All of you are watching this video because of your concern for the safety of your animals during an emergency in your community. This presentation will give you information on how to plan for your animals if there's a need to evacuate or to shelter them in place, and how to find resources in your community to help you with your planning. As an owner, you know your animals' health and safety rely entirely on you, especially in an emergency. As you probably know, the need for this information is huge. Your animals are a very important part of our lives. For people whose animals are trained service animals, they allow their owners an independence they could not receive elsewhere. Animal ownership is extensive. It's estimated that the average American household has 1.2 pets, not including wild or exotic animals, or animals of market or food value. Because animals can influence your decision to take protective actions, it's important you understand the steps to protect your animals if you're told by emergency officials to evacuate or shelter in place. A hazardous chemical release from a train derailment or a flood can prevent you from caring for your animals for days if animals are not evacuated with you. To major events such as a devastating hurricane or earthquake occur, animals may go untended for weeks if owners do not take their animals with them or shelter them in a safe environment. For the most part, people do a good job as far as planning for themselves and preparing their homes. Again, it's just leaving the animals out of the loop and spending some time and thinking about the animals' needs in a time of crisis, a little bit of extra food, a place to space in their cars, or transportation lined up ahead of time, whether it's by relative or local transport. I think they just need to spend more time working on that aspect, treating their pets more like family. As an owner, you hold the key to your animal's health and welfare. As you probably know, animals left behind may be found dead or never found at all. At best, they may need to be rescued, decontaminated, vaccinated, and treated for injuries before being returned to you.  Highly valued animals may be stolen and sold before you can return home. And left without food and water, normally docile animals can become vicious and be killed by law enforcement or wildlife officials to protect emergency responders or returning evacuees. This video will enable you to identify hazards that could impact your animals and to develop a basic emergency supply kit for animal care. During the video, animal care experts and veterinarians will explain why having recent photos of your animals and copies of identification and vaccination records are important in emergencies, how microchips work, and how to plan to protect animals if you're away from home. Why animals may have to be decontaminated after a hazardous event, and some basic precautions to take when animals return home. Evacuation planning for animals is often an overlooked item in community emergency plans, although some states are starting to develop certified disaster animal care response teams to help counties cope with animal populations in major emergencies. One recent change in preparedness occurred when the pet's evacuation and transportation standards act was signed into law in September of 2006. Nationally the pets evacuation and transportation standards act or the pets act has provided an incentive for local communities to comply with the requirements of that act. And the requirements of that act are for communities to have plans to deal with household pets and service animals during evacuation to be able to evacuate transport and shelter those animals and provide services that are related to those issues. This does not mean that public shelters must allow pets other than service animals to remain with owners, but that reasonable efforts must be made to accommodate the needs of individuals with animals when evacuations occur. Because of the potential cost and extra burden to communities to implement these requirements, having your own emergency plan that considers your animal's specific needs remains the best policy for you and your animals. Emergency plans are important for all types of animals from household pets and trained service animals to highly valued or exotic animals, horses, poultry, and livestock. American humane encourages responsible pet ownership regardless of what kind of pet. So while most companion animals or pets are traditionally dogs or cats, many families choose some other pet and often exotic animals such as snakes or alligators or iguanas or whatever, but regardless of the choice of the kind of pet, it's the pet owner's responsibility to plan for the care of that pet both during normal times and during emergencies. Planning is especially important if you have multiple animals or the animals are highly valued, animals with medical problems or that need special care or food or trailers or other large vehicles for transport. You should also be aware that some states forbid trailers on official evacuation routes during an emergency to make sure passenger vehicles are given maximum leeway to leave an area. While this video touches on some issues associated with protecting large animals and livestock, commercial farm operators or people with large herds or highly valued livestock, or who manage zoos or aquariums, should work with their state and local emergency officials and veterinarians to develop their specific emergency plans. If you look across their country, we have a lot of zoos. We have exhibitions like aquariums and we have wildlife sanctuaries, wildlife rehabilitation facilities. We have a lot of different animal facilities out there that may need some assistance if they get a fairly major emergency. The first thing that those facilities need to do is they need to have their own contingency plan for emergencies. Indigenous wild animals being the property of the state are generally the concern of fish and wildlife management agencies and are not considered pets in this video. Owners should always remember that unvaccinated wild animals can transmit rabies to their domesticated animals and themselves through an infected animal bite and all wildlife should be considered potentially dangerous, especially if the wild animal is behaving abnormally. The problem is whenever you take a population of animals, whether it be companion animals, wildlife, laboratory animals, livestock, you're changing the dynamics of the system. So say there's a wildfire and wildlife are affected, then those animals move into the general population and can commingle with domestic animals, increasing the likelihood of say rabies or other types of diseases. Planning to evacuate with animals is important because it will make sure your animals are as protected as you are. Most agencies now recommend taking household animals when residents are told to evacuate. While most public shelters do not allow animals other than service animals inside for health and safety reasons, some jurisdictions allow created animals with current vaccination and medical records to be sheltered outside public shelters. Others offer separate or adjacent facilities such as fairgrounds for sheltering animals. Many hotels and motels will waive pet exclusion restrictions during major disasters. You can usually obtain a list of pet-friendly motels and hotels through your state or local emergency management agency. Such information will allow you to leave with your pets, knowing you can assure both their safety and your own. Some people think confining pets in vehicles outside shelters is a viable option, but the practice should be avoided. You can place yourself and your pet in danger when caring for them during stormy weather or other hazardous events. And vehicles are not safe places for animals during severe storms where flooding or downed trees or structures are potential risks. In hazardous material releases where protection offered by a vehicle is minimal because of the high air infiltration rate or in extreme heat or cold. After finding out what your emergency management agency plans for animals in emergencies, it's time to develop your specific plan for protecting your own animals. Usually this includes selecting a destination site, adding animal care and food supplies to your emergency kit, having appropriate carriers and restraints for each animal, and taking additional water, bedding and cleanup materials such as paper towels and trash bags. If you know your animals dislike vehicles or going into crates, taking time to familiarize them with the routine by setting up the carrier and placing treats and familiar bedding inside so they can get used to it over time. If your community does not have an emergency plan that includes animals, you have a bigger job because you have to identify the hazards and their associated risks that could affect your animals. Understanding what the local risk is for a disaster is very important. It's really key to understand what that possible hazard would be and to plan for it. Most year-round residents are familiar with hazards that periodically occur in their community such as hurricanes and floods, but a newcomer or a visitor may be unfamiliar with the specific risks of a hazard or what actions to take in emergencies. People may reside for several months in an area for seasonal employment or vacations or for educational studies but remain unaware of the hazards to their animals at their temporary home. It's important that you learn about potential hazards wherever you take or house your animals. Other hazards that you should prepare for are potential train derailments or hazardous releases from industrial facilities or semi-trucks along major roads and highways if your animals are located nearby. Although such events have a low probability of occurring, a general evacuation plan for your animals can often be quickly adapted to meet such emergencies. Your local emergency management agency will often have maps locating flood zones or other hazards such as earthquake faults and areas subject to wildfires that you can view or copy. Some communities near nuclear power plants or military installations with highly toxic chemicals publish maps in telephone books, calendars or brochures outlining the emergency planning zones where a hazardous release could occur. Your local emergency management department can also tell you how to contact your local emergency planning committee, your citizen's emergency response team or your citizen's corps if they exist in your area for advice on hazards that could affect you and your animals. Generally people start by planning for weather-related emergencies such as floods or wildfires that could affect their animals. Having a personal plan can reduce the chance of injury and loss of animal life in fast-moving events and also aid recovery efforts. If you look at general preparedness planning for families you have to have your general family plan built and a kit built and as part of that plan not as a separate plan but as part of that plan you need to decide how you're going to take care of your pets and your livestock. So it's not a family plan and an animal plan it's a plan.  They present unique problems and emergencies because many farms are vulnerable to natural disasters because of their location near ponds and rivers or in remote areas. Certainly the economical implications of a disaster for our livestock producers is significant during a disaster and so we must have plans in place for evacuation, response to the injuries, the difficulty that animals may be getting into as far as the livestock are concerned. Take time to find out where animals are usually located or areas they usually roam through. Knowing this will help you provide the information to emergency response or rescue personnel. It's critical to quickly locate animals after severe storms or an event such as an earthquake or flood because animals can be placed at further risk if electrical lines trees or fences are down or debris is scattered through areas they normally frequent. Emergency sirens and responders dressed out in protective clothing or unfamiliar odors can also upset or spook normally calm animals. There are things you can do if not at home when the emergency occurs one is to designate a willing neighbor or friend to care for your animals. If you think there may be occasions when you'll be unable to provide for animals because you work or because of physical impairments or not having access to a vehicle to transport animals you should make sure your plan includes a designated caretaker who can help you and your animals in an emergency. It's important for people to understand that not everybody is going to be home during every emergency and be able to implement their plan like they would have hoped to be able to. I think coordinating with friends and neighbors so that for instance if you live in a real area and something happens and you're not at home that your neighbors have some ability to help you out with your animal issues when possible. The person should have a key to the animal's quarters be familiar with the animals know your plan sheltering animals understand your evacuation plans and destinations know where evacuation supplies are stored and know which animals should be evacuated. To clarify that such a person is the designated choice you should sign a form designating that person as the animal care provider and releasing him or her from responsibility should one of the animals be injured or require medical treatment during or after the evacuation. Another option is to place stickers or placards on front and back doors barn doors or pasture entrances to notify neighbors and response personnel that the animals are on the property. The sign should state where you can be reached and where evacuation supplies are located. You should also provide a list near the evacuation supplies about the number type and possible location of all animals on the property their names and preferences and how the animals can be identified. Sometimes you may be forced to shelter your animals in place this is because a fast-moving hazard such as a passing toxic chemical cloud may require people and animals to shelter in place before evacuating. Officials in communities with large chemical complexes often instruct residents to immediately shelter when hearing an alert siren and to wait inside for further information. Some disasters require that you must take care of yourself sometimes without heat or running water for some number of days and that sort of way of taking care of yourself if a disaster means that you're not evacuating but rather you're stuck. Emergency officials may also stage evacuations and direct one part of the community to shelter and another part to evacuate to allow those most at risk to leave first or to reduce traffic volume on vulnerable highways or bridges. Once you choose a place to shelter your animals practice bringing them into an enclosed space. When evacuating to another state you should be aware of potential problems on returning home if proof of ownership licenses proof of rabies vaccination or a recent health certificate for your animals are missing. All animals should always be clearly identified with readily visible tags or collars and with the same visible identification on crates or vehicles. If you plan to evacuate by commercial plane, bus or rail you should contact the carrier for their policies on animal transport. The ADA requires all public and private ground transportation services to accommodate service animals. Dogs, cats, birds or other animals will not be allowed to be transported by rail or bus. Airlines must permit guide dogs or other service animals with appropriate identification to accompany an individual with a disability on a flight. Identification may include cards or other documentation, presence of a harness or markings on the harness tags or the credible verbal assurance of the passenger using the animal. Some airlines allow service animals as small as an infant to be held but larger service animals must have their own seat. Some airlines allow a small number of ticketed passengers to carry a cat, dog, bird or other small warm-blooded animal on board on a first come first serve basis. Providing the kennel containing the animal fits underneath the seat in front of the passenger and the owner has a health certificate signed by a licensed veterinarian within 10 days of departure. The animal must remain inside the kennel in the boarding area and during the flight with the door securely closed. Airlines also transport animals as checked baggage or as air cargo for a fee. Because some cargo space is not temperature controlled some airlines refuse to transport animals below or above certain temperatures to protect the animal. If your plan includes evacuating with animals to a friends or a family member's residence you should try to be as self-sufficient as possible by having adequate food and water, bedding, medications and cleanup supplies for all animals for at least three days. Oftentimes distribution networks for food and supplies are disrupted for several days following a disaster. If the animal is unfamiliar with children or other animals you should make sure the animal is always restrained. Service animals are generally allowed into public shelters with proper identification although such an environment can be confusing and stressful for both the animal and the owner. You should find out if your community's emergency plan includes protocols for keeping service animals with their owners throughout an evacuation and what officials will provide for you once at the shelter. For example some shelters may provide kennels and some may not. You should remember that strange odors and people may distract service animals used to normal routines and trained to respond only to their owner and you should be prepared to handle those extra burdens. Service animals in a disaster have to be looked at in a different light than a general companion animal when a person comes into a human shelter emergency planners and shelter planners have to realize that that is not just their pet that is an animal that aids them in some way for some kind of disability that they may have. Service animals by law in many states have to be accommodated in a public premise. The same is going to be true in a disaster shelter situation. If you have a service animal you should always carry proof from your doctor that the animal is needed for medical reasons and what the medical condition entails. This is in addition to the animal's current vaccination record and license. Planning an evacuation kit for animals should include the basics food proof of ownership and vaccinations licenses and medications. A great benefit is a recent photograph that can also be used for posters or on the internet if animals become separated from you. You should remember that unlike humans most animal medications are supplied by individual veterinarians who may be unavailable during an emergency or not able to prescribe across state lines. Have enough medication on hand or keep what your animals may need in your emergency kit. Many people will say it's the animal owner's responsibility to evacuate their pet and we believe by all means at the American Veterinary Medical Association that when you own an animal you should take the responsibility of preparing an evacuation kit and a first aid kit for your animal. Emergency medical supplies for pets are similar to those you likely have in your own disaster preparedness bag. Besides bottled water, detergent soap and towels for cleaning basic medical supplies for animals would include a tube of triple antibiotic ointment, ace bandages, two inch tape, gauze rolls, boric acid ointment, small cosmetic sponges and sterile sprays to clean animals eyes, surgical scissors and a splint easily obtained from hiking or sport stores.  Liquid bandages can also be helpful for severe cuts until the animal can be treated by a veterinarian. Consult your veterinarian when developing a first aid kit for equine and livestock or for exotic animals. There are also a number of sources on animal care that can be found on the internet or at local libraries. Having current rabies or license tags on animals can help you reunite with your animals if you become separated because such records are public and can be traced. For small animals a collar tag or tape placed inside the collar can provide information on animals name, your name, address and telephone number, an out-of-state telephone number or contact and the animal's veterinarian name, location and phone number. These can also be placed on a temporary neckband in emergencies. When you look at animal identification methods there's a lot people can do ahead of time to identify their animals in a permanent manner. Collars and tags are good but they can be lost. Probably the best method of identifying companion animals is through microchips, little radio frequency identification devices implanted under the skin that allow animal control or animal sheltering personnel to scan that animal and be able to trace that chip number back to that owner. However you should be aware that in the chaos following many disasters emergency response personnel and animal care managers as well as veterinarians may be overwhelmed and unable to systematically check for such records. Thus it is recommended that a visible means of identification be placed on any animal evacuated. Permanent identifiers for larger animals such as horses or livestock include microchips, tattoos, ear tags or notches or branding. Halter tags and neck chains with identification are also used in emergencies. Temporary measures include livestock marking crayons, non-toxic non-soluble spray paint or magic markers to write on the animal's side or to mark the hooves. Keeping these in your disaster supply kit means you can have them readily at hand when preparing your animals or if they lose their ID during transport. During transport each animal should have its own leash, collar or harness. Small animals should have separate collapsible or airline approved carriers with bedding for transport. For extended stays cat carriers should be large enough to hold a small litter pan and non-spill water bowl with room for the animal to lie down comfortably. Dog kennels or crates should be large enough for a non-spill water bowl and to allow the animal to stand up and turn around. All transport carriers should clearly identify the animal, its special needs including medications and common foods, the owner's name, home address and telephone contact, as well as similar information of an alternative contact. Riding directly on the kennel or providing information on duct tape on the animal's collar will help identify animals when stickers or placards are lost or destroyed. Identification, medical records and proof of ownership are equally important for small animals such as hamsters, gerbils, birds, reptiles and amphibians. Birds should be transported in small secure covered carriers and not allowed out in unfamiliar surroundings. A spray bottle for misting birds in hot weather and a heating pad or lamp to provide warmth in cold weather can help reduce stress at the evacuation site. Using appropriate carriers helps avoid stress induced illness. Transporting horses, livestock or large animals such as llamas or emus can be difficult. You can familiarize your animals with traveling and trailers by periodically leading them into the vehicle and providing treats to reward them. If not enough trailers are available to evacuate all your animals you should establish a network of contacts consisting of neighbors, local haulers, farmers, producers or other transportation providers to evacuate in a disaster. You should always try to keep your animals separated from other animals whenever possible to avoid spreading diseases. This is important for small animals as well as large ones. Animal shelters are set up so that species tend to stay with their own species so dogs will stay in a dog area, cats will hopefully be in a cat area, exotics in an exotic area. You want to try to minimize the co-mingling of species because anything you can do to decrease the amount of stress for the animal is what you want to do. Sometimes veterinarians and commercial kennels can provide safe lodging during or after extreme events. Other housing such as racetracks, fairgrounds, extension service facilities or even veterinary colleges may be available for your larger animals. If you think you might need their resources you should get in touch with them prior to an event so you'll have a better chance to use them in a major emergency. After flooding manure and waste lagoons can overflow potentially contaminating ground and surface waters. Emergency officials, owners and farm managers may have to work closely with environmental and health departments to avoid this impact. After floods animals that have stood in contaminated water may be at increased risk for skin infections or toxin induced diseases. Animals which have been in flood waters can also suffer hypothermia sometimes irreversibly. Cuts from debris also make your animals more susceptible to tetanus infection. Decontamination with detergent soap and water may be necessary for all animals exposed to hazardous chemicals or contaminated floodwaters. If you have a reptile or other animal that needs to keep essential bacteria on its skin only water should be used. Because decontamination is often very stressful on animals it's generally performed by trained emergency response or veterinary personnel who will likely tranquilize the animals and who are wearing the appropriate level of personal protective equipment to protect both the animals and the person decontaminating them. They also know the regulations regarding proper disposal of the cleansing solution because it is often considered hazardous waste. You should not attempt to decontaminate animals yourself unless you are very sure the contaminant will not harm you or you can wear appropriate protective clothing and breathing apparatus that you've been trained to use and maintain. Returning home may place additional stressors on your animals. You should check all fences and buildings to make sure they're intact and structurally sound. If temporary paddocks are used ensure animals are properly confined with adequate supplies of food and water. When bringing your animals back into a disaster affected area they're going to be disoriented they're going to be confused because landmarks are going to have changed the smells are going to change the area is going to be changed. So it's important to not push the animal back into normalcy too fast so introduce food slowly let the animal rest a lot. Help those animals acclimate back to their situation and become comfortable in the area that's been affected by the disaster. You should also survey for wild animals rats or poisonous snakes that may have taken up residence in your animals quarters during the evacuation. Unfamiliar scents can also confuse animals. If possible initially release animals into enclosed areas. Household pets should be kept indoors until you can supervise them outside to prevent them from encountering wildlife or debris. Flooding or hazardous releases can leave harmful substances on forage materials in paddocks or contaminate food or water supplies. Any food or bedding materials that have been contaminated or which show evidence of being damaged should be discarded. Contaminated debris in areas normally used by animals can be harmful if eaten or provide venues for cuts or bruises. It is critical that you check all areas for potential hazards before allowing animals to roam freely. You should also know how to obtain alternative food and water supplies for your animals as normal sources may be contaminated or disrupted during a disaster. You should not allow your pets to drink water from toilets or faucets if emergency officials recommend boiling all drinking water. If water sources are contaminated that means boiling water for your pets consumption as well. Animals may have a very difficult time adjusting to life after a disaster has struck again because they're creatures of habit and they're creatures of familiarity. So when things have changed and the smells have changed and the sites have changed that's going to stress an animal out and so it's going to take a while for the animal to feel comfortable and safe in an area again. Many states are now setting up programs for credentialing animal care workers to assist with animals in disasters. Some areas have excellent resources like livestock oriented search and rescue teams, horse search and rescue teams. In various states we have SARTs, state animal response teams or CARTS which are county-based animal response teams. You can find out more about these teams through your state emergency management agency. In the future it is unlikely volunteers will be able to work with or help rescue animals unless they've taken the training. I think it's important to establish a system so that when we have an incident of national significance such as Hurricane Katrina and a lot of people who want to come in and help that we can somehow pre-identify those people that are truly qualified to do some of the specific tasks that are needed. If animals left behind are lost or unaccounted for you should physically check animal control and animal shelters daily. Post lost animal notices and alert veterinarians and neighbors of lost animals. Trained and certified disaster animal response teams may be able to assist in getting animals to safety after major disasters or in caring for lost animals. The ability to go in and help people at probably some of the most chaotic instances in their life. The ability to go out in the field and find an animal and reunite it with its owner is probably one of the most fulfilling experiences I think that anybody in the animal welfare world or even in the first responder world could possibly have. Animals deserve our attention in good times and bad. Be prepared, have a plan, involve your veterinarian if animals will require special care and know how to protect your animals in and after an emergency. Your care is critical to your animals health and well-being. Don't wait until it's too late to help them or yourself.


You look around the country and in places like Maryland I'm proud to say and you see a set of best practices when it comes to what it means to respect voters in their voice, whether it's accessing the ballot box or tackling the issue of partisan gerrymining, which we know is something that the devil's our democracy and drives people crazy. So we have examples everywhere of what a national set of standards should look like they could preserve and protect our democracy. The problem is right now without the ability in Washington to set those national standards for the country we're sliding towards two Americas, one America where it's relatively easy and convenient to get to the ballot box where you have confidence that your voice and your vote will be heard and another America where it's increasingly difficult and you're seeing voter suppression. Remember the goal here is just allow an expansive and diverse electorate to be able to show up every two years at the ballot box, but we're going to have one America where you can do that and another America where you cannot.


And welcome. My name is Shannon Kemp, and I'm the Chief Digital Manager of Data Diversity. We'd like to thank you for joining the first installment of the monthly webinar series, Advanced Analytics with William McKnight. Today, William will be discussing and kicking off the brand new series with trends in enterprise advanced analytics. 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. If you'd like to chat with us or with each other, we certainly encourage you to do so. Just click the chat icon in the bottom middle of your screen for that feature. For questions, we will be collecting them via the Q&A in the bottom right-hand corner of your screen. Or if you'd like to tweet, we encourage you to share highlights or questions via Twitter using hashtag ADV analytics. 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 speaker for this series, William McKnight. William is the President of McKnight Consulting Group. He takes corporate information and turns it into a bottom line producing asset. He's worked with major companies worldwide, 15 of the global 2000 and many others. McKnight Consulting Group focuses on delivering business value and solving business problems, utilizing proven streamlined approaches on information management. His teams have won several best practice competitions for their implementations. He has been helping companies adopt big data solutions. And with that, I'm so excited to be working with William. We've been talking about working together for many, for quite a while now. So I'm excited to kick off this series with him. William, hello and welcome. Hello, Shannon. And hello, everyone. Thank you, Shannon. And thank you to Dataversity for giving me this forum. I've often wanted a recurring forum for webinars, something that I could string together a little continuity, shall we say. So some common themes and so on. And I finally have that, so I really appreciate that. And also, Shannon remind me to talk to you about the music. I don't know if I have that in the cloud, but I might want to update the music here. Okay. So for everybody else, thank you again for coming. And hopefully we make a productive hour out of this. This is really a foundation piece for the entire series that we're going to have this year. I'm really excited about the series. A lot of the things I'm going to be talking about here today, I'm going to be drilling in on the subsequent webinars in this series. And again, it's going to be the second Thursday of every month at this time. So mark the calendars for that. And without further ado, I will jump on into the content for today. First little bio slides. Shannon already gave my bio. You can find out a lot about me at McKnightCG.com or various other places. I do encourage you to get in touch. And this is what we do, strategy, training, and implementation of the things that I'm going to be talking about here today. I'm also privy to a lot of vendor analyst days types of things and briefings and so on. And so I stay up on both sides. I stay up on the analyst side. I stay up on the user side, the buying side of this. As a matter of fact, I've just been behind a couple of large scale surveys of people like I think yourselves, people who would be attracted to this kind of a webinar, people who have purchased data management solutions in the past year. And I've been able to, in the course of 50 questions, dig into their rationale, their beliefs, the process they go through, and so on. So from both sides of it, the user side and the vendor side, I'm going to bring some ideas here about trends in enterprise advanced analytics. Now, we're not just strictly going to be beholden to this year, 2019, although the idea for today did come from the fact that several of my clients are still developing their 2019 plans, as the case may be. You know, things got busy in December and so on. So this may be relevant to your 2019 plans, but whether you have them locked down or not, keep in mind they're never really locked down. So they must be fluid today. But we're not beholden to 2019. I'm going to be talking about some things that probably won't hit your radar hard until 2020 and beyond. At some point none of us know, but I'm going to look at 2020, maybe 2021 a little bit as well as we go forward here. And there are some foundational pieces that you really need to be putting in place today. But I also understand that I'm going to be talking about trends that you can't just chase trends. You cannot just chase any old trends and hope for the best. You have to pick your winners. And you have to really, in this marketplace, there's a lot going on and there's a lot more that the vendors are talking about that I'm not even going to be talking about here today because I don't believe it hits the plans for even the global 2000 yet. So I'm going to be talking about the things that I believe in, the things that I believe are going to stick based upon my vantage point and hopefully give you some ideas about trends. So why are they important? It's important because beyond the mountain is another mountain. There's another mountain out there. We can't even see it right now from where we are, but I do know we have to get over the one that we are climbing up right now and then we'll look out and then we'll see what's out there. But there will be another mountain and you cannot just jump mountains. You can't jump from this mountain to the mountain in the far range here with the picture. You have to jump to the next one. You have to go down this one actually and get up that next one and they build on one another. And foundational pieces are laid and you go forward in that way. I've heard people talk about skipping trends and catching the next wave and so on. Oh, aren't we lucky we didn't get into Hadoop or some such thing? Not really because whether your platform was absolutely correct for that unstructured analytical data or the data lake as the case may be for what you used Hadoop for, nonetheless, you were using Hadoop for that thing. And so that thing is still relevant. That thing has a business relevance and the platform we might talk about. But no, it's not great to be skipping trends, skipping mountains. And I'm going to try to help you.  So every one of you that's in information management, myself included, we have to keep our radars open to messages that are out there and we have to have filters and we have to really think about what we're hearing and pull in to our consciousness, pull into our plans, start trying to implement them in our enterprises. Those things that we think are going to be keepers for building a foundational future. We are in the business of data. So everything we do is really important. And I have a whole presentation on this. I'm so passionate about it. I so believe in this that our information is exploding. It's becoming real-time. It's really what differentiates us from our competitors and our quality impacts everything that we do. And there's really not a strategic business objective that is not completely either nailed or at least supported through the use of information. And I like to talk about this concept of having information under management. And I'm trying to help my clients get more and more information under management. It's not that they don't have data running around or data in loose places or maybe working for one department over there or something like that. Of course they do. Everybody has tons of data, but it's under management. Is it in a leverageable platform? Is it in the very best place to succeed for enterprise purposes? That's what I'm talking about. Getting data into that right vessel, that right platform to succeed. And sometimes it's already in the right platform, but the surroundings, the accoutrements, the process surrounding that is not to a level of maturity that it needs to be at. Speaking of maturity, data maturity is highly correlated to business success. And we've done studies to prove this out. I encourage all of you to have a maturity model and to follow it and know where you are and know what things you need to do to get to that next rung of the ladder, if you will. That next level of maturity. And start working on that because, again, hopefully you believe my concept here that you can't be skipping rungs of the ladder. You can't be skipping mountains or levels of maturity. You've got to climb up one, two, three, four, five. And guess what? Today the things that make a level, any level, say level three, that might be a level two a year from now. It just keeps changing like that.  The key here, the leadership here that's required is to do that while at the same time continuing to deliver business wins and to do it in a scalable fashion. But most companies are not, you know, very high in the maturity modeling and our studies have proven that most of companies out there are still at a fairly low level of maturity. So all the things that you hear from the vendor community, a lot of that is kind of out there for a lot of enterprises. That doesn't make it right though. That doesn't make it right for you. You still need to be saying, I don't really care about what the other enterprises are doing. I care about what the possibilities are and how to mobilize the energy that we have in this company towards the very best things for us, both short-term and long-term. That's really what we're about. And there is a standard. And that standard is level three in my view. And I'm not, this isn't the maturity talk. I'm not going to expound on this tremendously here. I will have a maturity talk later in this series. But there is a standard that we all need to be at with data. And there may be some other maturity models out there for other things that you may or may not really need to be at some kind of standard for. It's just nice to know. But data is not nice to know. Data is the foundation of our business. So it's important to be at a minimum level here of maturity. And again, I'm going to let you for today anyway define that as you need to. But we need to be moving up. Maturity modeling helps because it gives you a sense of priority. You can't skip levels. I've said that a few times. Maturity levels tend to move in harmony. So it's not just simply data maturity. That breaks down into data strategy, technology, maybe your processes, maybe your architecture. However you want to break it down, that's a good way by the way, those three or four things. But the point is they're going to move up in harmony. You can't be completely great on let's say data governance but you're a zero on data architecture and technology. It doesn't work that way. You will not be. Things will move in harmony. So that thing that you do not like to pursue as a company in the area of data, maybe you don't like data governance as a company. Nobody seems to like it. You look around the office. Nobody seems to like doing data governance. Well somebody's going to need to because that's an element that brings up everything else. So look at it that way. Mid-sized and smaller companies, a lot of the things I'm going to be talking about here today, I'm going to say when I do maturity modeling, you can add one because you're not going to be able to embrace all the things that I'm talking about here. But you guys in the enterprise, you guys that call yourselves a true enterprise, the upper-mid market, I'm going to say, if you're following that category or obviously above that, all these things apply. And there's no easy way out. And what we really need are champions and leaders out there that are going to pick up the helm and find ways to get this stuff in the enterprise and get it moving towards bottom line business success. Momentum is paramount. So what you're at a one today. I don't know necessarily that anybody is so far gone. At least I haven't encountered any client that's so far gone in terms of their data maturity so far behind that there are completely lost cause. But I will say that quite a few of them, the pants are on fire. And we need to get moving very fast right away and missteps are going to be fatal at this point to that company's success. Hopefully you're not one of them, but the pants are just going to remain on fire as we go forward here in this data realm because so much is happening and so much needs to happen. So this is my funny little slide here about one thing that we're here to do and I want to remind us before I get into the trends. Raise the foundation of your company. Raise it up. We're here to make sure that the things that we're doing today with X amount of effort, we can do in the future with less than X amount of effort. If you keep throwing people at the problem, you keep throwing hardware at the problem, you are basically on a treadmill not getting anywhere. We need to be thinking and doing outside of the box. And we need to be embracing the principles that I'm going to be talking about here today. We need some of them, if not most of them, to be successful as an organization. So keep that in mind that it's not good enough to sit still. That's the point there, really. And I know as I get into this, the money tree doesn't exist. We can't just go and say, oh, you know, William or some person said we need to be doing this or that. We have money for that. No, it doesn't work that way. It doesn't work that way for me, that's for sure. You know, we justify our efforts and that's okay. That's expected in business. That's what I try to do. I try to hitch my architecture and my maturity efforts to an application budget. Yeah, a real application budget. Not one that is for, let's say, a data warehouse. A data warehouse is not an initiative, by the way. Big data is not an initiative. If you are treating those things like initiatives at your company, you need to be relabeling here because ultimately what the business needs is the bottom line impact of what those things do. And these are enablers to that.  So nobody needs a data warehouse per se. They need the things that data warehousing does for them. And I really believe a data warehouse, for example, I'll get into this, but it enables so many things in the organization that the organization needs that sometimes you can be overwhelmed by all the possibilities within a lot of the things I'm going to be talking about here today. But you've got to hitch your efforts to a budget that does exist or that you create, and I encourage you to create budgets. As a matter of fact, that's the point of my next slide here. As data leaders, yes, of course, we are judged on the success of our users, making users satisfied. Now, don't look at this and go, well, we don't have central IT anymore, so this isn't really us. I don't care. We still have this thing called an IT professional. And I'm going to get into this a little bit later as well. A technology professional that has to do things that enable business leaders to succeed in business processes and functions to succeed. That's what I'm talking about. Wherever you sit in the organization, as a data professional, you are measured on user satisfaction, of course. And then, for many of us, we think that's it. We think that we keep other people happy. That's it. We're good. We're golden. But I'm here to say, being a data professional is not being in the internal staffing business. We're not simply throwing bodies at initiatives that everybody else in the company seems to come up with. We need to be coming up with initiatives as well because only we have the foresight into what the possibilities are out there. At least I hope that's the case. I hope you're looking out. You're here today. That's part of it, right? Getting your education and continually thinking about these things that are happening, these trends in this marketplace. Yeah, that's what's going to create business ROI and growth and, ultimately, more data maturity, which only is good for the longer-term user satisfaction and business ROI. And, of course, there's other things that we're probably measured on as well as data professionals. But I wanted to add this, whether it's explicit in your, what you call it, your employee review form, document, etc., whatever, it's there. It's there. And these are the things that set you apart as leaders, is coming up with the initiatives and creating the budget, creating the excitement over new things for the business that maybe only you can do. Okay, whoops. Now let's get into the top trends in enterprise analytics for 2019 and beyond. And I've belabored the and beyond bit here a bit as well. These are all the things that need to be on your radar now, whether they hit and enforce this year or not. So let's start with data warehousing and the like, okay? So I have an access for you that I've come up with that is how I think about things. On the left-hand side, we have data cultivation on the y-axis. So this is level of refinement. This is the relative level of refinement that we have put our data through to be in that, to be in that analytic platform. The data warehouse has some highly cultivated data in it. I think we can agree. I hope we can agree. And I hope your data, I hope you think about your data warehouse this way. I know some of them are data dumping grounds and maybe I or somebody else wouldn't necessarily call that a great data warehouse or whatever, but data warehouses are supposed to have highly cultivated data. And as the builder, not the user, the data management professional needs to understand how that data is going to be used. Because haven't we had the conversation in data a hundred or a thousand times about how far we need to take the data to get the users to use it? Yeah, I certainly have. If the point and click of a particular item is not extremely clear to that user, then that's my fault. And I haven't done what I need to do. I have to really, really cultivate that data and bring it to a high standard. Okay, that's the data warehouse. That's what we've lived with for the past 20 years. And what about this other thing called the data lake that's emerging?  I have had conversations with enterprises that go on and on about what they need, and then at the end of it, they'll say, yeah, we need a data lake to do all this. And what they really described is what we've been describing for 20 years, which is a data warehouse. Okay, a data lake is different. I know it's new and modern terminology and so forth, but it's different from the data warehouse. Now, some would say, well, the data lake, it's just become a data swamp and nobody's using it and blah, blah, blah. It's going through its early stage growing pains. There's no doubt about it, but I'm a believer in this idea that there is another level here that we need a different platform for. Another level of lower data cultivation and lower usage understanding by the builders. And so that's a data lake to me. So I'm not a data scientist, although some would try to call me that. They don't really understand our industry, but I'm building, right? And most people in this industry are building, and then there are the scientists, and the scientists are the ones that are going to be using the data in the data lake. I must admit, I don't fully understand everything that a data scientist is doing to the data lake that I'm part of building, and that's okay. That's okay, as you can see from the axis. My cultivation is low. My usage understanding is low. We still got to build it. It's not the data warehouse where we bake in derivations and summaries and all sorts of aggregates, and we make it all nice and nice. The data lake is going to be a lot of data, a lot more data than maybe goes on to the data warehouse. It's going to be big data as well as the non-big data. It's going to be all kinds of data types, eventually, when done well. And it's going to be bigger than the data warehouse in most enterprises. And there's another level, right here I'll call it, the data mart, which is all over the place. We have to have some level of cultivation of that data. We have to have some level of usage understanding, but maybe not to the level of the data warehouse because it might be a more narrow audience for the data mart. So my point about the trend is that we are entering a period where we are starting to understand this and we're having more sensible divisions of analytic platforms. And all of them are relevant and this is my chance to say, hey, I think the data lake is great as well, so that is an important trend. Speaking of the data lake, where are we putting data lakes? Well, the first data lakes and the first analytical places for big data was obviously in Hadoop. I believed in Hadoop. I wrote a book on Hadoop. I've been part of implementing Hadoop in many enterprises and still am, really. Hadoop has become HDFS. There's many components to it, but its definition is really kind of boiled back down to good old HDFS. But what my surveys are telling me, what my clients are telling me, is that they're much predisposed now to cloud storage over HDFS when it comes to the data lake, that they have not provisioned or the one that they have may be in a different data management platform. So cloud storage is more scalable, more persistent and available and less expensive. And that's really key here. Again, we're talking about data scientists. We're not talking about it. If we went into data lakes with the data warehouse mentality, maybe that's where we went wrong. Thinking that there's going to be hundreds of users and thousands of users and they're going to need highly cultivated data and so on. No, that's still the data warehouse, by the way. In the data warehouse, we're going to want to put that on relational database technology, not in cloud storage or HDFS. And the data lake is increasingly more in cloud storage, but you should understand the trade-offs here because some data lakes, it may still make sense to be in Hadoop, to be in HDFS. HDFS has better query performance. Again, does that matter based on what I've said? Oftentimes the answer is no. HDFS has storage formats, Parquet and Orc, storage, if you will, can't be used on cloud storage. Eventually that will change and cloud storage has some limits within it today that force us to deal with them in an awkward way, I'll say, when it comes to putting the data in and so forth. But it can be dealt with, and my clients are increasingly saying, we want lots and lots of data in there and we like the less expensive nature of it and we can't see having more than this handful of scientists in there. So what they're telling me is that they don't need the extra, I'll say extra formatting and so forth that does happen with HDFS. Obviously that is far less than a database and a database is still obviously a place for a database or two or ten or a hundred in the enterprise. Another trend speaking of clouds, cloud storage, multi-cloud is becoming the norm. And again, I'm a little surprised at this, but increasingly companies are actually putting down a criteria of when they select a data management platform they want to be able to go in different places. This obviously hurts some of the competitors out there and it helps some other of the competitors out there in the data management space, right? But disparate data-related objectives are difficult to pursue with agility in a single cloud strategy. It's almost like we need multiple clouds. We need our private cloud. We need multiple of the public clouds. Maybe we need a software as a service provider cloud that provides some unique capabilities. So increasingly we're getting to the point where there are a handful of cloud providers. I will say that there are three really and we know what they are that are handling most of the infrastructure as a service and the platform as a service. And that's of course AWS, Microsoft, and Google. And Kubernetes is emerging and a lot of organizations are really beefing up their skills in this in order to take advantage of multiple clouds. It's the foundation of this new generation of cloud-native big data, a container orchestration system that allows us to have our applications across multiple clouds. So this has become a really strong trend and it's time to break away from big data for a moment and talk about small data and talk about small data that's very important. And it's time to declare 2019 the year of something and I'll start by declaring it the year of master data management. Yeah, master data management. It's been around a while, but it hasn't really hit stride until I would say last year and now it's taking off because why? A couple reasons. One is because information is increasingly being viewed as an important enterprise asset. And if that's the case, we want to take care of it in the very best way possible. And MDM is a very good way, very best way I would say to take care of a certain a slice of data in the enterprise. And again, I said it was small data, not large data. High quality, but not high quantity data. The other trend is the fact that we are leaving multiple data platforms in place throughout the enterprise. And I've alluded to this already quite a bit. Databases, cloud storage, some Hadoop maybe, but many, many databases, many, many cloud storages, multiple clouds and so on and so forth. We just can't afford to have our master data mastered everywhere. Or we are incredibly inefficient as an organization. And you know what? In the bottom line, I've done so many justifications for MDM over the years. And I like to do it on TCO because that's the easiest way to do it. I can show the differences between a current state and a future state in terms of cost of ownership of that environment. Okay, that's all great. But in the back of my mind, the real benefit from MDM comes from the fact that you will finally have all the data in one place. And with that comes power, with that comes the ability to spin up so many applications that take advantage of that fact and you can drill in deep with your customers, with your product and so on. You can go places you never would if you don't have it mastered. So I know I've belabored this slide a little bit here, but I did want to impress upon you. I know many of you are already thinking of out there, obviously. You're not going to be alone if that's you. MDM is going to be big this year and going into the future. It's part of the future data management platform. It's part of maturity. Something else is part of that that I won't quite declare at the year of, but I will say it's very important, data virtualization. And whether this is using a standalone tool like a Denoto or using those data virtualization capabilities within your databases and your applications, one way or the other, data virtualization has become something you cannot avoid in an enterprise that's accepting. If you accept the fact that data is important and data is an asset of the organization, you're going to have it in multiple great environments, such as the ones I've already mentioned and more. And if that's the case, well, you're going to need virtualization because you cannot put all data everywhere. You cannot put all data everywhere. You have to make decisions about where it's going to be put but that should not lock you into a place where, well, I have some data here, I have some data there. It's going to be awkward to try to pull them together. It's going to take too long and forget it. You have to be able to pull that report, that analytic, that process step, whatever the case may be together from the data across your environment and data virtualization is really the answer to that. So begin to embrace it if you haven't already. That's going to be important. Okay. Oops, going the wrong way. 2019 is going to be the year of something else as well. I'm going to declare the graph. I didn't quite say graph database, but I said the graph. Yeah, the graph. There's a lot of graph capabilities within databases now that we should be taking advantage of and certainly there is places in our organization for graph databases today. It's not just for the nice pretty interface that it provides us with all of the nodes where we can drill in and we can see who's connecting to and what not. That's all great and that's really a strong part of the value proposition, but what I like about it is the speed with which you can find connections and the relative importance that you can find out about the nodes on the network, in a graph database. In a graph database. What a graph database does is it stores entities and relationships or entities or nodes, relationships or edges. We know about this, right? Nodes and edges have properties queries to reverse the graph. Nodes can be homogenous or heterogeneous so they can all be people like in the case of maybe the Twitter graph who's connected to who and so on, the LinkedIn graph, etc. or they can be heterogeneous and these heterogeneous nodes is kind of where I'm going in a lot of cases today, helping clients find better performing ways of doing lookups because no matter how many levels are involved in the graph, you seem to get some good consistent performance and you don't have to use self-referencing tables and other source of relational tricks to get to some of the same results that we now are discovering that we need to get to with our data. So we have to understand the relative importance of nodes because we have limited capacity as an organization to do service, build product, all the things that we need to do as an organization. We have to deploy it strategically and graph databases really help you understand what the important things are for you to focus on in an enterprise. That's what we're learning. So 2019 organizations are going to embrace this, find a way to embrace this in your organization. Do not keep doing what you've been doing. If you haven't been changing in the past decade as an organization, as a person, it is certainly time now to do that because if you haven't, let's back up a step here. As a data professional, and I counsel many data professionals out there sort of personally, I want you to improve your skills 20% every year. That means in the course of about four years or so, you're going to be 100% turned over because if you haven't, all you're doing is you're building up technical debt personally and one day this is all going to come to fruition and you're going to need to change 100% and you're not going to be able to do it because you're just not used to doing it. Keeping up your skills, keeping up your ability to change and so forth, that's the way to go. So look for ways to embrace some of the things that I'm talking about here that maybe aren't on your radar today. You can do it and get them going in your organization to success. Stream processing. Yeah, stream processing. ETL is great. It's legacy. It's going to be around. It's still going to be deployed. No doubt about it. But there's going to be cases, plenty of them where streaming data makes sense as well in the organization. So there's a lot of streaming, pure streaming applications out there. So data lakes for example, they seem to be evolving towards the cloud object storage which I mentioned before and stream computing as a matter in which to get that data in and out of the data lake. So streaming also makes sense when ETL is insufficient. So when is that? Data platforms operating at an enterprise-wide scale. Not a narrow scope, but an enterprise-wide scale. A high variety of data sources and real-time streaming data when the data is arriving in real-time manner on a very frequent basis. It can easily overwhelm ETL. With ETL, you can get scale or you can get performance usually out of your ETL, but it's hard to get both today at enterprise levels for some applications. Some applications. And that's why we're deploying more and more stream processing as a matter of fact. My going-in assumption to an application is we're doing stream. Talk me out of it. Tell me why we need to stay with ETL when you have the power, the same low TCO as you do with stream processing. So that's where I want to go with moving data. Moving data is still alive and well, by the way. It is alive and well and strong and going nowhere. So the whole idea of data integration strong as ever because of all the platforms we have the importance of data and so on. All the things I'm talking about here today. So let's leave this for a moment and I've decided to go really broad today and kind of fire hose you. Hopefully you're okay with this and hit on all the trends that I see because there's a lot of them today, you see. Artificial intelligence. I mean, you knew it was coming, right? Well, I think data's new highest use will be training AI algorithms. Yeah. AI is disruptive. We know this. That's true in many ways, shapes and forms in our enterprise. And what I am challenging my clients to do is anything that you have as an initiative that says BI change that to AI and think about that. Think about that. Think about doing that as AI. Now, if you think of the initiative as writing reports or building KPI or something of that nature, you're never going to get there in terms of thinking about it as AI. You have to get behind the reasoning for the report. The reasoning for the KPI and so on. You have to understand why that is being done. And oftentimes when you get to that why, that is what you can disrupt with artificial intelligence. So think about AI not necessarily just BI anymore and one way, sort of the low hanging fruit that I've been able to introduce AI into enterprises is through automation. So we see now the BI vendors are integrating a lot of AI to automate moving predictive insights from complex data into various processes throughout the enterprise. Yeah, AI. AI algorithms are going to be important and they are obviously trained on great data. So another mantra of mine is let no data escape. If you've been letting data escape you are just hamstringing your future AI efforts. So get them under control. A data lake might be appropriate for all that data if you don't have another place in mind. And I'm often asked by the way on this subject how do we architect our environments our data management environments for the inevitable AI future that we all see, right? And I don't know that I have a great answer to this. I've been listening to everybody on it. I've been thinking about it. I've been working in client environments on some of my thoughts and so on. I think the best answer I have to that question for now is to build a great data infrastructure. And by great data infrastructure I mean all the things I'm talking about here today. I'm talking about data lakes. I'm talking about having a great data warehouse in place not necessarily two or three or four but if you do have that many at least understand them and understand their distinctions and not have them just be chaotic messes that or whatever happens today happens today to them and we don't know and they're just going off on their own but have some data architecture over the top. Have it be able to be drawn on the back of a napkin drawn on a whiteboard consistently by many, many members of the team and so on. A real data architecture will go a long way in that inevitable AI future. Data is the foundation. Now when it comes to displaying data I know every enterprise out there is embracing data visualization to some degree but I think it's going to really take off because so many organizations are still doing things the legacy way and reporting and reporting is great obviously we need it obviously there's regulations we need to report ourselves you know into that arena there's going to be some battles not worth fighting okay here's your report fine but there's going to be some open users that we can really help out there and we can help them out with data visualization instead of reporting so again like before I said I challenged my clients any time they're thinking BI think AI, any time you're thinking reporting think data visualization think interactive data visualization maybe some of these some of you would look at this and go that's not very advanced but some of these you know mildly advanced at least you know data visualizations like Sparklines, bullet graphs, scatter plots and so on I have learned that this is a real skill here as well there's a great place in the organization for the foundational person the back end person but there's a great place in the organization for people that can do stuff like this for our user community so think about data visualization I think 2019 will go a long way in replacing a lot of the old reporting that we're still doing out there with data visualization alright what else self-service self-service now if I haven't already overloaded your plate you know as a data professional with things you need to be doing hang in there because I probably will by the end of this webinar but there's a lot of work for us to do building a great data foundation and there's got to be places where we let go and we let that go into not only the user community but also out there directly to the users meaning not necessarily the IT person that sits next to the user but the user themselves and technology what we're doing is we're delivering right curated data if we do these things metadata, data quality performance and we understand to some degree how that data is going to be used we will move in the right direction we will build what they need to do now where I don't want to see there be a big old drop off is in between again go back to this this is happened in spades over the years but a great organization will ward off this which is not having there be a big drop off between the builders and users and self-service is right for abuse and right for there to be a nice cliff there where nobody wants to get into in between and that has to be seamless that has there has to be a not not a bridge but the foundation built completely between the builders and the users and an understanding at an enterprise level of what each respective party respond with the responsibility is of each respective party here now the technology organization the technology professional can focus on more value-added activities I already mentioned developing new applications not just responding with your pad in hand what may I do for you today but building the new applications of the future yes we are going to be increasingly responsible for that I think a good way to look at a future organization is is it technology driven it's a strategy driven by technology people that really understand technology or is it being driven from someplace else incorporating new technologies to improve the performance of what you have in place today constantly improving constantly raising that foundation and technology therefore can become more of a partner rather than a roadblock to business users and there's still still many abusive relationships out there between the builders and the users and I'm going to touch on that a little bit later so I'll drop off of this right now but I'm going to stay on the theme of people yeah I'm going to talk about the chief data officer here because the chief data officer has gone mainstream and it certainly appears it's going to stay that way now this may have a little ramification on some of the oldies but goodies that we enjoy in terms of titles around our organization like the CIO because there's plenty of work for the CIO but then again if you look at it there's so much work for the CIO that sometimes it takes a CDO and some of the other things I'm going to be talking about on the next slide so we got to figure this out as organizations who's going to do what but the chief data officer there has become some I'll say some subtraction around what that CDO does for the organization and what that role can be and I've done some writing on this and I talked about these things these objectives manage the project portfolio may not occur to everybody that is one of the top responsibilities of the CDO but I see it as a top responsibility of the CDO I see the CDO adding to and removing things from the project portfolio of the enterprise based upon data yes that's right that's where data needs to be I see a high responsibility as creating accountability and a lot of this accountability comes in the form of you know where I'm going data governance the CDO is responsible for the data governance in the organization making sure we have data governance is at a high level of maturity now the CDO may or may not participate in, lead and so on but the CDO has got to make sure it's there and protecting the company it's become so important today but don't become overwhelmed with GDPR and the like as the CDO but that is part of the CDO's responsibility making sure that we hit the markers when it comes to protecting the company and GDPR may or may not impact your organization directly but it's the idea of it should create some impact on your organization whether you have customers in the EU or people data from the EU or not because something like that is probably working its way around the globe for us here in America and it's only a good idea to understand our business to the degree that you need to pursue that strategy now I'm going to pick things up a little bit I've talked about this somewhat organizations acknowledge that there is a chief information architect and a chief analytics officer in addition to that CDO that's right something at the C level that looks out for analytics and information and somebody that understands what we're talking about here today but understands it to some degree of depth now what we're also seeing is that those data science pioneers out there are getting locked in that's right if you are a data science pioneer you almost already know it today there's still the door is still kind of cracked open for the rest of us but data science pioneers are starting to take off and what they do is they let the data speak what is the data telling us about this business let's believe it they are using statistical models and machine learning and these have deep implications to how we work and we're seeing work changed as a result of the work of data science already and these organizations are dealing in algorithm management they are trading algorithms throughout the organization already they have means for doing that and they have metadata around their algorithms and they have Kubernetes and different places different ways that they can deploy those algorithms upon different data throughout the organization so that's what those organizations are becoming and if you can't even think that way you need to start moving in this direction of data science because what happened is there were some fake it till you make it data scientists out there in the past few years that's right they weren't trained PhDs they were business analysts but some of them actually made it they tried and they did it and they are data scientists and they did the thing that you have to do at first which is the fake it till you make it part of it so before you can become a great data scientist you got to get in there and start trying things out and that is what that first wave of data science leaders did so congrats to them but the door still open for others who do not consider themselves in that category I think it's going to be very important to be in that category I think it's going to be very important to company success let's talk about data team dynamics here because I've talked a little bit about this already the notion of the IT professional it's alive and well and there is an acknowledgement of the need for data deployments to be near the business unit and that's being reflected in organizational charts today so I'm seeing a sea change in what organizational charts look like I'm seeing an acknowledgement now finally that there are technology pockets out in organizations and it's okay we can be above board we don't have to be hidden in the closet about this yes we have technology here and yes it's okay and yes we have a good balance with central IT but another thing about data team dynamics that I'm seeing and I'm grateful for this by the way as a consultant there is a distance to change that we've had over the past decade probably decades you know it's still there of course but it's starting to get knocked down because organizations are starting to understand how important it is that we do these things and they can't be listening to the people the naysayers that would have to stay the course don't get in the cloud we don't embrace agile development that's for something else that's not for us never mind the data lake or big data or Hadoop who needs that stuff why do we need to change from reporting to visualization the people that are doing this master data management I can do that for you here just let me build a little database all that sort of mentality is starting to not play well in an enterprise we're starting to learn and that's good and our skills most of us on a call like this from the analytical side of things we have analytical skills our skills are necessary now not only in this environment here that we're used to the data warehouse, the data lake, the data mart but guess what our skills are now being needed back in the operational arena and that line between operational and analytical it's starting to get a little bit blurry okay analytics are starting to be embedded in operations today sometimes they come from the things that we learned on the post operational side of things but they are needed extremely a lot in the operational arena of our business speaking of which what have we been doing over the past few years to support that we have been building no-SQL databases to support that, yeah not just databases but no-SQL databases have been sort of modern and relevant to operational big data platform selection some of us have seen a slide like this showing all the different flavors of operational big data but SQL hasn't been sitting around on its laurels and saying okay I seed I seed the operational space our bread and butter I seed that to no-SQL no, SQL has been doing a lot that makes it still relevant for operations most of it or a lot of it has to do with its embracing of the cloud those databases becoming more cloud-adoptive and performance and the optimizer and so on SQL did not yield ground and I think that I'm not going to say no-SQL is no more or anything quite like that but I am saying that SQL is a strong competitor in the operational arena and if you are thinking that way you are probably in an okay direction there notice I left graph off of that off of that graph has some unique capabilities and now I'm just going to talk about something really quick here about the future new data sets that are coming our way there are several that are very interesting that it's a lot of fun to be looking out into the data community and understanding what data sets are available what data has gone for sale what data companies are collecting which may be available in the future and so on but one category of data set is bio-data and if you think about it bio-data could render all analytics obsolete because analytics are simply about trying to predict the future if you think about it well bio-data is the future that is going to tell you exactly what the future is going to be for that person theoretically anyway some traps and trepidations on the path there we already are seeing it but that is part of the inevitable AI future and data sets of that nature are going to have to be embraced by enterprises so again great data foundation embrace data science you'll be more than ready for something like that so in conclusion of the formal part here today there's more maturity in moving imperfectly than in merely perfecting defining the shortcomings anybody can sit here and point out the shortcomings in the environment but what about moving forward taking action taking action that gets to production not just gets to QA not just gets through development but gets to production that's where it counts we have to be thinking the full life cycle build credibility don't be afraid to fail I said fake it till you make it about the data scientist don't talk yourself out of having a new beginning be open that resistance that maybe you have or somebody else you've seen have that's not going to play well so we go forward it's about making progress and it's about the journey and we have to be on a journey forward we have to be embracing the trends that are going to be sticking around and I've shared with you from my perspective what I think some of those are here today for 2019 and beyond and before we launch into some Q&A here hopefully you've given me some of your questions I apologize I failed to say to enter them as we move along here but hopefully you've done that and you can still do that right now enter some questions for me for the next few minutes but I'll see you again the second Thursday of every month same time same bat channel and feel free to use the hashtag ADV analytics for anything you hear here or want me to necessarily see out there on so with that Shannon do we have any Q&A? William thank you so much for kicking off the series here what a great presentation and we've had lots of comments of what a great presentation no direct questions yet here although we had a huge yay year of MDM fingers crossed I bet I know where some that's coming from you know you're in a data management webinar when that's awesome so yes if you have questions feel free to submit them in the Q&A in the bottom right hand corner and of course just to remind everybody I will send a follow-up email from this presentation with links to the slides links to the recording by end of day Monday for this presentation so I'll see let me dive right in here great presentation lots of great presentation comments everyone's loving it but nobody has any questions you were very thorough I'll be more thorough and mention the Q&A part at the beginning next time we've got the lots of questions because Shannon you just answered that William how many companies have been using ontology based models do you know about I don't know that hasn't been part of my part of my surveys part of some of the industries I've been in so I don't really know about that sure so let's talk a little bit yes go ahead I'm just apologizing that I don't no worries William let's talk a little bit about the series so what are we going to be covering through the year you talked about how this we're kind of queuing everything up for the rest of the year yeah we are it's just an exciting series here that I'm just so passionate about I feel like enterprises need to embrace these things but I also feel like people need to embrace these things and one of the very best things that we call in my career now over a couple of decades or more actually is helping people helping people learn more, do more be more effective in their organizations that's my passion and that's what I'm going that's going to be my bent as I deliver these presentations it's going to be practical and actionable and we're going to drill in on things like the cloud versus HDFS I think we're going to have one on the different databases that are out there we're going to have one on streaming data and we're going to have one on getting the enterprise ready for AI with data I'll do a lot of these things here today but obviously I didn't have time to drill in on them but I will over the course this year so be sure to come on back I'm excited for that I love the topic of AI I'm just a geek what can I say we have another question in here for you are companies using GraphDB to analyze ERP structured and unstructured data and how effectively has these worked over a traditional SQL or in memory HANA type databases there's more than one way to skin a cat isn't there but it is important to get into one of the best ways to do it and it all depends now I didn't mention in memory databases but obviously that's the highest performing category of database but a lot of what people are telling me is that it's too expensive for any application that we can find here today so I am leaning on graph databases as a means to do that do anything that has to do with relationships networks, hierarchies when I hear these words I think about a graph database I will not be shy to introduce a graph database into that situation over a relational database because if it's truly a graph workload and that would obviously merit a separate 20 question discussion but if it were truly a graph workload it's going to do so much better in a graph database not just from the algorithms that you have access to but the ability to get to the relative performance connection points between different nodes on the graph these are things that are hard in relational databases and frankly I have done it with relational databases before graph databases were a thing and I had the self referencing tables and the display part forget it, I couldn't do that but I could do the sequel to make it happen but it was just so clumsy and long so I think graph databases far less code can achieve what sequel can do and then some obviously so you're going to avail yourself to a lot more if you do think about graph databases William thank you that's perfect and that just brings us right to the top of the hour again I'll send you over the comments a lot of great comments here just thanks for the great presentation and indeed it was a great presentation so excited to kick off this series this way and thanks everybody who has joined us and the attendees who are so engaged in everything we did we just love it hope to see you all next month or second Thursday and again I will send a follow up email by end of the day Monday with links to the slides and the recording I hope everyone has a great day William again thank you so much everybody have a great day bye bye