DataSelf Analytics and Tableau for Sage ERP and CRM

Thanks for joining us. Happy Thursday. My name is Johnny Girardi. I'm the founder and CEO of Data Self and I appreciate your time and interest in learning more about BI and analytics for Sage, ERP and CRM. And we're going to be mostly focusing on Data Self and Tableau. So let's get started. The first part of this presentation, I will talk a little bit about generic DI and analytics concepts regardless of Data Self, regardless of Tableau, some informational content for you. Then I'll focus about the Data Self approach, why and how we do it. We'll spend quite a bit of time showing the product per se, we'll talk about pros and cons and then we'll open a Q and A session. The way we like to talk about this whole thing is telling the story of one of our clients, a distribution company here in California. A couple of years ago, the CEO of this company called me and he said, Johnny, my decision makers were very data driven. We like to look at data before we make decisions. Nowadays we have in our company several different data silos. They have Sage ERP system, CRM system, Google Analytics to look at website visitors, a separate payroll system, social media data, and a bunch of Excel and access databases. All of this data is of the business is spread out in different silos in my management team. Every time they want a report or maybe a new report, it becomes a complicated process. It takes my I team and several people to work and get data from one place to another in Excel and massage the data. In a nutshell, it's taking a lot of effort to maintain our reporting solution. A lot of people working a lot of hours every month. It's very expensive. The cost of this effort is not such a big a problem because we're big, we can afford all of this manpower invested in it. But my major issue is as decision makers because we want to see data before we make decisions. Too often we have to wait until we get the reports. So there are delays in decisions because the data is not ready for us to make decisions or we have to just wing it, make decisions without getting the data, either waiting or winging. It's not great and I want to get out of the situation. Can you help me? That was pretty much what the CEO told me as the main challenge and I said, well, sounds like I can. But let me tell you, before you tell you how we do it, let me give a little bit of education about why this is happening and how you can solve many of your issues. Regardless of what technology you Choose. So today, when you ask for, let's say a new report, there are three phases required to get that job done. The first phase is called data preparation. Data preparation is a person, or maybe more than one person that will hear your question, your business problem, and they'll have to find where is the data. To answer this question, they have to know the source database, let's say the Sage ERP system, the CRM system, Google Analytics, whatever it is. This person that will find the data, the tables and fields and whatnot, is usually highly technical, specialized, quite often a consultant, sometimes an outside consultant. And it's a very tough job to find the data to do the data preparation. Once the data has been found, then comes the next phase which is called the data presentation. Now it's actually building the report, maybe a grid, some summaries, maybe some charts, filters and whatnot. Building reports usually is also a highly technical job. Requires someone that knows crystal reporting services, Excel and whatnot, and then a lot of time involved in building the actual report. The third and last phase is the data distribution. Well, typically the person who built the report is not the person who needs the report. So it must be sent to someone else. If there's only one person, quick and easy, that needs to receive the report. But if you need to send the report to a large number of people, 5, 10, 20, 50, 100 people, then it becomes slow, time consuming and error prone. So these are typically the processes required to get new or modified reports done. Now, one of the best ways to automate a lot of this process that you have today is using what is called a data warehouse to do the data preparation. What is a data warehouse? A data warehouse is a database dedicated for reporting purposes. All your data from your ERP system and other sources can be brought into the data warehouse and the data can be blended together. If you're looking for the ERP system, maybe you want to combine your purchasing with your inventory on hand, with your sales order to the projections. Maybe you want to get your financial information drilled down to more details that is not in the same GL side. In the data warehouse we can blend any data together. Sage data with social media, with payroll, whatnot in the data warehouse is just data together and it's blended. Now to build and maintain a data warehouse is also a very technical job, very complicated. Yes it is. But the beauty is once the data warehouse has been configured and mapped to pull this data together, once that is done, like a one time procedure, it becomes completely automated every day, every time, the schedule is the Data will be refreshed automatically, completely without human intervention. So data preparation becomes no longer a problem once you have a data warehouse, because the data warehouse will automate a lot of this massage before was done manually. Then you will need an analytics platform to do your data presentation and data distribution. Now, there are three main requirements or three main important features of a good analytics platform. The first one is because people have different working styles. Some people are working always in front of a desktop, some people are carrying their notebook to different places, some people are using mobile devices and some people want to receive their reports and dashboards by email. Or maybe some people want a blend of those options. So the first main feature of strong analytics platform is that we'll provide ways to render information to desktop, web, mobile devices and emails. So that's critical and it must support that. The second main feature is ease of use. A lot of the decision makers today, they need and they want to be empowered with a reporting tool that they can easily access the reports anytime and anywhere, that they can easily slice and dice their data, drill down to data, download and even build new reports from scratch. New questions are popping all over all the time and many decision makers want to be self sufficient. So I consider the most important feature of an analytics platform as being ease of use in allowing decision makers to take ownership of a lot of the report ad hoc analysis. The last main feature is speed. You want your reports to run in seconds. Regardless of how big your database is and how many databases you have, you want reports to run in seconds. So be sure that your platform will be fast to render reports very, very quickly. So I told the CEO these concepts that regardless of which direction you go, if you use it yourself or not, these are features BI feature that will get you from where you are today into a much better, faster, less time consuming and more empowering BI solution. Now before I jump into data self, I'd like to open a quick poll to check some of your questions. So let me start a poll. What are your main reporting challenges? So be able to see on your screen now 5 options. Please check as many options applies to you and please be sure to press the submit button. A few more seconds. Okay, five more seconds. Okay, thank you. I'm going to close and I'm going to share with you the result there it is difficult to use the most critical one, the most popular one and lack of data silo consolidation. Okay, thank you very much, I appreciate that. Now so I just talked about the concepts of, you know, how the challenges and how to solve those Challenges from a generic standpoint, how does Data Self does it? I'm the founder of Data Self. I founded data self in 2005. And when I founded Data Self, the vision of the business has been quite simple. Companies in the mid market that use products like Sage and competing products, the decision makers of these companies, they need great reporting tools. But the ones available in this market are usually they're inexpensive but they're not very easy to use and they're not fast, so usually complicated and slow. And if you go to the Fortune 2000 world, there you'll find great BI solutions that are really easy to use and run really fast. But quite often they are too complicated to deploy and too expensive. So the vision Data itself has been. Well, let's actually look closely in the Fortune 2000 BI world and let's find the right tools and let's bring them to the mid market. Let's make them simple, let's make them better, let's make them affordable. So let's create our own expertise and do that. So that's what we do. What Data Self does is we bring the best of the breed technology out there. We make it simple, we make it faster, we make it affordable, we make it work for you as a mid sized company. This is Gartner. Gartner is one of the most reputable companies doing technology assessment for Fortune 2000 companies. In every February they tell or they assess how well the BI vendors are doing in the Fortune 2000 world. Make a long story short, Tableau and Microsoft had been leaders in the BI magic quadrant from Garner for several years in a row. So this is one of the best technology used by Fortune 2000 companies from a BI standpoint. And that's what we bring to the mid market. We make it simple, we make it better. Let me talk about that. So when I show again the architecture of how to solve those problems the CEO was telling me about, we use SQL Server as the data warehouse platform. SQL Server is one of the most widely used data warehouse technologies available out there. However, if you just go and use SQL by itself for data warehousing, it becomes very complicated. Well, we have added our own extraction and transformation and loading tool that pretty much eliminates SQL Server programming. So we make SQL Server data warehousing easier, faster and more affordable for mid sized companies. So we simplify it and then we have added Tableau as the analytics platform. And for the past four years in a row, Tableau has been considered the gold standard for analytics platform for Fortune 2000. So it's one of the best technologies out there. So that's where we bring as well. So from a technology platform standpoint, this is exactly meeting the vision of data self. We're bringing the best of the bridge technology from Portugal 2000. We're making simpler, we're making better. Now, for the past 11 years, we have been seeing how our clients use this kind of technology for their own reporting. And every time we see a report that they create that could be valuable for our clients, we add to the out of the box solution. So today we have more than 5,000 reports, dashboards and KPIs that we have out of the box. They cover financials, payables, receivables, sales, inventory, purchasing, whatnot. So there's a lot of reports for the ERP and ECRM systems that augment the value of this great technology that is data warehousing in Tableau. Now, some people asked us, why did you pick Tableau among so many other analytics platforms in the Fortune 2000? Well, it was a long assessment, and back then, Tableau was not yet a corner leader. But the main reason, I think it boils down to the story behind Tableau. The Tableau founders, they were Stanford University professors and they hired psychologists and graphic designers to study how business people go through business data and make decisions. It's a journey, it's a process. And they studied this process and they came up with a procedure and they thought, well, we can create now a software that will make this procedure and help decision makers to go through this journey with little assistance. So Tableau is pretty much the only Fortune 2000 BI vendor that studied the process, the problem of decision making. And after the end of this process, then they hired the software engineers. Pretty much everyone else started from software engineers creating, oh, let's make something better, let's make something faster. They didn't look at the problem, they just tried to make something faster and flashier. And Tableau didn't. So it was a great story. Now, how does Tableau does it? What should I do? We humans are very visual animals. If we weren't, maybe we weren't being here as a species. But here we are. If we're in this situation, we don't have to think. We just jump the hell out in front of the snake. That's what the blood tries to do with the data. Of course, not with snakes. So let's talk about it. Rows and column reporting. Absolutely. Tableau in data cell. For the data warehouse, we heavily support rows and columns. But if I ask you how many nines Are there on this table. If you're like most of us, you have to go through the rows and eventually count. What Tableau does is as subtle but obvious change that will give you the insight. Like right now I can tell there's about 10 nines. So we shorten the time to get the insight so I have more time to decide and act on my decisions. What if I show you this? I see here product type, product markets, sales, profit. And if I ask you which market has the biggest sales, which products are not so profitable? Again, if you're like most of us, you have to go to the table and eventually you come with the answers. What Tableau does is something like this. Bigger bars, bigger sales. So I can tell Central has the biggest sales overall and profitability. Reddit's not so profitable so quickly I can tell which ones are not so profitable. So I'm shortening significantly the time it takes to get the insight. So again, I have more time to decide what to do and most importantly to act on my decisions. Now, this is a business. You want to be sure that your insights are beautiful and really insightful. Not so much about being fluffy and beautiful, but being insightful. You want to be sure your insights are accurate. What I'm talking about, let's say 3D charts, like this 3D pie chart. If I ask you which slice is bigger, blue or red? If you're like most of us, you can't tell the difference because they look very similar. Because 3D charts can be deceiving. Well, Tableau does not support natively 3D charts because they can be deceiving. Instead, Tableau provides beautiful charts that are very insightful and accurate. Like in this case, even if I remove the labels, I could tell that the red slice is bigger than the blue because actually in 2D is more accurate information. Now, if tableau is so great, tableau is so easy. Why exactly do I need data Self? That was what the CEO asked me after I went through this, this discussion. Well, I told the CEO absolutely you can get tableau and you can actually build the plumbing. The plumbing is finding all the tables that you need from all your systems. Eventually have to massage this data in a staging database or data warehouse. Absolutely, with the right talent, you can build the plumbing, you can build the reports and dashboards, and you can do it. But. But typically it's going to take you a long time, usually several months, if not years of several people working to build the plumbing between your data sources and tableau. And that's what we do out of the box, we give you a fairly code free data warehouse that already has mapping to many ERPs and CRMs in the market. Sage, Microsoft, Salesforce and whatnot. And we have more than 5,000 reports at a starting point. So why should you reinvent the wheel? We can just shortcut the time significantly and cut the cost to get the job done. So that's what we do. We make it simple, we make it better. We augment significantly the value of tableau. All right, before I jump into the next session, I'm going to open a second poll. What are your main reporting areas? So please check the options and don't forget to click the submit button. Check as many as you want and be sure to click the submit button. Ten more seconds. Five more seconds. All right, thank you. Let me share it. So the biggest are financials and sales. Thank you very much for your feedback. So let's jump into the product presentation. The product presentation I'm going to go through is actually the case of this distribution company after they acquired Data Self. What happened? And the CEO is going to these board meetings on a monthly basis to discuss what happened last month and what they're going to be doing for the next month. And in the past he was going with a stack of paper and you know every board member have the stack of paper with the report will be discussing things. Quite often someone would have a question about this and that and sometimes there is no report to answer the question. The CEO would have to make notes and I'll get back to you and decisions will be postponed or they would just have to wing it because they could not wait for the answer. So I'm going to show actually how the CEO built some of these reports before were done by someone else and how people are consuming reports with Data Self. So the first thing is actually showing last month sales details. So they want to see sales by customer, by product, invoice number, invoice date. So I'll show you how the CEO built that report. Then they are doing marketing campaigns and they want to see how website visitors are affecting their sales trends. So I'm going to show how the CEO build that report as well. Then regional sales in US and Canada and how large the deals are. That was going to be the last report. I'm going to show how he built and also I'm going to show some other reports that were used are being used by this company. So are you ready to see the product? I know the PowerPoint can be boring, but hopefully it was educational so I switched now to the data self analytics desktop. Most of the things I'm going to be showing how to do the desktop can also be done using web browsers and mobile devices. So it's the same idea. So the CEO came here after training, little three hours of training and decided that he want to build himself some of these reports to see how easy it was. And to do that, when you open the desktop tool, the first decision you have to make is what is the connector you're going to be working with. And here we have a few sample connectors. These connectors are the plumbing that we have done. Datasef has done from tableau all the way back to the data warehouse in the data sources. So you can have a lot of different kind of data connectors. The reports the CO is going to be building are out of the revenues or sales connector. Now the first report is sales by customer by product in last month. So what now I need to do is primarily learn how to drag and drop. So let me find my customers, which is right here. Customer name, drag and drop into my report. So these are all the customers I want to see sales for my measures and I just have to drag and drop into the report. Just drag and drop. There it is, sales. The whole company is used to buy customer. Well, I want to see sales last month, so let's bring date fields and just again drag and drop into my columns. Oops, sorry, I bought the wrong field. Invoice, date, drag and drop. Then I see sales by year in my sample database. I have four years, but it would show as many years as you have in your source system. Now I want to see sales by month. I can expand year and now it goes to the quarter level. I can expand quarter and go to the month level. I can expand weeks, I can expand today's hours, minutes, fiscal periods, whatever the time bucket that you want to analyze. We can build those buckets into the data warehouse and once they are built, as a business person, you just have to expand, drag and drop and do your different time analysis. Now in my simple database, my last month is in October. So actually I only want to see sales for last month. So let's filter this report and I'm going to take the invoice date, just drag and drop into my filter shelf and then I can select to filter by a different time bucket or choose relative date and then I'm going to choose month, previous month and that's it. There it is, sales last month. Now every time that I open this report will always show last month. And if I want to change, let's say I want to see the last three months being November, October, September or maybe the last four months. I just change here. I can change to different time buckets and the report will reflect right there very quickly, very easily. Just go back to the previous month which was the report that the CEO was building. Now I want to see sales by customer, by product, invoice number, invoice date and whatnot. Well you just have to know how to drag and drop. So product is here I think product drag and drop between customer and sales. There it is by customer by product. I see sales invoice number. You go to the invoice fields, find invoice number, drag and drop. There it is, invoice date, same thing, drag and drop and you get it. Very easy to build reports by just dragging and dropping. Many of our clients users have learned how to build reports from scratch by watching a presentation like this. If you know how to drag and drop, you can do it. Now there's a lot more things, a lot more sophisticated techniques, but a lot of the reports is just drag and drop. Okay, that was the first report. Second report on the build is showing sales trends. I want to compare sales and website visitors. Well before data self it was thinking about more than a day for the IT team and their marketing team to be working getting data from Google Analytics and ERP system, massage the data and blah blah blah and put in Excel or chart and whatnot. It was very time consuming job. Well, my team worked with their team to bring Google Analytics data to the data warehouse. We blended that Google Analytics data with sales and now in the revenues connector we also have website visitors. As the CEO I don't care how it was done, I know my team did it properly. I just need to know how to drag and drop. So the co came here, he double click sales and double click invoice date. So he have a chart showing sales by year. Well he want to see on a monthly level. So let's go to the month level. Now he's seeing sales trend over the years by month. Now he took website visitors and he just dragged and dropped into the report. These are website visitors, let's make a bar and this is sales. And I even want to put in a dual axis and there it is. Website visitors are my bars. Sales is my line. How about that? The CEO built this report from scratch and now every time they open it, it's always refreshed, completely automated. That procedure was taking more than a day to people to come up with a Report once a month, they have it automatically done. And the CEO built himself, he was very proud of it. The next report is sales by geography. You can put on a map any kind of information that has a geography component could be shipped to. In this case, going to be the customer address. So customer state, invoice, size and sales. And then I'm going to put this on a map. And there it is. Let's make the bubbles a little bigger and let's go this way. Bring it here. Easy. You know, again, the CEO was able to build this report that shows bigger bubbles, bigger sales, and they're sliced by the size of the deals. And it was a very insightful report. Now the CEO goes to the board meetings still with a stack of paper, because some board members, they don't have tablets. Some of them, they have tablets. The CEO goes with his iPad and he want to have these three reports on a dashboard. So he came here and he created now a dashboard and he said it's going to be a automatic size and he just picked the queries that he want to add to the dashboard. Just drag and drop. So the map, put the map under the report, the sheet with the trend analysis put at the bottom, and then take the revenues report and drag and drop on the right corner. Just drag and drop. Make this a little bigger. And that was it. Built from scratch in a few minutes. A report, a dashboard before was taking so many people to put it together. Now the beauty is when he goes to the board meetings, sometimes a board member that does not have a tablet or a notebook, and they say, hey, you know, Mr. CEO, I'm going to this trip and I'm going to visit our clients in California, Texas. How are we doing over there? In the past the CEO would have to make notes and I get back to you or having discussions later on. Now on his iPad, he can take using his finger, he can just select California and Texas and he gets the answer. He can print this report to a PDF and email to the board member or even print on the printer that they have on the board room and just get on with their business. So again, shrinking significantly the time to get the insights so they have more time for decisions in acting. And this is pretty all of these reports, they're very dynamic. You can just pick and choose and automatically they will change and change the whole report. Now what I just showed you is the desktop tool which is usually used by publisher users and decision makers who are going to be on desktop quite often. And they want to have the full power of a desktop application. But again, most of the things I did here on the desktop can also be done on web and mobile devices. Now let me show how typically people will be consuming reports. Most users will be consuming reports using a web portal, using web browsers or mobile devices, and even emails. So when they log into this portal, the tool will know who they are and which reports they have access to. So if I'm a salesperson, I will only see sales reports. If I'm a person from the purchasing department, I only see purchase reports. Or maybe I'm the person who has access to everything. Now when I open a specific report, let's say if I open this report here, then the system can control what data I can see. So let's say if I'm in California, I would only see customers in California. If I'm the rep for Florida, I only see customers in Florida. But if I'm the, let's say, VP of sales, the same report shows me the top customers across all territories. So a single report can serve many people in the user credentials who control what each person can view. All right, now let me go here and filter for financials. So here I just select. Let's look at this financial report here. There's doing some ratios of expenses, overhead by revenues by different location. In this company that I'm talking about, they have four different locations. This is not their data by the way, but it looks like their data. So the person who built this report can control the user experience of non sophisticated users. You know, we call the viewer users. So let's say if I come to the Atlanta box and click it, maybe I could go straight into the details of the Atlanta office and the details could be whatever that I select as the person building the report. Or I could say, you cannot change anything. You just can only view this report and that's it, you cannot change anything. Or when I click on this Atlanta box, it pops like this little window and gives me more options to drill down. Here I'm seeing two drill down options. Maybe I could have five options, five, ten, whatever. In this case only two. And when I click on one of them, like balance details. Now when I click, I go into a completely different report. In this case it's still a financial report, only focus on the appliance information. And I could do more analysis here. Now I drill from a financial to a financial report just for the sake of example. But when I drill down, I can drill down into any other data in my data warehouse. It could be sales, it could be purchasing it could be CRM, it could be Google Analytics. If you could relate to. The point is, once the data is in the data warehouse, the people building the reports and slicing and dicing the. You have the freedom to jump from one place to another because the data is all together in a single data repository anyhow. Now, if I'm a viewer user, a non sophisticated user for this reporting tool, maybe that's it. I cannot drill down further because the tool doesn't allow me to. But if I'm a power user, a more sophisticated user for reporting purposes, then I have the edit button. And if I click the edit button, let's say on my mobile device now, I can change the report. Let's say I'm looking at this report, it has GL segment one and two and I want to put segment three as well. Well, because I'm a power user, I can focus on this report. I can come here to my GL account and I pick any field in this case segment three and I just drag and drop. Maybe at the beginning, the middle or at the end of my report. Let's put at the end right there, I see segment three, maybe I'm going to put in the middle instead. Right there, segment three. The point is, with this kind of technology, you can empower your users, your decision makers, anytime, anywhere, using different devices to easily access their reports. The report will run in seconds. It doesn't matter how big your database is, how many databases you have is going to run in seconds, and if they need to change the report, slice and dice it, drill down, download or even build new reports from scratch, they will be able to. Because this tool has been optimized with all the bells and whistles data warehouse in Tableau to allow decision makers to do it. Alrighty, I'm not going to save. By the way, you can also control who can save reports. So if I'm a power user, you, the admin person can tell, okay, I can only save reports for myself or I can save them back and modify the official reports for everyone else. Those decisions security can also control. All right, okay, so. Oh, by the way, let me go back to the prior page now. The last thing is, okay, I have this report here, I'm accessing it. Many people like to go to the report platform, to the report portal to access the report. But some people, they like to receive the reports automatically in their inbox. There are many ways that can be done, or there are two main ways that can be done. One is as a user, I can decide which reports I Receive like in this case, if I receive this report on a scheduled basis, I click subscribe, I pick a schedule like Friday 6pm, I click subscribe. And from now on, every Friday 6pm I'll get an inbox, an email in my inbox with this report with the latest information I can view it. If I want to interact with my report, I can click on it. And from the email it will jump right back into this portal. And then if I have more filters or if I have power capabilities, I can keep on changing the report and do more analysis. But it becomes the data comes to me, I don't have to go to find the data. The other option besides the self service subscription is you, the admin people. You can actually push reports in a PDF or Excel format in different schedules. Let's say every day you can send a lot of reports to external reps showing their sales and every week you send to other group of people other reports and every month you send someone else. So you can also push reports, you can do pull, you can do push reports. You have both approaches. All right. I hope you found the demo exciting and informative. Now we're going to go back to the PowerPoint and move to the next section of the presentation. Pros and cons People always ask us awesome. But you know, tell me the good and the bad of it. The pros and cons of data warehousing. Let's start with the cons. Well, one of them is it requires skilled people. Data warehousing is more sophisticated, more complicated than regular reporting. Yes it is. The good news is with data self we pretty much eliminate programming. So building, maintaining a data warehouse you do not need to have programmers is much easier, much faster with our etl. So you still have to have skilled people, but they do not need to be necessarily programmers. Much easier. Second is most of the data in data warehouse is not real time. You can do real time. Yes, you can. But most of the data will not be real time will be refreshed on a scheduled basis and it requires additional investment. So there is a cost to have a data warehouse and you got to put the money to have those benefits. What are the pros? Well, one of the most important is the single version of the truth. Sometimes when you don't have a data warehouse, if you take two reports that are showing, I don't know, financials or sales and whatnot, sometimes, I mean, who guarantees that the rules, how you calculated your gross profit, your cost of sales, your inventory on hand was calculated the same way among both Reports. Sometimes different people build the reports and they use different premises. And when you're making decision in comparison, you compare some apples to pineapples. A data warehouse, you define in a single place how you calculate your metrics, how you calculate your gross profit, your sales, your inventory on hand. And all reports pull the data from those single definitions. That will guarantee different reports with the same metrics will be using the same rules. And then you'll be discussing using the single version. The truth. That's a very important benefit. Second is all of your data silos. And many of you said one of your main challenges is having your data silos. All of your data silos can be brought into the data warehouse. Now all the data need for reporting comes from a single place. There's no need to be having different people maintaining different things. Everything is together. You can blend the data, you can jump from one data to another because it's all together in a single data repository. And the third and final benefit is performance and ease of reporting. Most reports from data warehouse will run really quickly and the data is organized in a way that is easier for reporting and friendlier for decision makers. So performance and ease of reporting are the two final pros of data warehousing. What about Tableau cons? Some people think that because it's a product outside of Sage, it's a downside. So we say it's a con, it's not embedded. You can embed Tableau into Sage? Yes, absolutely. You can insert Tableau reports into it. But it's a standalone product per se. Some visualizations like, you know, 3D charts are not supported. So if you want, you'll have to export to Excel. It's very easy to export Excel, but you know, you do not get easily, let's say 3D charts in Tableau and it costs more money. So you have to put some more money to get the benefit of Tableau pros. The most important by far is ease of use. We've been using Tableau as the analytics platform for five years and so far there is no product out there that is close to ease of use. It's awesome to work with a product that is the most empowering for decision makers. It's really awesome. So ease of use is the most important one. It's very fast. It focus only on beautiful insights. And standalone I actually think is a pro because most, a lot of decision makers may not be a Sage user. So having a product that is outside of Sage, you don't have to buy a license for Sage to open Reports you can run anytime, anywhere. So I actually think standalone is a pro. Should you build yourself or should you buy from Data Self? If you build yourself, you're your analytics solution. What are the cons? Well, first is low and costly. You have to probably hire some people to build the plumbing, make the connectors, build the reports. Typically it takes several months and more than two people to build a comprehensive solution like ours, covering apar, GL sales and whatnot. So it takes a lot of effort, a lot of time. And if you do so, be sure to find and retain skilled talent. Because if you have to maintain the solution in the long run and you no longer have the same people, good luck, you have to hire again. The new people don't know what have been done. They have to build again from scratch. There's going to be a lot of cost in the long run, so be sure to keep the people. If you decide to build it yourself. What are the pros? Everything designed specifically for your needs from the beginning. Everything is done specifically for what you need and you have control of everything because it's your own decisions. What if you get a solution like Data Self out of the box with all of these data warehouse connectors and thousands and thousands of reports? What are the cons? Absolutely will be a higher initial license cost. You get a lot of value, but you got to pay for it. You always get what you paid for and you get already a platform like in Dataself use SQL Server, Data Warehouse and Tableau is one of the best. But you are being tied to this platform. So it is a con for some people in being not as much as control in that sense. What are the pros? Well, you get a lot of reports, you get a data warehouse, a lot of connectors, really, really fast. Usually in a few weeks you have a ton of things working, things that would take you several months to years to get if you build yourself. So speed is a major benefit of getting some things out of the box like Data Self. The solution is completely customizable, so everything can be customized the same way that you could do it yourself. So it's completely customizable. You have completely control the process. And we have been doing this for 11 years as a team, actually for 16 years if you look at our core team. But we have built best practices around data warehousing, around analytics. And what you learn from us is also how to do things in a better way that can support your growth in the long run. If you don't have the best practices and you hire people and they start from scratch building best practices. It takes time, it takes expertise, it takes effort to make the team work together. Now, in a nutshell, that means typically when you buy from a company like us, your total cost of ownership will be significantly lower, much lower. Because in a few weeks you can get so much more value and you know how much it's going to cost if you build yourself. Who knows how long it's going to take? Do you need to hire more people? In the long run, you're going to be changing people. There's a lot of uncertainty if you go through the building yourself. So overall the total cost of ownership will be usually higher if you do it yourself. All right, BI deployment approach, should you go cloud or on prem? We support both, but anyhow, with the public cloud, sometimes you cannot put your data in the public cloud. So legal is the first question. If you can, then the cons are sometimes you don't have much control in the platform because the cloud will be upgrading when they need it, when they want it. And sometimes you have to be retraining people in a schedule that you'd like not to. So control can be an issue. And sometimes you might have issues uploading your data from a speed standpoint as well as reliability. I've seen many clients that have cloud BI solutions out there and say, oh, sometimes we need the data, but it's because there's some Internet connection issues, it's not refreshed yet, we gotta wait. So cloud can have those issues of upload speed and reliability. The pros obviously the initial cost is usually pretty low, so sometimes it doesn't cost much at all to give it a shot. So it's easy to, you know, from a cost standpoint. And also you don't need to maintain service and whatnot. Everything is done in the cloud where the on premises or private cloud approach, so you own the solution, you have the infrastructure. Well, cons is typically is going to be a higher initial cost in higher cost for you to maintain the servers and whatnot. And the pros is well, you have more control everything. You decide when you want to upgrade, are you ready, what do you want to upgrade, what change you can do. So you control more the process. And typically there are no issues with the upload speed and reliability because the BI is closer to your data sources and there's no such a thing. Some people have security considerations saying that some people say cloud is better than on prem. If you want to discuss those topics, I can go into more detail. We have a very interesting perspective about which one is more secured. But I'll leave that for later in case you want to peel the onion to discuss security options for both. Overall, I tell people if your main data sources are on PREM or private cloud, I would say go with a on PREM or private cloud BI solution. If your main data sources are in public cloud, then it's completely fine to go public cloud with your bi. So to me, typically where your largest data sources are is what defines which way would be the best way to go. But again we can discuss in more detail in case you want to discuss this later. Alrighty. What's next? If you'd like to see Data Self in action, you can actually go to our website. There is a trial now button. Just fill out the form and download a trial version of Data Self. If you want to see Data Self with your own data, then you can send us your data and we will give you back a trial version of Data Self with your data. Typically people who do a test drive a Data Self they will buy it. So just do it if you're serious. But it's an awesome way to see how empowering and how easy to use the solution is by doing a test drive. Again, you can do the one on our website that has a sample database, but it's really informative. And by the way, we have a year end incentive. So if you have budgets to invest in BI and we are on the table, be sure to consider our year end incentive and can ask more details on a one on one basis and then I can give you the the goodies of how much you might save. Before I open a Q and A session, let me open the last poll. So what would you like to do next? Please select the options and click the submit button. Be sure to select all the options and click the submit button. 10 more seconds. Five more seconds. All right, thank you very much. Just quick sharing it Discuss pros and cons is the biggest option. Absolutely. At the end of the presentation I'll show you my contact information in case you don't have it. And one of the things I'm here as a professional more than being a dataself CEO is to educate you if Data Self is a good option and how the other options out there in the market stack up with us and whatnot. I don't want your money if you're not a good option for you. I'll be glad to refer you to my competitors if I feel I'm not a good a good fit. So feel free to contact me to ask Me question, I'll be as much unbiased as possible, at least to tell you what is fact and what is opinion and then you feel free to, you know, come up with your decisions. If you have questions, Please use the GoToWebinar chat panel and I'll be reading questions and addressing them. So we do have questions here. The first question I have here is from Marta, how long does it take to deploy Data Self? Marta, an awesome question and to answer this question, let me actually, oopsie, sorry. Let me go to my website to just give you some insights of what to get in a deployment. If you go to dataself.com and you go to Solutions and 5000 KPIs and here we have a list, sorry, a list of all the reports available out of the box for CRM as well as for erp. And let's say that you have a Sage ERP product, right? And you acquire dataself. Once you give us full access to the environment, we're going to be installing Data Self. You know, we have security and we just have to do our job. Typically in two days you will start having access to your data using dataself. So how long does it take to deploy? About two days. What do you get out of two days? Well, you get the out of the box solution which you're seeing here as listed. Typically what happens is, let's say the most popular scenario of our clients is they want to see, let's say financial or sales, let's say sales. The most part is sales. They want to have a better sales analysis. So after two days we will show your team the over 1,000, maybe 2,500 reports out of the box, showing sales trends, customer, product whatnot. Then your team will look at the data and the out of the box solution is plugged to the default tables in your ERP system. Your customer, your product, your invoice header, invoice detail, your GL tables. But quite often the way that you do business, you don't use the default settings of your ERP system. You have done some customizations. Our out of the box will not recognize the customizations until you tell us. So once you start seeing your data, you may realize, awesome, everything is good. Give me training and I'll be gone. Or you say, hey, can you actually add some additional fields here that are not out of the box? Or the way that you're calculating gross profit should include some kind of coupon that is in another table. So typically once you have the access to the out of the box Solution not typically. Let me rephrase it. About half our clients only need our out of the box solution. As is, they will take over, they'll be trained and they'll start to customize themselves. The other half of our clients will need some level of services, custom services, to adapt the out of the box to the specific ways of your ERP system. It's your M system and those customizations could be only a few hours, maybe a few days, maybe several weeks even of work, depending on the sophistication. Most of them are little, you know, few days and maybe a few hours, a few days. But the point is, once you get two days, you get your data, you start looking at it, and then you can start asking for more customizations on the back end of the system in case the out of the box doesn't fulfill all your needs. Marta, that was a great question. Thank you. One more question I'll be able to answer because we're running out of time. Question from Kelly how do you compare to sei Sage Enterprise Intelligence? Kelly, thank you for your question. So how do we compare with Sage Enterprise Intelligence? So first of all, Sage Enterprise Intelligence, my opinion is the best DI technology that Sage has adopted over the years. Personally, I've been working with sage for about 15 years and they have done a great job selecting SEI as the best. Looking from the outside, from the high level, it looks similar to ours, it's mobile, it's web based, so it has many similarities. However, let me go back here to my PowerPoint, Show this. Here I'm going to show my assessment and from what I've heard from other people, the SEI is not as easy to use from a back end standpoint as well as from a front end standpoint. On the back end my understanding is they use data warehousing, but they're using SQL native tools which usually require stored procedures, integration services. So it's a programming kind of job. So maintaining the back end you need to be more of a programmer. You have to have more of a programmer person to be involved. My understanding also they use Microsoft OLAP cubes which is also a very program intensive OLAP technology. So the back end is more complicated than ours. Our technology we rarely use cubes. We use a better tool than cubes, faster, easier. And on the data warehousing, our ETL eliminates programming, no stored procedures, no integration services. So it's easy on the back end. And in the front end we use Tableau, which again as I mentioned Gartner has rewarded Tableau as the gold standard for the last four years in a row is one of the easiest to use most empowering analytics platform out there. Where would SEI as a client tool sit here? I don't know. Gartner doesn't seem to be looking at sei. I don't know why, but what I can tell you is I've heard and when I see that tableau is easier to use faster and having Gartner giving this kind of reward as being the gold standard, I feel comfortable we have overall an easier to use platform in a faster so it's not only my opinion Gartner kind of confirms. But yeah, I don't know where SEI would fall into this bucket here folks. Unfortunately we're running out of time so I really want to thank you for your time. By the way, when I showed you in our website Solutions 5000, if you also click Dashboard Samples, you'll come to this page here that has some sample reports and dashboard that we have available out of the box. We can have an idea of what is included. Please feel free to do so. This session is being recorded in the next few hours. I'm going to be sending you a link to the recorded session. Feel free to forward it to other people. If you want to talk with me to discuss pros and cons and whatnot, you can see here my cell phone, my email and I'll be really glad to support your decision making process. And if we do business, awesome. If we don't, at least I'll help you make a better decision. Thank you very much for your time and interest. I hope you have a great Thursday and looking forward to be in touch soon. Thank you.