How BI/Analytics changed at Sage Summit 2016

Good morning everyone. Thanks for joining our How BI and Analytics Changed at Sage Summit 2016 webinar. My name is Johnny Girardi. I'm Data Self's founder and CEO. So again, thank you very much for joining us. The way I want to talk about how BI and Analytics changed is by pretty much telling the story of one of our clients. This particular client is a distribution company here in California and the CEO called me and told me, hey Johnny. Our decision making team, decision makers are very data driven. We love to analyze our data before we use our gut feeling. So we're very data driven. We look a lot of reports, dashboards, and it's been a very slow and time consuming process.

We have systems, we're having a lot of challenges getting data in a timely fashion. You know, we have a ERP system, we have a CRM system, we want to bring data from Google Analytics to see our website visitors, we have the payroll, we have social media and other systems. In all my team management, finance, operations, marketing, payroll and whatnot, we are usually waiting for my IT team and accounting team to put the data together for us. Sometimes it's just refreshing a report and sometimes it takes hours and even days to get people to get us the latest data. Sometimes we're in meetings, we're discussing things about the operation and a new question pops up. Usually many new questions pop up and we don't have the answer in our fingertips. We have to wait and ask for someone else to come up with the answer with the report or we have to wing it. Sometimes we cannot wait to get to the data. We have to just use our gut feeling and make decisions. Either way, waiting or winging, it's not the best scenario. Can you help us? So that's pretty much what the CEO told me a couple of years ago and I mentioned, well, my goal here is pretty much first of all, educate you as how can you move away from where you are into a better framework? Just talking about the concepts of making your process more efficient, giving your team access to your data, anytime, anywhere. And then I want to tell how we do it and if we can be a good fit for you. Awesome. But let me give a little bit of education. So I went to this conversation with the CEO and told him, well, why are you having challenges today? First of all, every time your management team or decision makers ask for a new report or dashboard or modify it, typically you have to talk with a consultant, an expert, an IT person, maybe a team of people and explain them what you want. Then this person let's say has to know where to find the data that has the answers to your questions. So they need to do what is called the data preparation. Data preparation is understanding the data sources, the databases, the tables, the fields, how to find the information, wherever it is to get to the answer. This work is very, very technical. Usually only consultants and IT people, kind of business analysts, kind of know how to find the data. Second, once you find the data, you need to put in a format that answers the question. So usually a report or a dashboard with charts and grids and calculations. What not like an Excel file, whatever it is. Typically the work of data presentation or building the report per se is also very technical and usually also involves a consultant, an IT person I call an expert. Finally, the person who built, let's say the dashboard report must send it to other people. Sometimes only one person. Cool, quick and easy. Build a report dashboard and email to the person. Sometimes you have several people. I don't know if you're building a report for salespeople and you have 50 salespeople or 10 or 20, whatever the number is, then sometimes this person building the report must create a specific report for each of these recipients, only focusing on the recipient's interest. Let's say if I'm an account manager for California, I only want to see California accounts. The person in Florida on the Florida. So a report for every single person and then email to all of them. These reports, very labor intensive, error prone process is just a mess. Is that how it's happening today? I asked the CEO. The guy said absolutely, we're having these issues. I didn't know the naming convention that you're putting here. But yes, that's what we have today. We have to use our IT team, consultants, what not to get all these reports together. And usually it takes many dozens of hours per month for these people to put reports for management. Well then I said, let me tell you how we can make this process almost completely automated. So here are your data sources today. You know, you have your ERP system, your CRM, Google Analytics and whatnot. There are then we call different data silos. As the CEO of the company or management, you have a single business and you want to see sometimes all the information you know, your finance and your CRM and your sales, your payroll in a single dashboard for you as a single business, even though you have these different data silos. So part of the solution to solve this problem is using a data warehouse. With a data warehouse, you can actually bring all your different data silos. You know, your ERP your CRM and whatnot into a single data repository. And from a reporting standpoint, you can blend the data together. You know, you can have your financials with your sales, your inventory, your services, your payroll, your Google Analytics, whatever data is, once you bring to the data warehouse, it's all the data from your business. And from a management standpoint, it's all kind of blended together. So the data warehouse usually is a way to tackle the data preparation phase. It's a highly technical job. It's very technical. The beauty is once you have mapped the data into the data warehouse, typically the whole data preparation becomes an automated process. Every day, every hour, whatever the schedule is, the data is brought into the data warehouse, it's crunched, it's consolidated, KPIs are created for you and from a decision making point, you just need to drag and drop into a reporting tool. So very, very easy. Typically also when you start with a data warehouse framework, you start with a single data source. So maybe phase one of your better BI will be just pulling data from your ERP system or your CRM. The good news is as you move forward with this project, eventually you'll bring all of your data silos into this consolidated data warehouse and now you can have a single view of of all of your business, of your data together blended manually. You remove the manual copy and pasting and massaging the data is all automatically refresh. It's all there. So this is part of the problem or solution. The next step is actually, well, now you need to give the information to decision makers. So typically you're going to be using an analytics platform to take care of the data presentation and and distribution of your reports. Now there are three main requirements that you should be looking at when you look at your analytics platform. First of all and very important is usually you must provide several different ways to render your reports and dashboards to people. You know, some people are sitting on their desks all day long, so you need to have desktop, web kind of interface. Some people are mobile, in meetings, maybe, you know, driving and whatnot. So you need to definitely enable web and mobile devices with that account information. Some people like to receive the reports and dashboards by email on a schedule basis. So they also must receive information through schedules like an email. So the first component is the analytics platform should provide different ways to give information to people the way that they want to receive information. Second is ease of use. Most decision makers, or a lot of them are not necessarily it savvy. So in order for them to open their reports and dashboards. And sometimes they have to change. They have to slice and dice, to drill down, to download information, even create new reports. So to enable them to do all of these things by themselves, because new questions pop up all the time, the solution must be really easy to use. So easy to use is one of the most important components. If I would say what is the single most important component is ease of use. Because today decision makers must be able to change the reports, create, download, do different things. A lot of the time, you know, new quests are popping all the time and they need to be self sufficient. Third requirement is fast. Who today likes to wait for several minutes or even hours in the report. People have no time. A good analytics platform must run reports in seconds regardless of how much data you have. So three requirements. Deliver data anytime, anywhere. Second, ease of use and third, speed. So that's pretty much what I told the CEO, what he should be looking for to solve his challenges of reporting. Before I move on, I want to make a quick poll with you guys asking what are your main reporting challenges? So let me just start this poll here. So if you don't mind, please enter, choose all the options that apply to you and don't forget to click the submit button. So make a selection and don't forget to click the submit button. I'm still getting plenty of answers. Let's wait a few more seconds. All right, five more seconds and I'm going to close the poll. Okay, much appreciated. Let me share the results. So what we have is slow in access, Anytime anywhere is the most popular. Okay, thank you very much for sharing your opinion. Let's move on here. So once I told the CEO how to solve the problem from a generic standpoint, I told him about why and how Data Self does it. I'm the founder of Data self and about 11 years ago when I founded the business, the vision has been since the beginning the following. Typically we work with mid market, you know, companies that have products such as Sage ERP Systems, Microsoft ERP Systems and CRM systems or Salesforce, things like that, acumatic and whatnot. And this, what we call this mid market or tier 2 ERP market has many reporting tools available and we call them mid market reporting RBI tools. They're good, they're inexpensive but quite often they they're not providing information anytime, anywhere, they're not as easy to use and they're not very fast. However, if you go to the Fortune 2000 world then you'll find great, great BI analytics platform that are really easy to Use really fast, that deliver information in different ways. But typically they're too expensive, too expensive for companies in what we call the mid market. So what we have been doing as a team at Dataself is what we go to the upper market. We go to Fortune 2000, we look at great technologies over there and we find the ones that fit the business model that we believe will work for mid sized companies. And we make the technology easy, simple and affordable. So that's what we do, we just bring the best of the breed and make it work for you. That's what we do. Make it enterprise grade technology, simple, affordable and quick to get return on investment. If you look at technology today, what we use is Tableau, Microsoft and this is Gartner. Gartner is one of the most reputable companies doing technology assessment for Fortune 2000 companies. And every year in February they release an assessment of how the Fortune 2000 companies are doing, how the Fortune 2000 BI vendors are doing the open market. Make a long story short, Tableau and Microsoft for several years have been considered leaders. They're one of the best technologies when it comes to BI and analytics. They're not perfect, they're not a magic wand, but boy, Even for Fortune 2000 they're one of the best. And that's what we bring to mid sized companies. If you look at the architecture that I showed before to solve the problems the data warehouse and analytics. We use SQL Server for data warehousing and SQL Server is one of the most widely used data warehousing platforms out there. Most of the people out there use SQL Server programming in order to build and maintain data warehouses, but we don't. Programming works, yes, absolutely works. But it's typically slow, expensive, time consuming and hard to maintain. Instead we use our ETL tool which allow us to do the extraction, transformation and loading so we can deploy, build and maintain data warehouses in a fairly code free environment, much easier and faster. So back to the vision. We're bringing upper market technology making it easier and faster and more affordable. And then on the analytics platform we use Tableau, which for the past four years in a row, Gartner has rewarded Tableau as the gold standard for analytics platform. So it's one of the easiest to use, one of the fastest to run and delivers information in many different ways. You know, desktop, web, mobile devices, emails and whatnot. Finally, we data self have been putting together this kind of technology for about 11 years now. And over the years we have learned how companies like you have been using BI in reporting. And every Time we see a new report created by a client of ours that can be generic, can be useful for our generic clients. We add to the out of the box solution. So today, not only we have all this great technology, Fortune 2000 technology that makes easy, fast, easy delivery for things, but we have more than 5,000 reports Dashboard KPIs as a starting point. It's a lot. I know most people don't need 5,000, but the point is quite often a lot of these out of the box reports you will need right off the bat because they are best practices. So many of our clients use extensively out of the box. Many of our clients use a fraction as a starting point. So a lot of value in the out of the box solution. Now some people ask us, why did you choose Tableau as the analytics platform? Well, when we chose Tableau about five years ago, they were not yet the leader in the Gardner magic quadrant. They were still in the middle of the pack. They were growing, but they were not yet. And we found it to be one of the easiest to use very fast and delivering different methods. And eventually we learned that. Why were they so easy to use? Well, most of these BI companies out there, they were created by kind of software engineers that thought, hey, I can do better, I can do flashier, I can make it run faster. And they created a BI solution. Well, Tableau didn't start that way. The founders were actually Stanford University professors and they hired psychologists and graphic designers to study how decision makers make sense out of business data. It's a process, it's a discovery process. And they have to go through this data discovery to make sense out of it. So these professors, they studied this process and at the end of the study they realize, huh, we can make a software that will help decision makers to walk through this journey. And then they hire the software engineers. So this whole history of Tableau started from the problem, the decision making problem and how the software could help people walk through the journey. So it's a very fascinating story. Now how Tableau does it. Something like this. What should I do now? Well, we humans are very visual animals. If we weren't, maybe we wouldn't have survived as a species. But here we are. When we see things visually, we quickly get insights. And what Tableau tries to do is give you visual cues quickly. Not with snakes, of course, but with data. So let's talk about it. Rows and columns reporting absolutely Tableau. And we support extensively rows and columns. It's critical. People need to see a lot of times numbers by the painting no brainer. But if I ask you how many nines are on this table, if you're like most of us, you're going to take several minutes, row by row, if you're going to tell how many there are. What the blood does is something like this. It's a subtle change. In this case, bold red. And now in a few seconds I can tell there's about 10. So you're shrinking the time that it takes to get to the insight so you have more time to make a decision and most importantly, act on. So that's the idea. Shorten the time to get to the right insight so you can do your decision making process and act on it. What if I look at a table like this where I see product type, product markets, profit, sales. If I ask you which market has the biggest sales or which products are not so profitable? Again, if you're like most of us, it's going to take a while. We're going to come with the answer. What the blood does something like this. Bigger bars, bigger sales, so you can see that central overall has bigger sales than all the other regions. And profitability is in red. In this case, not so profitable. In a few seconds you can tell which ones are not doing so well. Again, shrink the time to get to the inside. So you focus on decision making, process your gut feeling or not, and then act on it. Finally, yes, you want beautiful insight, you want beautiful reports and charts, but most importantly, you want insights. This is a business. You want to be sure that when you have your insights, the information is accurate. It tells you the story that you need to see. What about it? Well, if I Show this beautiful 3D pie chart, I find it very beautiful. It is very beautiful from my perspective. But if I ask you which slice is bigger, red or blue? You know, when we make 3D charts overall, because we put it at an angle, quite often we can misread because it's not so clear what we're looking at. Tableau does not support natively 3D charts because once you put in 2D, you have precision, you have insights. Non misleading insights in this case. Now, I can easily tell even without the numbers that the red slice is bigger than the blue. So again, tableau focus on giving insights, valuable insights, not misleading and beautiful ones. And because of that, they do not support graphical representations that can be misleading. So it's very cool to see that. Many people ask, but I want to see 2D. Well, if you want a 3D pie chart, if you want to see 3D pie chart, why not Export to Excel, very easy. And use Excel as a way to show your fluffy, not so insightful charts. Maybe you actually don't want to show people that you're not growing so much. So you put it in 3D and put in a chart and nobody sees. Well, as a philosophy, we data, self and tableau want to be sure that when you're making decision making process, you're having accurate, beautiful insights. How you do with that. If you export to Excel and use 3D, that's your call. But natively we want to be sure you get the right information. All right, before I jump into the product presentation, let me make another poll. So I'm going to launch the second poll which is what are your main reporting areas. So if you don't mind, please checking all the options and be sure to click the submit button. Please don't forget to click the submit button. I'm still getting many answers. All right, five more seconds. Okay, I'm closing it, let me share it. So financials shows us the biggest and then sales and then inventory management. Okay, thank you very much for your feedback. Alrighty, so let's go to the product demo and so far you know all these things I'm telling you right now. I told the CEO of this distribution company here in California what I'm going to show you next which is actually the product demo is what and how they have been doing since then. So the CEO told me, well, I have this monthly board meetings that I have to bring a lot of reports and it's time consuming, it is slow. Sometimes people give me reports an hour before my meeting and it's hard for me to digest the data to talk with the board I don't like. I want to have more time to have the insights. So when I talk with them I'm more intelligent and we have a more intelligent discussion. And most importantly, quite often in these board meetings my board is very demanding. I get questions and I don't have answers to my current reports. I have a bunch of printouts of reports and people ask me things I don't remember and I have to say, well let me make some notes, I'll get back to you. I want to be more self sufficient. I want to do things on the fly. Can you help us with that? And I said well let me show you. What I'm going to show you next then is the self service bi we do with data discovery. So three of these reports that the CEO was taking as a printed report. Now he goes with his iPad and he has all of these dashboard reports on the iPad and he actually built many of the reports himself. So I'm going to show three of the reports he built himself. The first report was or is. He needs to show the board this month's sales details. Sales by customer, by product, invoice number, invoice, date. Sometimes they discuss individual large sales. Second piece of information is they do a lot of marketing. Sorry, a lot of marketing on their website. So they want to see how website visitors may be affecting their sales trend. So they want to see sales from the ERP system along with website visit from Google Analytics, two different data sets they want to see together. Then they're shipping products all over US and Canada. So he wants to also see sales by geography, by state and how big the deals are. And then I'll show some other reports they have been using. All right, done with the PowerPoint. Thanks for your patience. I know sometimes it gets boring. Hope you find it informative. So this is the data self desktop client tool. We have the sub client tool. We have web and mobile devices. Most of the things I'm going to be doing with the desktop tool can also be done on a web browser or even using mobile devices such as tablets or smartphones. And by the way, we have native apps for iOS and Android for both tablet and smartphones. So the CEO came here and said, hey, I'm going to start building my three reports. The first report is this month. Sales details. Well, when building new reports from scratch, in this case, your first decision is what data source you're going to be using. In this case I'm looking revenues, data source or connector. You can have a lot of different data sources here. You know, financials, CRM, what not. In this case, I'm just picking the revenues because I want to see sales and I want to see no sales by customer this month, by product, invoice, number, invoice and whatnot. So how can I do it? Well, once I choose the connector, I can start selecting dimensions and measures and just pretty much drag and dropping. So when I see sales by customer, so here are the customers, I open the customer, I find customer name and I just drag and drop into my report. So these are all my customers. I want to see sales. So I take sales from here and I just drag and drop into my report and there it is, sales by customer. This is the total sales in the whole company history. Well, I just want to see this month's sales. So let me take invoice, date and drag and drop into my columns. So right now by default I'm seeing sales on a yearly basis. If I take the year and I click on the plus signal, I expand into quarters. If I click expand quarter, I go into months, I could go to weeks, I can expand to fiscal period, whatever the time bucket that you want to analyze, we usually build in the data warehouse those time buckets. And once we have built you can have many different time buckets. As a business user you just have to drag and drop and expand from the top level all the way to the bottom level. Very, very easy for business people to to change the time framework. Now I have here a lot of months, I just want to see this month sales. Well, I want to just filter one specific month of this whole report. What I do, I drag and drop. I drag and drop invoice date into my filters shelf and then I can select different kind of time buckets or choose relative dates which I'm going to do right now. And then I'm going to choose month this month. Now the beauty is this report now will always show this month, whatever the month is. Sometimes the board meetings, a board member would ask what about last month, last year, I mean different periods. Well, now the report is ready, I can click on this report and say previous month. There it is. Oh, maybe I want to see the last, I don't know, four months. There it is. Very easy, very intuitive. And let me go back to this month. Now I want to see sales by customer, by product, invoice number, invoice date and whatnot. Well, what do you have to do? You have to learn how to drag and drop. If I want to see product, product is here. I drag and drop between customer and sales and there it is by customer, by product. I see sales when I see invoice number, what I do. Yes, you guessed it, I drag and drop invoice number right here. Drag and drop between customer, product. There it is. Buy customer, invoice number, product, invoice date, same thing, drag and drop. And there it is in a nutshell. Many of our clients, they have learned how to build reports like this and many of the reports by watching my demo. If you know how to drag and drop, you can build a lot of reports. A lot of reports. True, some business people are so busy they don't want to bother. But if they wanted to, they could and usually have someone close to them, an assistant or a peer that would be the one building these reports very shortly and send their way and then they can make the decision making process. Ease of use is one of the most Critical requirements of a good analytics platform. And this is really one of the best, one of the easiest to use technology out there. Okay, so we just built our first report which is this month's sales details. How about marketing sales trends? Well, now I'm going to build a new report so I'm going to click a new sheet. And before Data Self, these companies, the distribution company in California, the IT team and their marketing team would usually work for about two days to put together sales and website visitors. It was very labor intensive. It was only a single report. And now once we deploy Data Self, we pull the Google Analytics data into the data warehouse and now it's all crunching every day the data is all ready. You just need to drag and drop and that's what the CEO did. So he need to see sales and website visitors. So in this case he drag and drop sales to my rows. So this is a total sales. I'm going to take invoice, date and put in my column. So I see sales here by year, I actually want to see by month. So I'm seeing now sales by month, the whole company history. And now I want to put website visitors, well as the decision maker. I don't care how they put it together. So Data Self and their IT and marketing worked into the data warehouse. Once it's in the data warehouse, it becomes another measure. So in this case, website visitors. What As a decision maker I have to learn how to do drag and drop. I take my website visitors, I drag and drop my report. So these are website visitors and I make a bar. So it's different than my sales, make the bar a little thinner. And then I tell the tool, show me this on a dual axis approach and look at that. Website visitors are my orange bars. Sales is my blue line. And I got the report from scratch. It's running refreshing every time that I open it. Completely automated. Two days before 2, three people working to get this together. Now it's completely ready automatically. If I make a variation as a decision maker I could. But for this example, that was what they was looking for. Awesome. Third report is geography analysis. I want to see sales by region, by state and deal size. So you can put any kind of geography component, bill to ship to location, whatever it is, it has an address, you can map it. So I'm going to choose in this case customer state. I want to choose how big the invoices are in my sales and ask the tool show me this on a map. And there it is on a map. Let's make the bubbles A little bigger and actually let me a little bigger here and let me centralize this. With a few clicks, I was able to see bigger bubbles, bigger sales. And the bubbles are sliced in different colors which represent small and medium and large invoices aggregated. Awesome. So this will report the CEO built by himself and then he wants to see on a dashboard on his iPad. So now we're going to create a dashboard and we're going to just drag and drop. So the map goes to the dashboard. I want to see the trend analysis just drag and drop at the bottom and. And then the other detailed report, I'm going to drag and drop whatever I want, just drag and drop and you get the result. Make this a little bigger here. So I just built this dashboard I can publish to my web server. And then sometimes when the CEO goes now to these meetings and a board member would ask the co, how are we doing? California, Texas, I'm going to be traveling over there in the past. The co make notes. I'll get back to you now on his iPad, you know, using his finger. Oh, California, in Texas, no problem. There it is. And then he can export this report to a PDF and email to the board member. Right on spot. Very easy, very intuitive, very dynamic. Again, empowering decision makers to shorten the time that it takes to get to the insight so we have more time to decide and most importantly, to act on. It's amazing. Okay, so this report, this example that I went through is what the CO went through. As you can tell, you do not need to be a rocket science to do this. Any person who wants to do it, they can. It's very easy, very intuitive. Now, how most people will be accessing the reports? Well, most people will not be building reports. They may be consuming reports that are ready. So typically they're going to log to a web portal. This web portal can be in your intranet or can be on the Internet or in the cloud. We have on prem in the cloud or hybrid deployments. So you have options. The thing is, it's a highly secured framework. This is designed for Fortune 2000 companies. And only people who know the URL of this portal and have the right credentials will be able to log to the system. Now, when you log to the system, let's say using your mobile device, then you can only see what we call the projects that you have access to. So let's say if I'm a salesperson, I would only go automatically into the sales project, only with the sales reports and dashboards. If I'm the cfo maybe I have access to the accounting or financials project and, and maybe to the older projects, the financial, the payroll services and warehouse and whatnot. Now the other thing is as a user, once I opens a report, let me just open one of them here. Then the tool can be configured to be user sensitive. So let's say this is a sale showing top customer by sales change since last year to date, customers who grew the most in sales and the ones who declined the most in sales since last year to date. Well this same report can be for all users. So if I'm the rep for California, I only see top customers change in California. If I'm in Florida, only see Florida. If I'm the VP of sales, I see the top customers by change across all territories. So same report answering questions for everyone. Now let me do some search here. Let me look for financials especially. There are so many people looking for financials here. So here looking at some financial dashboards and reports, let me open one of them. So now I'm looking at this financial report that shows me by different location, some ratios, you know, HR expenses ratio versus my revenues, overhead and whatnot. Now when the person designed this report, this person can design how the experience will be for other users. So let's say maybe the report cannot be changed because it is in a certain way. Or maybe you can change the periods to look at different period. Or maybe you can allow them to drill down or slice and dice in certain ways. So when you build a report you control what other users will be able to do with the report. In this example, suppose I'm a cfo, I come when I see on Atlanta and I click on the Atlanta box and I have two different drill down capabilities. Maybe I could have only one. When I click I go straight into the drill down. Maybe I can have 10 options. In this case I have two. Now I select one of the two and when I click on it I go into a completely different report. In this case it is still a financials report, but maybe I send the CFO when click on the Atlanta, into a CRM report, into a payroll report, into a Google Analytics report. It doesn't matter all the data in the data warehouse, you can control the user experience as they go through this decision making process. In this case as a CFO I get into the financial details. If I click here, the report is dynamic and it changes on the fly. So all the things very dynamic. Now as a CFO maybe I'm a power user and while the non power users can only navigate in this predefined configuration. As a power user, I can go anywhere that I want. So as a power user, I have the Edit button. I click edit and now I could be doing this on my tablet. I go into this new edit mode and say, hey, I'm seeing segment one and two, segment one and two and some information. I actually want to add segment three and I could be using my finger. Segment three let me drag and drop at the end of my sequence. So I have segment two, one and three, maybe. No, I'm going to put at the beginning. As a power user, I can take an existing report and completely change it and I might have rights to save it back to the original or maybe not only save it to myself. Security controls what people can do. But the beauty is you give decision makers, you empower decision makers with a tool that they will be able to change things by themselves. I'm not going to change, I'm not going to save. The last thing I want to show on the product is, well, what if I want to receive this report by email? I don't know, every Friday or whatnot. As a user, I can click subscribe and I can tell. Send me this report. Every Friday, 6:00pm I click subscribe. Guess what? Now, every Friday, 6:00pm I got an email with this refresh report. This report refreshed. And if I click on the report on the email, it jumps back into this portal and then I can start slicing and dicing again, giving people options to consume the reports. All right, I think you have found the presentation insightful. I want to go back to my PowerPoint. We have a few more things to cover. All right, now I want to talk about the pros and cons about data warehousing. Some people say, wow, data warehousing. I heard it is expensive, it's time consuming, It's a hell. What about it? Well, let's talk about it. What are the cons? Yes, it requires very skilled people. Be sure if you're going to be building a data warehouse, the people doing it are very skilled. And most importantly, be sure you retain them or you have access to them in the future. Because if you have to let them go for a while and then two years down the road to get them back again to make maintenance, and they're not available. Good luck. So, yes, it requires skilled people. A lot of the data is not in real time. Yes, it's possible to make data real time, but most of the time it's usually not real time. Sometimes that can be a Problem for some people. And finally, it does require additional investment. Absolutely. Now, what are the pros? First of all, in the data warehouse you do the data preparation. So you bring all your data silos together, you make all of your rules, you define how your revenues are, how your gross profits are, how your expenses are. And once you define those rules in the data warehouse, they become the single version of the truth. So every time you build a report showing your metrics, they all pull the data from the same version. So you guarantee the reports will have the same rules behind the scenes. Sometimes it's a very critical benefit because sometimes you have different reports, they're using different calculations and you're comparing apples to pie. Apples and you don't even know about with the data warehouse usually don't have that problem. The other thing is, hey, you can have all of your data together in a single place as I showed, just drag and drop. And you can see your financials, your Google Analytics, analytics, your sales CRM all together. It makes easy for decision making process. Finally, with the data warehouse, reports will be easy and will run fast. And again, easy and fast is critical. How about Tableau pros and cons? First of all is not embedded automatically in your systems. It's a standalone product. So people say, hey, I actually want to be part of my CRM. I want to be part of my urp. Sometimes it can be done. Absolutely. Sometimes it can. But it's a standalone product that must be inserted manually into other processes in case you want to. So sometimes people see that as a con. Some popular Visualizations such as 3D charts are not built in. Can you do them? Yes, but it's a very hard process. Usually it's better to export to Excel than do outside. Some people, they like, they want it. So hey, either you start using some other tool or always export to another tool that will support this kind of potentially deceiving data representations. Finally, it is not inexpensive. It requires some additional investment. It does not break the bank, but it requires additional investment. What are the pros? The most important ease of use. As I mentioned, Gardner has rewarded Tableau for four years in a row as the gold standard for analytics. One of the most important things of the decision is because of their ease of use. It's not a magic wand, it's not perfect, but it's one of the easiest to use reporting tool available out there. Speed run, report very fast if focused on beautiful insights. Again, the idea is to be sure that when your decision making team is looking at your data and charts, they show information accurately. So very important. And standalone product actually overall I think is a big benefit because as a company you don't only have an ERP system or only a CRM system. You probably have an erp, a CRM, a payroll. Gomez, you have a lot of different systems and having a product that can work across all the products is a great benefit. Quite often decision makers are not users of your ERP and CRM or not. They're not. So why have a tool that is always embedded in those systems? You have a tool that can actually be independent from those systems. So to me, standalone is a big benefit. Should you buy or should you build yourself everything that I talked about here, you can build it yourself? Absolutely. Now what are the pros and cons of one or the other? So if you build your own, what are the cons? First of all, it's going to cost you a lot of money. Most likely you have to find and retain skilled people. Usually going to take months, sometimes years to put together a data warehouse very well designed in an analytics platform with a lot of reports and dashboards. Typically this takes several months and sometimes years of investing into this costly, slow and hard to retain people. Be sure if you're doing this and building yourself, be sure to retain this team that are doing it. Because in the future, especially the back end, the more complicated parts, because in the future, in two, three years, if you have to maintain that backend and that people is no longer with you, it can be very, very costly to maintain someone else's code. So usually long term maintenance can be very, very challenging. What are the pros? Well, from the beginning you control the process and you only focus on things that you want specific for you. So sometimes that can be a very good benefit for your business. What if you buy an off the shelf solution like Data Self? Well, cons is going to cost you more money. Now it's going to be tied to a platform. We use SQL Server and Tableau. It's a great platform but it's tied to this platform. Be sure that if you buy from an off the shelf like Dataself that the technology that they're offering is industry standard and is one of the best. And we check those boxes. So if you go with us, yes, we are tied to SQL Server and Tableau but boy you're tied to one of the best out there. So higher license cost and tight to platform, those could be negative components unless you are looking at the right perspective. What are the pros? Well, everything can be customized specific for your needs. So even though you have 5,000 reports as a starting point and you only need 100, no problem. We delete the other 4,900 and we can completely customize those 100 whatever you want specific for your needs. So having an out of the box solution as a starting point like we do is usually not a problem. To customize specific for your own needs speed typically in days or weeks you have a system that will take you probably years to build from scratch. So much easier and faster to get the result. We've been around for a long time. We use technology that is widely supported. So it's very easy and fast to maintain a technology like ours if you buy it already because we're going to be there to support you and you can find in the market a lot of people that know SQL Server that know tableau that will help you support in case you don't want to use us as a resource. We use best practices to build. So usually you get a great well designed technology and at the end of the day it would be a lower total cost of ownership. If I would say in a nutshell, why I would recommend buying than building yourself is because you either pay it now or you pay later. If you buy something ready that works well for you, you pay more now, but in the long run you pay less because you have a lot of things is well supported have best practices, low cost of ownership. If you build yourself, yes, you don't pay as much money now in licenses, but you'll be paying people and rehiring people and changing people to do it yourself. So pros and cons, you have to see which one is the best for you. What's next? We're getting out of at the end of the presentation. So first of all, if you want to see data self with your own data, send me an email. A lot of the times when we do a presentation of Data self using the client's data or the prospect's data, the sales process becomes one hour demo, some pricing, discussion requirements, what not, and the decision to go forward or not is a quick yes or no. So I highly recommend if you're interested in Data self and you can send us your data, we'll sign NDAs and whatnot, you'll see that this can be very beneficial to see if it's a good fit or not. If you move forward quickly with us and you can order by the end of this month, we have a special promotion running two power users for free. My last poll here, if you don't mind, give Me your feedback before we open the Q and A session is what would you like to do next? So if you like to please check the boxes and don't forget to click the submit button. Be sure to click the submit button. Five more seconds. Alrighty, let me share the result. So a lot of people want to learn about data warehousing Tableau, the out of the box test drive. Okay, awesome. We'll be in touch with all of you giving more information. Let me hide this and let me open for questions and answers. So if you have questions unanswered please go to the GoToWebinar panel to the question section and just send me my way and I'll be answering. So let me see if we have any questions here. So the first question from Taylor is does this work with Google Analytics? Yes. Taylor, thanks for the question. The actual demo that I did when I was showing website visitors website visitors data was coming from Google Analytics. So yes, we can combine your Google Analytics data with other data. Taylor, thanks for your question. The other question here is from Carol. What source systems you support natively out of the box? Carol, thanks for your question. To answer this question actually let me go to. Sorry to my website. So if you go to my dataself.com go to Solutions and click analytics by ERP and CRM it will show you here the current out of the box solution. I mean we work with all ERPs, all data sources. Yes, we work with all of them. But the 5,000 reports KPIs we have built currently for these systems we have Microsoft Sage Infor and we are actually in the process of deploying the Salesforce connector as well as Acumatica and Netsuite. We should be adding to this list very shortly and we support most of the older versions. Let's say you are in a Dynamics or Sage product from you know the last version you have is from 2004. We do support old versions as well. Carol, thanks for your question. Let me see other questions here. Question from Mary how much data self cost? Very good question. Let me put it this way. You can buy data self or you can subscribe to it. It has nothing to do to how you're going to deploy it. You can buy it or you can subscribe. Regardless it's going to be on an on premises in the cloud kind of solution. I'm going to give you the subscription pricing because many people start with the subscription because it makes it affordable to get started and then usually down the road they go to up to purchasing in case they Want to change the expense from a capital to an expenditure or vice versa. Categorization. So if you subscribe the entry level system, the entry level licenses is for five users. So you have the data warehouse, the web server, five user licenses in all the reports and dashboards. And this will cost you less than $1,000 per month. We require year commitments. But in a nutshell, for less than $1,000 you can have five users with the data warehouse, the web server and all those reports. So it does cost some money. But if you look at the benefit you might get from it, it's usually far bigger than the actual expense. Mary, thank you very much for your question. Let's see if we have more questions here. So Tim is asking to show again the architecture of the solution and give a little explanation. Tim, thanks for your question. Let me go back to my website instead and go to solutions and architecture. So this is the architect of our solution. Let me click. So I'm going to get a bigger picture. So what we have here is your data sources, your ERP systems, your M and whatnot, Google Analytics. And then the data is brought over into a SQL Server data warehouse. Most of this process will be handled by the etl. So you don't need to do programming to bring the data, refresh it and massage the data. Then we have this. It shows like a little cloud, but actually it's a web server. It's not necessarily a cloud. It could be cloud, yes, but it could be a web server behind your firewall. So it's a web server powered by Tableau. We have a Tableau OEM version that is a little bit more affordable than the Tableau regular. Those are details. We can talk later if you're interested. But then the data is crushed further from the data warehouse and then Tableau can deliver information using desktop, web, mobile devices and emails. In wrapping all of these great software components, we have all of the templates to do these 5,000 reports, dashboards and KPIs. Usually the data flows from the data source all the way to the end on, let's say the refresh of the data warehouse and the data in the analytics usually is done on a scheduled basis. So it's kind of batch basis. But depending on your data sources, the refresh can also be real time. So you can have some report that you click on the user interface refresh and it will pull the data right from the source all the way to the actual device. We don't recommend that. Or be very careful when you're doing because once you give a tool that people can easily slice and dice, build reports and refresh data that is very easy to do that they may be refreshing this a lot more and you may slow down your data sources. You want to be sure you do not slow down your data sources. You don't want to slow down your GL transactions, your invoices and whatnot. So usually the data warehouse will prevent that from happening. If you do refreshes on a batch basis, maybe every 15 minutes, you can refresh information that should be more real time for end users. Much appreciated. Your question well, we are pretty much wrapping up our presentation. We have some more questions, but we will address on a one on one basis. I really appreciate your time and interest. I hope you found this webinar informative. If you want to discuss things about it, please feel free to call me or email me. Unfortunately, I forgot to record this webinar, but we'll make a recording and we'll send you away probably the next day or so. So if you want to share with other people, you'll have a record. Folks, thank you for your time and interest. Have a happy Thursday and feel free to contact me anytime. Thank you. It.