a very, very large global workforce exceeding 60,000 folks. And so the challenge here is that MDM is vital to well operations, but it's also vital to the investment that the organization is gonna make. And deep water assets, as well as other domains of data and information. And so today their existing processes in which they were actually handling some of this master data was that the data wasn't linked together. There was issues around understanding the critical data of these multiple systems for day-to-day operations. And I'm sure many on this call have witnessed this is require a lot of IT support in order to be able to derive value from that data, as well as the integration across these systems were very inefficient. And by introducing and providing if you will a master data management at Data Hub, we're able to support a lot of the business value that you see here, which is creating that golden record for now what is considered up to 10 domains of data. And some of these domains include vendor, location, equipment, customer and material domains, but also enriching and exporting that data across systems. So having system and system consistency and ensuring that data quality is the same across these systems and you have the same types of insights and outcomes, but also enabling integrations across multiple source systems both on-prem as well as across the cloud. And so there's a lot of value that we're as able to be delivered through the support of just a master data management solution that's paired with data quality that is governed by the rules of the organization to understand exactly what these things are and how those things are described as part of these various views of the business relationship as a whole. So with that being said, what I'd like to do is next bring it back to Sue who will talk to us some more about evolving data on the moves. So Sue, back to you. Thanks Chuck. Another way that we're witnessing the evolution of data quality and data governance is through the recognition of the importance of data on the move. Data on the move is really any type of data that's not considered to be in its final destination or in its final state. This is basically transitory data that's moving through multiple locations or for one format to another. Let's take a deeper look at examples of how organizations are evolving their data on a move. Data on the move includes a number of different key business initiatives from data transformation and modernization projects where data is moving from legacy or on or third party sources to the cloud or other destinations to help further realize any greater business value. This also may include any data that may be altered while hopping from one source to another. And it could also be moving any type of data from mainframe to the cloud via Kafka or some type of API or web service. Another huge piece of data on the move includes movement of data related to M&A, mergers and acquisitions that demand accurate and consistent mapping and transition of data to quickly capitalize any business value of that M&A. Finally, data on the move may include simply monitoring and observing data quality and anomalies as it moves across your organization between systems and processes to ensure quality and consistency. This includes monitoring from system A to system B or system B to system C or even from system A to system C to get the full breadth of the picture of where your data exists. Let me walk through a few customer use cases to learn about how to share how they are approaching data on the move with a more evolved approach to data quality. Auto owners is a regional property and casualty insurance company that provides life, home, car and business insurance. They serve over three million policyholders in 26 operating states. And the challenge that they faced was within their financial claims division related to data modernization and the movement to a large data warehouse. Their main goals were to, number one, improve the quality of their data and number two, balance and reconcile their diverse and large data sets. Their main drivers were to modernize their data streams to support their admin system modernization and to provide more accurate and reliable data for corporate reporting and analytics. The part of our solution that was a deciding factor for auto owners was having an out of the box workflow within the tool that helped them get to the right identified data owner stakeholder in order to fix data in a timely fashion so that reconciliation piece. Another great outcome of the solution was that they initially thought that they were gonna have to do two separate RFIs to deal with this, one for data quality and then one for the reconciliation piece. So through the evolution here and after reviewing our solution they determined that our tool was able to satisfy both cases for data quality and reconciliation and they were able to consolidate the vendor selection process using our solution. Let's continue to our second use case here. This midsize health insurance company is a not for profit that serves over 4,000 members across their entire state. The challenge that they faced was that their existing claims process resulted in missing late and even duplicate claims that ultimately led to several compliance fines as well as very poor member experience. This problem was even escalated to the CEO who wanted to put it in place the proper monitoring and validations to ensure this would not happen again. Their main drivers for their business was to reduce their compliance risk and they ultimately wanted to strive for a zero compliance risk fine environment that was their ultimate goal. As a result of selecting precisely this customer was able to provide monitoring over all of their claims and 100% of the claims across all of their systems and interfaces and across all the data hubs in which their data is processed. This gave them better insight into any of the escalating issues that might have been faced by poor data quality within their claims process and it did drastically reduce the amount of reconciliations mostly manual reconciliations that occurred over the weekend for them. So they were able to achieve their zero fine environment that they were going for regarding these statistics. The next topic that we're gonna talk about in the evolving nature of data quality is evolving operational value. Evolving operational value is something we see consistently in customers using our technology to quickly solve complex operational picture challenges. These solutions can take the form of data quality issues already described we've already talked about or complex data integration of data augmentation processes to complete missing data fragments or create an operational picture pattern as we've heard described by our customers to close that gap between perception and actual fact. Data ops is an emerging discipline of many organizations but the constant is resolving the demand for business value and data integrity to increase the operational value of the data assets we're creating. One aspect of our value contribution is enabling teams to react quicker with automation eliminating time consuming and error prone processes. Precisely supports data operations and now evolving data ops concepts by simplifying the cycles to create data assets that are fit for purpose, fit for use immediately. The result is providing trusted operational data with greater efficiencies and a more complete operational picture. Examples of attributes that make data more fit for use include product interchangeability, matrix solutions that include what products are capable of what, assets and field attributes, customer demand recommendations, what products recommended not just by social association but by actual buying patterns and also known purchased items and compatible related items. We also see around supply chain management we see demand to consolidate vendor performance metrics and actual demand forecast to rapidly identify supply gaps and top performing vendors. In the example you see in front of you this large healthcare organization had an initial base business need to validate addresses beyond just a mailing address. The evolved operational processes made the data more fit for use and solved many other operational gaps. In this case, it included the data recommending radiation and data management functionality to quickly correct data integrity issues thus driving the adoption of a larger solution through a correlation of multiple data sets and a more holistic operational picture. Specifically, we leveraged position association looking at practice attributes, building in the dimension of time which is critical and the association of the physicians and their areas of specialty, the location of their practices, understanding what rights doctors had to work in certain healthcare facilities. And then we even needed to factor in drive time distance which is also critical to this customer. For healthcare providers having data traceability and a clear understanding of the validation and standardization methods is critical. Black box solutions and fuzzy data associations many times create undesired research efforts. And one of the dominant strategic benefits for precisely technology brings is minimizing predefined taxonomies, data producing methods, processing methods that force customers to customize and adopt the non-optimal business practices or technology frameworks. Our second example is around data integration of data quality issues. And we're gonna talk a little bit about this. Data integration of data quality issues share many of the same characteristics and business impacts that Chuck described earlier when we were discussing single view of data. It's kind of a different side of the same coin. But resolution of these issues can be resolved in many different methods. The power that precisely brings to the market are a collection of best of breed technologies to meet individual organizational challenges not forcing your organization to adopt one technology over another. To highlight our capabilities we chose this complex manufacturing data integration business challenge. In this scenario, there is not just one source but this is a multi-source system issue with a timeliness issue of operational logistics. So the complexity of taking multiple systems in this case, product, customers, vendors, location and employee data domains, tying them together and providing an operational picture throughout the dimension of the transaction as one of the critical elements the customer wanted to resolve. Here we were able to incorporate advanced addressing validations and enrich them with geolocation intelligence that was leveraged throughout the transaction. These types of solutions incorporate the need of data consistency across multiple systems and the creation of multiple operational pictures in near real time. This approach is to prevent data gaps and increase the offers of operational awareness across those multiple domains. The primary benefit to the client is the focus on the fit for use data resolution at the beginning of the operational process and then subsequent refinement of the data to mirror the operational picture demand throughout the entire transaction. The solution approaches well beyond the aggregation of metrics or analytics or mastering a few data elements or just traditional data standardization. This approach drives data driven decisions throughout the entire operational chain once again, evolving it to the next level. These types of solutions are just one example of how precisely delivers a complex solution using configurable, agile and highly integrable technology assets whether they're precisely branded technologies or if they're existing client side technologies which we can also work with. So with that, I'm gonna turn this back to Chuck to summarize our message. Thank you, Sue. And as we started in the earlier part of this conversation is these use cases and driving off this evolving value evolving value around insights across many different types of industries. But very interestingly enough, really each of those we're trying to get to the same benefits and the benefits really are optimizing those business decisions, gaining, if you will, clear alignment around strategic direction as well as the execution accelerated time to value as well as the improved engagement of top talent on both the strategic and innovative initiatives across the organization. And as Sue was talking about earlier is through this evolved approach is really thinking about data integrity from an end to end capability in the sense that what you really wanna do is integrate which is to modernize, if you will, your infrastructure either for the cloud or to eliminate the data silos or to automate existing business processes to also validate that data and build around that the appropriate data governance and quality initiatives and make sure that those are built as a data-centric process to both ensure accuracy and the consistency of that data to leverage, if you will, location. And location is an inherent asset to your data which you can actually derive a lot more sophisticated analytics and if you will actionable insights based on where that location is or where interactions happen and then in the enrichment component which is to compliment a lot of your core business data with expertly curated data sets that can add that additional layer of critical context which really can help to drive increased value. And when we think about data integrity as the integrate, verify, locate and enrich it wouldn't go without saying that we want to engage and certainly drive a seamless what I consider a personalized omni-channel experience where you make sure that you're able to communicate consistently across any medium at any given time and really be able to engage at the right time with the right message to the right individuals or the right, if you will personas that you are targeting. So with all that being said I'd like to now turn it back over to Shannon who will actually help us with some of the questions. And Sue, thank you so much for this great presentation. If you have questions for them, feel free to submit them in the Q&A portion of your screen and just answering those commonly asked questions just to know I will send a follow-up email by end of day Thursday with links to the slides, the recording and anything else requested throughout. You all are being very quiet here but let me dive in here. What cloud-native technologies can precisely work with? Yeah, so I'll take that one and Sue, you can comment on it any further. When we think about cloud, we're really thinking about two aspects of cloud. One is there's the azures of the world, the AWS's, there is GCP for Google and certainly each of those have their own pluses and minuses as it pertains to the deployment capabilities of how organizations wanna integrate and leverage each of those clouds. But there's a second, I think facet of cloud which is what are we looking to try to achieve? Are we looking for operational value? Are we looking specifically for analytical value? Are we looking to try to hedge our bets between the two? And so in thinking about the cloud, we also think about the elastic nature of the cloud and what we mean by elastic nature is to support the organization's ability to scale up as time and as the requirements require or to be able to scale down and save money. So think about various promotions that you might do during a Super Bowl or doing a sporting event or during any other type of big event. You may have a large volume of data that's gonna come in from a seasonal perspective. And so you want that elastic nature where you can scale up, where you can support that. But then you don't want those systems just running because you may not have those campaigns, you may not have the volume. So you want it to be at a scale down and you want it to do it intelligently, right? So you don't wanna have to think about when you scale up or when you have to think about scaling down and you need this to be sort of in this elastic auto-scale capability within the constraints of how you position the technology. So I think that is another facet. And then a third component of this is thinking about the various, if you will, data warehouses that are out there. So you might have a traditionally warehouse that you built in-house but you might be thinking about and looking at leveraging let's say a modern data warehouse like Snowflake. So you might want to have data processes that are gonna run native to a Snowflake environment. You may wanna have data processes that run native to a let's say a Databricks environment for analytics or for other outcomes. And so I think this third facet of this is both the ability to be able to run next to the data so you're not extracting the data, you're able to maintain the data in that single source. And then I think the fourth component of the cloud is all about when you think about enrichment. So in thinking about enrichment, there's lots of various different data providers that are out there. Precisely is also a data provider through our spectrum on demand. And so there's an API capability that needs to support the say a validation of an address or a data enrichment around that address or being able to support various different facets of data enrichment, which could be a name and or email and or phone or other types of information validation. So there's a lot when we think about the cloud as to these various perspectives and how you actually might consider, you know these integrations both as a hybrid capability. So thinking about, you know you might have some on-prem solutions that tap into the cloud. That's what I was considering with like spectrum on demand versus cloud native which you're actually deploying the capabilities inside these cloud environments to support those types of operational outcomes. Hope that answers the question. Definitely. And certainly can have people ask additional insights if they would like some more information but moving on down the line here, you know how we get this question a lot in all of our webinars and all the context and it's always good to get a new perspective on this. How do you overcome the difficulty of getting buy-in from leadership for allocating resources to enrich data? So do you wanna start that off? I do, I do. And actually I do wanna talk a bit about in a number of the use cases we mentioned our strategic services team. And the purpose of the strategic services team is to make sure that you have an organized plan, a business case that is measured and that is reported back on and that you have a game plan so that as you're moving forward you know that you are meeting your goals. Now that doesn't directly answer the question about what we're talking about here but that is the problem that we're looking at, right? Is that anytime you're looking at bringing in any kind of data initiative whether it's enrichment, whether it's governance whether it's quality. If you don't have a strategic plan that is going to resonate with all of the influencers up and down the organization it's very difficult to move forward or it's very difficult to move forward and continue to understand are you reaching the real value that you need?  We are an unusual company in that we have our own strategic services team. We know data intimately we have a number of people who are previously CDOs and in larger organizations who now will work with our customers and with our prospects to make sure that number one we've clearly defined what the goals are. What are we trying to do? Are we trying to enrich? Are we trying to bring in governance? What's the purpose? What's the goal? What are the things that we should be measuring so that we can document that value? And in our solution we innately do that document the value and then have it reported on so that you are actually making sure that that business case is being realized. So the question is once again how do I build a good business case? It's not as easy as it sounds, right? Just because you have a pain it doesn't mean you can go out there and say here's a solution and make sure that you're gonna be getting that kind of buy-in. But it really is about making sure that you have a strategic plan and measurement of that strategic plan so that you can make sure that you are delivering on business value. Now the short part of that answer is once done it's a lot easier to replicate and that first strike is really the hardest. So hope that answered the question as far as being able to get there for making sure that you're getting buy-in. Love it. I'll leave it up to both of you to respond or add as you wish to these questions. So I'm moving on to the next question. As far as data in motion and verify and timeliness how can that be done reliably with quote unquote real time and near real time which can be in seconds and minutes, hours and lost old school daily delivery and validation does not have that complexity of validation timeframe. Yeah, so I can get started and I think when we think about timeliness I think time is becoming a dimension that is almost expected as we think about the stand up of various center of excellence as we think about the business being more engaged if you will on driving these initiatives or being part of these initiatives. What we don't wanna do is drive projects to be an IT only focus but as part of that, that's that integration into if you will a set of user experiences. And so one example of a very simple user experience is for instance on address validation old school delivery around address validation might be that I would enter the address however it might be I might actually take an extract of that data and then I would go validate that against a validation engine and then update the data in the targets location where it might be. Then you might really move forward a little bit from old school from a batch perspective into where I might do a real time API but it's on the submit and during that submission process I'll get feedback that says well, maybe this isn't the right address or maybe I'll get an address recommendation that I could potentially use. And then there's one step even further which is how do you integrate that address validation into the actual field while the individual is typing? So when you're like on Google or whatever when you're typing it actually makes certain recommendations around what you're typing the same thing with address validation as you're typing in the address it actually is coming up with the address and then you just select from the list and it then pre-fills if you will, all that information that is necessary so it actually enhances that overall user experience and it makes the overall validations on the back end a lot faster because we're not building in this exception logic that says well, we got this address but it's not the right address and all of that. So I think when we think about these capabilities it's really about where in this real time near real time in milliseconds if you will responses that would support these various initiatives. And so extending that even further into like for instance, address and or not address but email or phone or other types of validations is leveraging the technologies in a very similar fashion but then really understanding the requirements around this is to streamline the user experience we had a streamline if you will, the data so that we're doing things a bit more prescriptively with the data versus trying to be react on the back end. So hopefully that answers the question. Sue, do you have any additional comments you wanna make? I was just gonna jump in a little bit Chuck obviously talked about looking at data that needs to be enriched or standardized in real time and his answer is perfect on that I wanna address the dead in motion part and I don't wanna get too technical but the solutions that we have to offer have unique capabilities to measure how long it's taking something to move from one system remember we had that system A to system B we have unique capabilities that we can actually determine it should go from system A to system B within a certain timeframe, if not send an alert we can validate that all files are received in a certain timeframe. And again, as far as that from system A to system B to system C or going across that's how we actually are looking at those things in real time or I would say near real time I'm being honest with us here we actually do even have the capabilities of doing quality checks in the Kafka messages so as they're going across. So again, don't wanna go too deep but taking it a step further as far as dead in motion that's just kind of another piece to what Chuck said already. Okay, both. And our community loves to network with each other do you have user communities that are able to learn more from other users? Sue, do you have that? Absolutely, as a matter of fact we have a very robust community especially in the governance world as a matter of fact we're incredibly proud of that we have customers that are regularly presenting their best practices and standards around what they're doing as far as governance and quality we have a very robust community as far as our other solutions other the other things that we've talked about here but it really is something that as a product marketing manager I'm constantly learning from those groups as far as what are the new tips and tricks out there in different ways that we can learn from each other. So yeah, really something that we're very proud of here precisely. Very nice because networking is so important too. Absolutely. Data users. So what is data observability? You know, that's a, I can take that if you want. You know, data observability is an extension of data profiling. When we think about data profiling, you know, a lot of times what we're thinking about is, is really trying to understand the measurement of the statistics around the data. So maybe looking at various conformity or maybe various, you know, patterns in that data and really this is a precursor to what we consider a lot of data quality, you know, projects. And then maybe ongoing profiling so that you might better understand, you know, the trends of that data over time. Data observability takes those trends and sort of drives it, you know, it puts it on steroids and what we're looking for with data observability is things like, for instance, volume drift or schema drift or data values that have been introduced into fields that are not necessarily intended for, you know, the kind of value. So like, for instance, putting names into an address field or putting address fields into name fields. And then also really paying attention to and better understanding, right? Schema changes, schema drift and all of this being set with, you know, a number of observations. So this is an ongoing process that happens behind the scenes. It's a bit more proactive and what we mean by proactive is the sense that as these, if you will, events happen, these drifts or these observations happen, what we're able to do is provide an early warning system around that. So instead of actually being woke up at, you know, two in the morning because of a problem with the job that's running, right? You might start to get some trends that say, hey, over the last couple of days, we've noticed that the volume of the data actually has decreased. We've also noticed that the values that are normally in each of these fields is not complete or we're looking at values that are not, you know, if you will adjacent to the type of field that it should be in. And so you can get these early warnings, these alerts and then you can evaluate those and say, you know what? I actually want to do something. I want to take some action on that. Or you could say, hey, I want to ignore that alert and maybe set a threshold that says, you know, for this type of alert to pop up again, maybe it's not just I want to see it decreased by 1,000 records, if I have 10,000 records that are coming in on a day-to-day basis, but maybe if it drops by 2,000 records, right? If it's only 80% of the volume that I expect, now I might want to, you know, start to see this and start to understand that. But the other aspect of data observability is just being able to evaluate that on a time scale. So basically looking at, you know, how are these trends and how are we evaluating this and what kind of things that we need to do with that data. And all of those are actually really good insights that feed into the governance process. So think about, you know, making sure that we're compliant to the rules around the engagement of that data as well as to the data itself, right? So applying it to the data and making sure that we actually have the right, if you will, operators that are happening on the data to ensure that we are conforming to the requirements as a whole. And observability really helps us to just maintain and stay on top of our data. Because, you know, we've heard many times before from not just from analysts, but from what we've witnessed in industry is that when you do data quality projects, you do have, if you don't have an ongoing, you know, effort to maintain that, is a three to 5% decay in the data. And oftentimes some of that decay goes unnoticed. And this is where observability really helps is to help bring or illuminate when those data decay issues happen and hopefully help you to stay ahead of them. And if you will, make sure that they're, you know, they're being managed adequately. Perfect. Thank you so much. Everyone's a little quiet today. So that's the end of the questions that I have queued up. I'll give everyone a quick moment if you want to add anything else. Again, Chuck and Sue, thank you so much. Anything else you want to add? While we give everyone a quick moment to add any additional questions. I'm good. I just appreciate the opportunity for everyone to join us here. Thank you so much. I like that for the same. And thank you both. It's always a great presentation. I really enjoy this and already it's been requests to share with our team. So, so always a good sign. So thank you both. And thank you to all of our attendees for being engaged in everything we do. Just a reminder, I will send a follow-up email by end of the Thursday for this webinar with links to the slides and links to the recording. Thanks everybody. Hope you all have a great day. Sue, thanks Chuck. Hey, I thought it went well. A little silent. I was hoping for a few more questions, but we got a couple. Yeah, yeah. No worries at all. Thanks all. All right, thank you so much. Take care. All right, bye-bye. Bye-bye.


The following is a presentation of TFNN. The morning market kickoff with your host, Tommy O'Brien. And good morning everybody, Tommy O'Brien coming to you live from TFNN. Tommy O'Brien the fourth, he's taking the day off today. He's out there hanging out with Nana. Everyone's feeling good for the first time in a little while, so we're back at it looking forward to an hour of action packed market commentary and news. And we got some action to kick things off with the S&Ps off by 23 points. That's about half a percent. And boy, you see the acceleration, about 6.30 in the morning. Things were flat in this market. And just like that, we get a three hour run to lower prices. We're sitting at 4,300 in the S&P. NASDAQ 100, off 7 tenths percent right now, off 104 points, 14,880. We got the Dow off about 4 tenths percent, 33,500 the Russell off by nine. Crude, $88.49 this morning. Gold off $5 to $18.42. The dollar has been strong, right? To put it lightly. Dollar pushing 107.21. And the story of the day, it's been the story of the week. It's been the story of last month. It might be the story of this month. How about a 106 handle on the tenure? Now we got yields right now in the tenure, 4.71. 4.71. But yeah, I was saying, I came on the air, we were at lows. We were at 4.73. 4.74, I think, is almost what we got to on the tenure. Those are all the headlines. Highest level in 16 years, 4.71. Think about that. Over a 10 year period, guaranteed that interest rate to compound. We have not seen it in 16 years. Yeah. And let's get around to the 30 year that is recline some of those losses or clawing some of those losses back, I should say. We're back above 112. But boy, I've been talking about the fact that context is important, right? When we were having these conversations, so that's the monthly, let's put it, now you gotta put it on a monthly to go back that far. So look at the month we had in September already, we're what, two days into October? No, that's just the one day in October, 1202, is where we're sitting at. We started last month at 121 and change. You got up to 121.29, right? Mammoth moves on the 30 year, the 10 year across the board. We have the 10 year sitting at 4.73 and we are seeing a little bit of a pullback right now. But I'm jumping around to see how yields have reacted because I've been talking about the ladders, right? So what are we at? We're now at a 5.15%, five year CD, 5.15%. A five year CD, you're talking about 4.8%. Okay, it's important to have that context of where we are on a CD because that is some of the competition for market funds, at least keeping that in mind. And I keep saying it, man, if you're in the upper echelon of retirement, you're talking about retirement money that you aren't willing to see a 20% pullback ASAP, you should consider a hefty portion of your portfolio, man, in CDs, when you were pulling 5.15%, the reason why I say, let me just, I'm gonna copy this so you can take a look at it. The reason why I say the CD in particular is because it's less risk when you're into a CD. Okay, we gotta talk yields, man, we gotta talk CDs. We gotta talk guaranteed risk-free rate of return. So these are the CD rates right now. Now these are non-callable, okay? They are brokerage CDs. Make sure. But nonetheless, the guaranteed rates on each duration on a one year, you're pushing 5.5 on a two year, 5.4, three year, 5.15, a four year, let me even expand it, there we go, a four year, 4.9 and the five years pushing 4.8. Now the reason why it's so cool doing a ladder, okay, is because every year you get to catch up with what the market interest rate is protecting yourself if inflation really roars, that's the worry here, okay? Because you could say, well, geez, that's a great ladder, but you know what, I don't need to ladder things. I'm just gonna go out to that five year and go to 4.8% because I'm worried that inflation's gonna go down in the next year or two and even that five year in a year or two is gonna be dramatically lower. So that could be the case, right? That is the case that is a potential opportunity cost of locking this in, but here's the kicker. What if inflation keeps going higher? Okay, over the last year we've seen this play out. People locked in rates at a very reasonable rate of return. Okay, this is not like if you need to trade out of these that you're gonna lose capital. If you plan on holding these through expiration, through the duration of the CD, you will get that risk for your rate of return. So maybe people locked in 4% last year, but here's the problem. Inflation is still roaring, so the real rate of return is not as high as you may have anticipated, okay? By laddering CDs, your real rate of return stays closer to if it's a positive number, it's a positive number, okay? But you're more protected because if inflation goes up, when these ladders roll off on a yearly basis, what's gonna happen? You're still gonna be getting lofty interest rates to compensate you for the inflation that's roaring. The flip side of that is, is if inflation gets squashed and the economy's in trouble and the Fed is cutting, what will happen? Well, what's gonna happen then is that the interest rate that you're getting when you're laddering these is gonna go down, but that is more okay because the real rate of return is still similar when you factor in that inflation is gonna go away in that type of a scenario. Nonetheless, we're gonna keep our eye on these, man, even a two-year ladder, right? Rates are not going down for a couple of years, man. 5.5%, a two-year ladder. If you're talking about investment money, you're pushing 5.15%, and that is as of this morning, it'd be interesting to see if that changes. What were we at last week? 5.11 and 5.12 potentially on that number. So we've seen the 10-year rise, the two-year not so much. The two-year's locked in where it is right now. It is moving, okay? But I had to have that conversation because we're gonna keep our eye on that. And here's kind of the case of the two-year, right? Look at the two-year. The two-year is not even below where we were two weeks ago on Wednesday. Compare that to the 10-year, folks, okay? Two full points below where we're at. Now, that was the Fed Day Wednesday. You could say that we're a point and a half below on the 10-year, but it is the longer part of this curve, not the two-year, okay? The Fed spoke, everything calibrated. You gotta move from 101.15 down to 101.07 on Fed Day, and that's where we've stayed on the two-year versus the 10-year and even the 30-year. Look at the trend in these longer-term yields and realize that the shift is not right now on a Fed over the next two years. The shift right now is a dramatic shift in the repricing of the longer-term part of the curve. Now, we jump around from there. That is part of the equation that uninverts the yield curve, okay, because what do we have? We have a yield curve that is dramatically inverted to the tune of pulling up rates where they are on a duration basis. You get the two-year sitting at 5.11. We were approaching 5.2. We were approaching 5.2 on the two-year, okay? So we've had the two-year pullback. Meanwhile, you get the 10-year right now, 4.72, we'll call it, okay? So you're two years at 5.1, you're 10 years at about 4.7, you've got about 4.1, excuse me, 0.41% is the inversion right now between the two-year and the 10-year. Well, you might not get the two-year going down anytime soon, but what could save all the recession indicators, okay, as you're gonna get a higher rate for longer, you're gonna get a higher interest rate, maybe a higher R star that neutral rate the Fed is looking for. Stay tuned, folks. We got lots to talk about today. We're coming back with our man, Kevin Hinks from the Schwab Network. We'll be right back. If you're looking for potential trading setups in the stock market, then Rocket Equities and Options Report is a newsletter you should try. Tommy O'Brien delivers options and equity trades when the markets present them, using a combination of fundamentals and technicals. Sign up for Rocket Equities and Options Report today with a 30-day money-back guarantee so you have nothing to risk. For all the details and to start your subscription today, visit the front page of TFNN.com. TFNN, Educating Investors. Everything in the universe is governed by the Fibonacci Sequence, and this mathematical principle is responsible for everything from the most aesthetically pleasing artwork to patterns in the stock market. To stay on top of stock patterns you can take advantage of, sign up for the Fibonacci 24-7 newsletter at TFNN.com. When you subscribe, you'll get a weekly report from veteran day trader Larry Pesavento on stocks you need to pay attention to, and you can trust Larry's analysis. After all, he's got 45 years' experience as a day trader. Larry will also provide daily charts, videos, and data on the key markets that he's tracking. Expect notifications from Larry on market movement you need to act on at any time. 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At TFNN, all our newsletters come with a 30-day money-back guarantee, so you have absolutely nothing to worry about. Visit TFNN.com and try Mastering Probability 30 days risk-free today. TFNN, Educating Investors. TFNN has launched the Tiger's Den, hosted at Discord. TFNN has been educating traders for more than 20 years with live programming hosted by a variety of professional traders during market hours, the Tiger's Den, available to all tigers and tigerses for just $1 for the year. There's no catch or added costs when you join our community of traders. Sign up today and become a part of this educational community of traders. Just visit the front page of TFNN.com. It's in red territory. You get the S&P futures off by 29 points. We're trading at 42.95 right now. That's a decline of about 2.30%. We get the NASDAQ 100. We're reaching pre-market session lows almost right now. We're trading off 8.10% off 125 points in the NASDAQ 100 to talk about some of the market action. Let's jump over to our man, Kevin Hinks. Every trading day, folks, 12 noon Eastern time. Right here on Tiger TV, the Schwab network with fast market. Your host, Kevin Hinks, Tom White, the team at the Schwab network. Great lineup of guests. They usually walk you through three hypothetical trade setups, folks. If you ever want to learn about options, okay, even if you know trade options, I always say understanding them can help any trader check out the program fast market at 12 o'clock. Kevin Hinks, how about these yields, man? Good morning, Tommy or Brian. Yeah, higher yields, higher dollar. Both of them weighing on stocks, Tommy, and it looks like the start of October is very similar to what we saw in September. So at least the start of October, Tommy. So yeah, toppy waters right now as we deal with not higher yields, Tommy, I would call them spiking yields. And the markets don't like spiking yields, Tommy. They make the market uncomfortable. Now, if they plateau out, if they calm down, the markets get less uncomfortable. But right now we are in full uncomfortable mode, Tommy. That's a good way to put it, man. Full uncomfortable mode. I was talking about, I kicked off the program, Kevin, just taking a look at the two year, which obviously moved on Fed decision about two weeks ago now, and then you have the 10 year and the 30 year, and we've really seen since two weeks ago, the longer duration yields, right? Are the ones that are really moving the most right now, at least since we got that Fed move of a couple of weeks ago. And that I was talking about potentially the yield inversion and how now you have longer term yields, they're rising a bit. You still have the two year well above where the 10 year is. But how do you look at that inversion right now, Kevin? It's got a long way to go, but longer rates going up, that would be one thing that might save all these indicators saying the yield inversion, we've all been hearing it for so long. It's a recessionary indicator. What do you think about the inversion of the yield curve still in some of that movement, especially on the 10 year and the 30 year? Yeah, the yield curve is steepening. It's not all the way there yet, but it is starting to steepen. And that's probably the function of the understanding that interest rates are gonna stay higher for longer, right? Loretta Messer said it yesterday in some of her comments. She said, her comment was, we are likely near or possibly the peak of the Fed funds tightening cycle. Now our task turns to ensuring that we keep monetary policy restricted for long enough, Tommy. So higher for longer means now the back months or the longer dated instruments are starting to move higher. So yeah, that is steepening the yield curve. We'll see how it finally plays out, but yeah, those higher yields, they affect stocks, the higher dollar, the Bank of Japan move to go back in buying bonds starting tomorrow, that's moving the dollar. Yields are higher. That works against stocks. You see stocks were, yesterday's market, Tommy, was interesting. The magnificent seven or six of the seven without Tesla kept the market looking better than it actually was in my opinion, because take those six or seven stocks out and the market was weak yesterday as well, showing that again this morning, Tommy. It was a great point. I was looking at Apple yesterday. I just pulled it up at least Apple and Microsoft when you were having the conversation, Microsoft trades from about 316 to 322 yesterday, man. And Apple shares right out of the gate jump from like 171 up to almost 174. Yeah, 174 at one point yesterday, strong day from some of those big tech stocks. With that in mind, man, October started yesterday, Kevin. We're coming into a new season of course, but we got a little bit of a low before we really kick things off on earnings. What are you guys talking about on fast market coming up on the Schwab Network at 12 today, man? We're going to look at Boeing that stock is getting absolutely annihilated lately on the downside here, getting severely oversold. Like fully this can do presentation on Spotify. And then we're going to look at Amazon in the final segment. So three really big high profile names we're looking at today, Boeing, Spotify, Amazon. Amazon, man. Quite a run from the first of the year. I got it up here on the Thinkorswim platform. $81.43, man, is the low there as we were right near the beginning of the year and quite a pullback though from that high above $145. Kevin, I appreciate the time as always. Can't wait to talk to you tomorrow. We'll see where yields drive some of this conversation and we look forward to the show today talking about some of those equities I had Boeing up there too. Quite a pullback for Boeing. I think I saw one of the airlines inking a deal with Airbus potentially this morning over the weekend. Maybe I saw that. Kevin, I appreciate it, man. Have a great day. We'll be watching at 12 o'clock today, man. Have a great day, Tommy. Thanks for having me on. Always a pleasure. Folks, check it out. Fast Market from the Schwab network. Aired every day, 12 till one right here, live on Tiger TV. Kevin Hinks, Tom White. They have an outstanding lineup of guests that they bring on and the way they walk you through hypothetical trade setups, folks, for me, it's the best way to learn.  They'll manage them the next day. You know, if it needs trade management, that's a lot of what you learn. And as I always say, when I bring Kevin on, if you don't trade options, that I understand, but understanding how they trade, understanding how they're priced, understanding the implied volatility with them that is priced in, et cetera, it speaks a lot about what the market is pricing in for equities as well. So even if you're an equities trader, understanding how the option market is pricing things, that's something that will help you as an equities trader, even if you don't trade options. And yeah, I'll have to find that news because I think I did see something. And I'm just seeing Wells Fargo with some stuff in terms of the news, but I thought I saw something talking about a deal potentially with one of the big airlines getting some new Airbus planes. I said, huh? All right, I'll have to fight through that at the break, but nonetheless, there's the Charter Boeing, man, pulling back from 240 to 187. And I mean, look at this thing longer term, right? Quite the spike up to 446. You got the 737 Max pullback, which was from 446 down to about 350. Then you got the COVID drop off that put it down to 100. Since then you're facing some resistance at the 240 to 250 area. That's where you pulled back from this year. You got up on the COVID highs to about 278, that high of 2021. Really interesting when you look back, right? How some of the market, it was a early spike for some equities, Boeing. I mean, we got the highs in the market at the end of 2021. By that point, Boeing had already pulled back from 280 to what, 200. I mean, another stock that made that peak early. Amazon actually, no, so not so much the case. I guess they got up to that high though. In September of 2020 and went nowhere until the market fell apart towards the end of 2021. Disney was another one, right? Early, early accelerator and had already pulled back. Yeah, made it to 2000, excuse me, 203 by March of 2021 by the time the market had peaked out. You're already back to 145. Just interesting, you learn from history folks in terms of the rollover was taking place in some of these equities and the Fang stocks. Remember, we're holding up so well. Kevin put it yesterday, holding up so well. Yeah, there was Apple's acceleration into the market highs, not a coincidence, right? Peaking out, but guess what? We got new highs from Apple, pretty remarkable. Microsoft shares, Kevin mentioned it. Strong day yesterday from some of these Fang stocks, not so much the case this morning. Microsoft charges higher to almost 322, 48 was the high, we finished the session at 321.80 yesterday. And yeah, we're gonna give up about $2, $3 right now for Microsoft shares, but quite the acceleration for them. And we got to keep our eye on yields in the dollar. Little bit of a give back in terms of the lows. We did have a 106 handle in that 10-year and as Kevin said, it might be able to handle higher rates, but boy, can it handle a 10-year going from 117 to 107 over a period of five months because that is what is happening right now, man. Stay tuned folks, we're coming back for the open. Don't go away. Currencies, commodities and bond markets are as important as ever right now with how they're driving the volatility in equity markets across the globe, which is why it's a great time to try out Teddy Kegstad's Tiger Forex Report. Teddy Kegstad breaks down the forex markets every Monday using his 30 plus years of experience as a trading veteran of futures, forex, stocks and options. Teddy releases his weekly Tiger Forex Report every Monday morning with coverage of all the major currency pairs, including the dollar index, the euro dollar, pound dollar, dollar Swiss, dollar yen, as well as many more. And he also has weekly coverage of the crude oil market and the 30-year T-bonds as they both influence forex markets tremendously. When you sign up for the Tiger Forex Report, you also gain instant access to Teddy's 60-minute webinar archive he just hosted, forex strategies and fundamentals, what is behind the Tiger Forex Report. For all the details and to start your 30-day Tiger Forex Report subscription today, visit the front page of TFNN.com. TFNN, educating investors. Currencies, commodities and bond markets are as important as ever right now with how they're driving the volatility in equity markets across the globe, which is why it's a great time to try out Teddy Kegstad's Tiger Forex Report. Teddy Kegstad breaks down the forex markets every Monday using his 30 plus years of experience as a trading veteran of futures, forex, stocks and options. Teddy releases his weekly Tiger Forex Report every Monday morning with coverage of all the major currency pairs, including the Dollar Index, the Euro Dollar, Pound Dollar, Dollar Swiss, Dollar Yen, as well as many more, and he also has weekly coverage of the crude oil market and the 30-year T-bonds as they both influence forex markets tremendously. When you sign up for the Tiger Forex Report, you also gain instant access to Teddy's 60-minute webinar archive he just hosted, forex strategies and fundamentals, what is behind the Tiger Forex Report. For all the details and to start your 30-day Tiger Forex Report subscription today, visit the front page of TFNN.com. TFNN Educating Investors. Sharpening your skills as an investor is like getting better at playing a musical instrument. You have to practice, sure, but you also need excellent instruction from experts. At TFNN, you'll get advice and guidance from the authority in technical market analysis, and it's not just dry, tedious text either. TFNN airs live financial content streamed live on TFNN.com and TFNN's YouTube channel with Tiger TV, live every market day from 8.30 a.m. to 4.00 p.m. Eastern, for free. Each host is an experienced trader and gives their take on the market while taking calls and questions live from around the world. From the moment the market opens until the closing bell sounds, Tiger TV has eight different shows with expert hosts to help you make the right moves with your money. Watch online at TFNN.com or on TFNN's YouTube channel and become the investor you were born to be, TFNN, Educating Investors. Don't forget, you can listen to TFNN live on your mobile device 24 hours per day. Go to TFNN.com and hit Watch Tiger TV. That's TFNN.com and hit Watch Tiger TV. Welcome back, folks. We have the market open and S&Ps catch a little bit of a lift coming into that opening bell. We're still down by about 20 points or just about half a percent in the S&P NASDAQ 100, off 6-tenths percent. All the markets catch a little bit of a lift in the last few minutes coming into the opening bell. Dow off 110, the Russell off by seven, and it was United, the airline. United closing in is the headline here, but I think, yeah, as soon as today. A321 Airbus, narrow-body jets, United closes in on an order for them as soon as Tuesday today. Yeah, a purchase by United would add to the A321 in the U.S. airline, the U.S. airline already has on backlog. So they have 120 already. The airlines pay about 60 million each and they had 120 on backlog. They've been loading up on the largest Airbus narrow-body as the airline retires, the Boeing 757. They've ordered some of the rival 737 MAX model as well and they've been one of the largest post-pandemic aircraft buyers and said plans to add about 700 narrow and wide-body planes over the next decade. 700 planes over 10 years, right? Hiring more than 10,000 pilots. I mean, 10 years, I know 10 years is a long time, but 10 years ain't that long a time, man, to add 700 planes on one airline. You jump over United shares down a bit, down about 6-10% right now with the market in negative territory for United. Okay, let's talk a little bit of markets. Pulling over one of the articles I was reading this morning. This one from Bloomberg, Treasury sell-off fuel speculation that bond vigilantes are back. You better believe it, man. This bond market is volatile and ripe for even more accelerations potentially. Now this story out last night and just some of the statistics in here, I mean, pretty remarkable when you look at this chart, right? Yields, we all know they were low, pandemic lows, right? 2020, Fed cuts everything. Rates go to basically zero. They're sitting 10-year Treasury yield at half a percent. My brain always goes to somehow when I see charts like this. And this is where banks decided to put all of their money when there was an influx of deposits on a long duration. How's that happen, right? And then look what happened. Yeah, of course it did. Who was locking in 0% interest rate right there, man? The risk was not worth the reward. That's something you always wanna keep in mind, folks, okay? Cash can get destroyed, but is the risk worth the reward? I mean, everything in life has a risk reward ratio, not to get philosophical, but it really does. And many times that is the calculation that drives many people in terms of what they decide to do with their action. Risk versus reward, 0% interest rates, man. Putting your money there at a long duration. And then they're never, you know, as we all know, and then everyone's surprised somehow when they go BK. But check out the acceleration, right? This is the 10-year. I said, we're at 4.7. Even from where we were a couple of years ago, right? This recent run, starting since May, where we've just really spiked from a 10-year approaching 3.5 to 4.5%, well above anywhere we've been in the last 16 years or so is the number. Now, what this talks about though is the manufacturing PMI, to give this some context here, okay? They're talking about it's been excessive given recent economic data, okay? And that it's decoupling from manufacturing data. That is the purchasing manufacturing index in red. And you see the decouple in terms of it rising as we got to rise and then quite the pullback in manufacturing, which has not correlated to a pullback in yields, okay? One other chart that I thought was cool that I thought you gold bugs may appreciate. The 10-year treasury yield diverges from copper-gold ratio, okay? Now, this is Ed, is it Ed Yardini? Believe it is, right? Yeah, economist Ed Yardini, and he's been a bear, okay? So take it for what it's worth. But he's talking about a decoupling here that is signaling, okay? Most of the bond indicators that worked in the past haven't been working. We suspect the Fed officials may soon be alarmed by the unyielding climb in yields if they aren't already, they should be. The bond yield was highly correlated with the ratio of the prices of copper-to-gold from 2005 to 2019. They've diverged significantly since then and you check out the acceleration. There is a correlation. Highly correlated, that's a little bit debatable. But yes, but you see the decoupling that has taken place, man, okay? You have the copper-gold ratio sitting at just above one. Meanwhile, you got yields pushing 5%. The last time yields were pushing 5%. In 2006 and 2007, you really got an acceleration there, not the case right now. What that means exactly? I'm not sure. He's pointing to a decoupling in yields though, okay? And that I would keep my eye on because even if these charts don't illustrate that that's what's coming, folks, there's still dramatic risk. Everybody's talking about supply and I can't help but talk about yields endlessly on the program because it's a vicious cycle, okay? When you think about the fact that number one, I've talked about that things look rosy on this chart because it goes back to 2003. You put the 30 year back here and you go back to 2003 and you see anywhere before this chart, that's the 30 year. Yeah, anywhere before that point in the chart, that's actually the high point on the chart that you were at. You actually got much lower when yields were much higher, okay? And these were not the crazy 80s times, folks. I was in high school during 97. You were the 30 year trading at 89, it's at 111. So there is room for things to change in terms of the yields and then you go to the debt. Of course that becomes political. I'm glad the country didn't shut down, okay? You gotta pay your bills. You gotta figure out how to pay the bills and we pair the debt in terms of just not paying our bills. It's probably not the solution. I understand everybody uses any type of leverage they can during a negotiation. It's tough when going over the cliff. Hurts real people in terms of those paychecks. Stop, I mean, servicemen and women stop getting paychecks during that. You're gonna have potentially payouts for retirees. All these 10 year yields we're talking about, those could be impacted, right?  If interest rates go up, that debt becomes more expensive to service, thereby requiring you to issue more debt to service the debt you have, right? It's a very difficult prospect right now. And when you think about, okay, the risk, I mean, folks, what if we just get a six to seven week stop gap measure to keep the government open and you're telling me right now that you trust the government for 30 years with your money and meanwhile you're getting barely over what you get for a five year, the risk associated on the longer term duration, government bonds with what's going on is very difficult to assess as somebody that is just looking at the risk reward of receiving your money back on a timely basis, okay? I don't imagine things are gonna fall apart in the next year or two. But over the course of 10 to 20 to 30 years, I hope we're still paying our bills. But if I was viewing this as a business transaction where the other counterparty was just a business entity and I saw the inner workings of that business entity barely keeping their operations open, barely basically giving themselves the ability to issue more debt to pay the bills they've already incurred. And I considered lending that business money. I would have a severe risk on a longer term basis understanding why I never saw the potential for an impasse that somehow stopped payments to a certain degree. With that in mind, right? Yields may be persisting because you're gonna have a supply problem, man, okay? And until we get that under control, I think rates on a longer term basis have to go higher and we're seeing that happen. Stay tuned folks, markets in red, we'll be right back. You might think that if you want to be successful at trading in the stock market, you're going to need a crystal ball. After all, it's impossible to predict the future, right? Like any endeavor in life, before you decide it's impossible, get some advice from the experts. You might find that it's not so impossible after all. For daily market overviews that give you direction on the key indices, selective stocks, and commodities, subscribe to the opening call newsletter at tfnn.com. 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Yes, Atlanta Fed chief. Just wanted to make sure for some reason question myself. So he's out here this morning, making a lot of sense I think. I'm not in a hurry to raise, but I'm not in a hurry to reduce either. The Fed should hold interest rates at elevated levels for a long time, quote unquote, to bring inflation back down to its 2% target. He called that 2% non-negotiable. Can't wait to see if they actually try and tweak that going forward. Times change though, as we know folks. So I want us to hold, I think that's appropriate thing to do for a long time. That's what they're saying now, it doesn't have to be the case. He does not vote on the rate decisions this year, okay? But this is the message getting pushed out there and I think it's probably gonna be the way that plays out at least for the November meeting. There are almost 5.5%. Where the economy is growing right now is not 5.5%. So it's probably a restrictive, everything's probably in this, right? Cause I don't know where exactly the economy is growing right now on October 3rd. So everything is kind of a personal take opinion, guess best guess scenario with the information available. But they're at almost 5.5%. The economy's probably, inflation is probably not 5.5% right now. The economy's probably not growing at 5.5%. That means it's a restrictive rate policy. As the rates go down, right? Excuse me. As inflation wanes, as growth recedes a bit from the growth that drove generational inflation, that 5.5% actually becomes more restrictive. The closer the Fed gets to their 2% goal. So that's even more worrisome if you're still hiking at a time when you have inflation coming down. Let's just say you think inflation is at about 4% right now. Let's do 4.5. Let's say people out there think inflation's at about 4.5%. Now on a core basis, it's probably a little bit lower than that right now, which is what the Fed is looking at. So let's say core inflation's at about 4%, okay? Just using simple numbers. The Fed is at about 5.5%, okay? It's a percentage and a half above the growth rate in the economy if that was the R star, which doesn't quite correlate, right? Inflation does not equal R star, but R star is kind of the natural growth rate of the economy that if the Fed matches the R star, that that is bliss, that's euphoria, right? The cost of capital is just equivalent to the growth rate, therefore not allowing it to overheat or over cool, okay? But they're all theoretical numbers. Nobody actually knows where that number is today, which is important. They're just trying to peg that number. But let's say R star's at 4%, the Fed's at 5.5%, right? Well, let's say they bring inflation down a bit. Now you have core inflation at 3.5%. Fed's still at 5.5%. It's even more restrictive now, because the growth of the economy is only 3.5%, and they're still at 5.5%. Then you get it down to 3%, right? Well, geez, now it's really restrictive because the economy was growing at 4%, and the Fed was charging 5.5% for capital. But now it's only growing at 3%, and they're still charging 5.5% for capital. It's a bigger restrictive gap that it has on the economy. You get down to 2.5%, you get the point, right? So what happens? As they get closer to 2%, that rate that they are at, even if they just stay there, is akin to putting more pressure actually on the economy. That could be an argument for eventually some cuts. You start getting down to those numbers because if they leave it at 5.5% for too long, what's gonna happen? It's gonna become too restrictive because we get closer to 2%, and you still got the Fed pushing 5.5%, that could tighten the economy to a degree that could cause a recession. We get to see it all play out, but I thought that was an interesting take when you walk through the scenario of how that plays out. And yes, so keeping things higher for longer, as long as the trend keeps going that way, or even if it just stays, excuse me, folks, even if it just stays where it is right now, is in if inflation is staying at 4% and we're making marginal gains to 3.8%, to 3.75%, to 3.6%, every little marginal gain you get actually means that staying where you are for the Fed has more impact. It is a more restrictive policy than it was prior because as you inch towards 2%, remaining at the current rate that they're at, the Fed at 5.5% almost, puts more pressure on the economy. So keep that one in mind too, as they start having those conversations about potential cuts because at some point, a 5.5% Fed policy rate on a growth rate of like 4%, you could probably make the case that if the Fed's brought the growth rate down from 4% to 3%, well, maybe they could ease up a little bit on their 5.5% because you don't need to be at 5.5% anymore because now you've got the inflation rate down from 4% to 3%. So even a number of 5% or 4.5% would still have an impact. It's kind of just a thought process, but that is going to be something we deal with if the Fed starts making progress. The flip side of that is if it starts going up again, that is the scenario that they probably will consider hiking again. I think if we stay where we're at right now, they're just going to give it a long time because in theory, they are at a restrictive policy rate, man. And yes, it's going to take some time, but they'd rather do that than really start messing with what, 10% mortgage rates, a 7% tenure yield, stuff like that. That would really put some strain on the economic engine of capital and how it flows through the economy. Okay, what else do we got in here? Yeah, let's talk about that. Jamie Diamond, he's talking about that the children are going to live to 100 and not have cancer because of technology, very reasonable with the way biotech is progressing right now. And I like this one even better. They'll probably be working three and a half days a week. Why not three, Jamie? Why not three? No, I kid. Interesting nonetheless, where does this fall? Because I have a kid who's two years. You saw him on the program yesterday. And I mentioned this in some of those talks, the auto workers are having, right? Five day work week, two days of rest. Be able to question the norm, man. Okay, there's no reason why with the level of wealth and technology that our country has in particular, and many countries out there in the first world, that the five to business model could not be achievable in another fashion, especially with where technology is today and the ability to work remotely. So, you know, they're talking about the auto workers potentially working four days. Well, you can make a very reasonable case outside of the personal bias that we all have because we've grown up in an economy where people are expected to work Monday through Friday and you're on the weekend, Saturday and Sunday can make a very reasonable case that working four days a week and only resting three days a week is still a lot of work for a lot of people. And I guarantee that the country could figure it out because guess what? Everybody said you couldn't work from home and figure it out. And we figured it out in like two weeks when we needed to, right? So just be able to be open to change and be aware of your personal biases. For certain companies, it's not gonna happen, okay? For certain positions, you still gotta work six days a week. But as time progresses and technology increases and AI helps things in terms of productivity, right? Very possible to achieve those types of productive gains with technology that might allow you not to have to work five and then rest two. All right, folks, stay tuned. We got one more segment. S&Ps right now, negative by 12 points. Markets catch a little bit on the open. Stay tuned, we'll be right back. The Gold Report. As a precious metal gold is still king, it continues to hold the most effective safe haven and hedging properties across the global major trading hubs of the London OTC market, the US futures market and the Shanghai Gold Exchange. The Gold Report. Tom O'Brien publishes his weekly Gold Report every Monday morning for subscribers consisting of coverage of the XAU, HUI, GDX, the dollar, bonds, the South African RAND, as well as 25 different mining equities with specific buy-sell recommendations. The Gold Report. New subscribers get a 30-day money-back guarantee so you have nothing to risk. Subscribe to Tom O'Brien's Gold Report newsletter now at TFNN.com. You might think that if you want to be successful at trading in a stock market, you're going to need a crystal ball. 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Go to TFNN.com and hit Watch Tiger TV. That's TFNN.com and hit Watch Tiger TV. Folks, we have yields. Yeah, pulling back a bit from where we were. Let's check out in terms of where we are on that yield curve. But you talk about a pop right now. You have the 10-year trading at 106.29. We've driven all the way up to 107.10. You're talking about a 10-year yield just under 4.7% right now. We were at about 4.73, I think, 4.74. Almost 4.75% on the 10-year yield. We almost hit this morning. We're right at about 4.7% right now. And markets easing a bit. As we've seen that with the S&Ps, had a 4,200 handle to kick off the program. We're trading right now at 4,315. And folks, if you didn't get a chance to check it out yesterday, a new program started yesterday on TFNN, our man Peter Bruno, the Wall Street Money Hour. So that is live from 2-3pm eastern time. That's Monday through Friday, every market day. He'll be in the slot right before my dad, coming up at 3 o'clock. So check out Peter's outstanding program yesterday. I know he's excited, man, to be doing the program out there every day. He's going to have the Wall Street Money Letter that's going to be up there on the website as well shortly. But check out the program 2-3pm yesterday it began. But that's every market day. Today, Wall Street Money Hour with Peter Bruno. So check that out at 2 o'clock today if you haven't yet, folks. And this market, you talk about relentless, right? We just got back 20 points in the S&P. We jump over to the VIX this morning, backing off a bit, but still relatively high. You're pushing an 1,815 VIX right now. And as we finish it up, we got about 30 seconds here. Article from the Journal I found interesting this morning. This went out at 8 in the morning. Wall Street thinks America's homes are overvalued. Okay. And this talks about, of course, as prices paid for the average single-family property hit record highs, you have big investors potentially taking a pass. How about single-family homes? Okay. Property values back above where we were at a year ago. Remember that? We just got prints for, I think it was June or July talking about we were actually above. Multi-family? Not quite the case, man, for big investors. How about this chart here? The portion of U.S. home purchases made by landlords with 1,000-plus houses. Look at the fall-off. As you got big-time investors pulling back, yield's playing a part of that for sure. Okay. Yield's playing a part of that for sure. And that's not even talking about corporate. And watch out for corporate as the world has changed. And, yeah, commercial real estate changed as well. Thanks so much, folks. Stay tuned. We got Basil coming up next. Have a great day. We'll see you tomorrow, folks.