Analytics for Sage ERP webinar

Thank you very much for joining us. Today we're going to be talking about analytics for SEI graphy. And before I jump in the presentation per se, I just want to give a little history about the company. I founded this company, DataSelf back in 2005. So it's been about eight years. The core team at DataSelf BI has been working with business intelligence and analytics for the Sage market since the year 2000. So we have about 13 years of experience working with analytics for this market. But anyhow, when they founded this company, the main vision was mid sized companies that use Sage software, Sage ERP and CRM could really benefit from data analysis, easier to use when it comes to finding information about the information. And back then the technology was kind of not really designed for business people. So the beginning of my vision was, well, what I want to do is find in the market the best technology, the easiest to use so we can empower decision makers with the ability to find information and light enough information by themselves with little assistance from it. And at the same time I want to come up with a technology that will enable the IT team to be really productive. You know, they need to support decision makers, they need to support operations, but they need to be efficient. They need to be able to provide information in a timely fashion and efficiently. So the goal was something really easy to use for business people and at the same time something industry standard for it so they can maintain easily, quickly and for an affordable price. And that's how Data Self started. So what I'm going to show today and talk about today is analytics for Sage ERP. As I mentioned, we've been doing this for about 13 years. We have learned a lot from analytics and how people use it. And the goal of today's session is a little bit of education. So having said that, well, I haven't introduced myself yet, sorry about that. My name is Johnny Girardi and I'm Data cell founder and CEO. So just the agenda, we're going to spend about 15 minutes or so talking about why analytics and then I'm going to jump into the product and show how we do it. So first of all, Data Self analytics we have for several ERP, pretty much all Sage ERPs we covered out of the box. And the Sage X3 is coming up in the first quarter 2014. We also cover some ERPs from other competitors, but this is the webinar for Sage, so we're sticking with the Sage ERP packages. So typically why companies look for analytics, usually analytics is not financial reporting. Per se. It's not balance sheet profit losses, not the perspective it can be. Out of the gl. Absolutely. We do analytics out of the GL modules. Purchasing, payables, receivables, payroll and so forth. But typically most companies come looking for better analytics when they're looking for better sales analysis, better supply chain, and sometimes you see their manufacturers also for improving the manufacturing process. So those are the three most popular reasons why people pursue analytics from Sage ERP when they come to us. So let's talk a little bit more about them. Analytics for sales is the most popular need that people come to companies like us. One of the most basic things you want to do is just having a better understanding of their sales and profitability. They may want to analyze sales by customer, by salespeople, by product, by territory, product line shipped to in warehouse locations, merchandise by channel, look at cost of sales, quantity shift, sales and profitability. Analysis is one of the things that people look the most. And our solution is really comprehensive and does a great job, as I'm going to show in the product presentation shortly. So that's one of the most fundamental needs that people come to us. Other people come because they have a more sophisticated or elaborate ordering and invoicing process. And sometimes it's not very efficient and do not find where things can be improved. So having a better understanding of how the ordering, the invoicing, the shipping happens can be a challenge. And analytics provides many ways to look at all of the possibilities and help you find ways to improve the processes. Sales commission is a very hot topic. Some companies have very simple sales commission comes with the Sage products and they're happy. Some companies, they have a more elaborate sales commission process, more complicated calculations, combining different components, different criterias. And sometimes it takes a lot of hours at the end of the week or the month for someone to put together all the numbers to come up with the right commissions. With analytics solutions like ours, we usually can automate sometimes the whole process. It becomes automatic, real time, you know, every day you can have where people are when it comes to sales commission. So people can keep track of their goals, their quotas and so forth. So sales commission usually a hot topic for many companies. And analytics can make a big help improving the process, forecasting very popular need as well. Whoever is selling, they're usually trying to understand how they can better forecast incoming orders, looking at past sales, current trends. And analytics provide several functionality that can help people do more accurate forecasting of sales in any time period, by day, by week and so forth. Price and strategy Companies sometimes they have big contracts that they sign for long periods. Six months, 12 months, two years. Let's say if you're selling to big boxes like a Walmart Target, usually the contracts are big for long periods. So when you come up with a price strategy for those contracts, you better have the best information. So you're going to get into a win win situation for you and for your clients. So having a good understanding of the components that go with the price strategy can be challenging. And analytics can provide many insights help you come up with the right pricing. One of also the most popular needs that people come to us is data integration. For certain analysis I'm talking about for. For instance, the sales information can come from different places besides the erp. It can come from Excel files that people like salespeople are putting their thoughts and their forecast. It may come from point of sale systems. Information can come from clients like Big Box is giving a forecast of their incoming orders. And then people have to combine this external data with their own ERP sales data to make analysis. And this is something we do a lot, combining data from outside sources or sometimes you're moving one accounting package to another. Let's say from right now Sage Pro to Sage 300, 100x3 and you want to combine the history of your old ERP with the new erp. All of those things can be easily tackled with data self analytics and one of the reasons people come to us. So these are some of the most popular needs from a sales standpoint that we can provide value on the supply chain. Supply chain can have so many different possibilities. Inventory management is one of the most popular. People want to have a good understanding of what's on hand, what warehouses, quantity on hand, by product, by product line. So inventory management, inventory turnover, what items should be moved or what items have been sitting for too long with no sales so you can get them out of the way. Inventory management is usually popular way for analytics to provide value. Sometimes you may have elaborate inbound or outbound routing in logistics. Maybe people are bringing products from overseas, from Asia. It may take months to get here. So knowing exactly where things are, when you're going to get them, are you going to be able to supply your orders on a timely fashion? Can be a challenge. So analytics can help. Maybe on the outbound you have trucks out there delivering things. Maybe you want to factor into an analysis, weather forecast or you know, traffic issues, whatever. So inbound and outbound routing logistics can be also helped by analytics supply chain collaboration. You know, you may have your vendors or your shipping companies or your own trucks. And you want to incorporate information from them into. Hold on a second here, let me see. It looks like I'm. Oh, I'm sorry, I was on a pause mode. Sorry about that. So you haven't been able to see my slides anyway. So, supply chain collaboration. You may want to have information with your suppliers, with your trucks, with your shipping companies, and see where things are so you can better plan your shipping, your manufacturing processes, purchasing processes. You know, you may have elaborate purchasing processes that you have to have a better understanding of how to make it more efficient. Analytics can also help you with that forecasting. By the same token that you may want to forecast your sales, you may want to forecast your inbound items. Again, you know, you may have things coming from overseas that are going to take, you know, weeks or months. You have to maybe shuffle things around in your warehouses. So forecasting your quantity on hand can be challenging. And analytics can provide value data integration. By the same token, on the sales side, you may want to integrate information coming from external data sources such as Excel or maybe your clients on the supply chain. You may also want to incorporate information from your vendors, from your shipping companies, your own trucks, and have a better understanding of the supply chain. So these are some of the reasons people use analytics that we can help with. Alrighty, so those are the most popular reasons why people come to data sales. We also help again with purchasing, payables, receivables, GL analysis, payroll analysis. Pretty much any kind of data can be improved by data set analytics. Now why data self analytics? Well, going back to my vision, when I opened the company, my vision was to simplify analytics and amplify it. In what sense? Well, we want it to be simple. We want to empower business people to do the job themselves. We want it to be able to support decision makers quickly and efficiently. And as a starting point, when people acquire this lpi, we want them to have more than just a tool. We want them to have a complete solution. So we simplify and we amplify the whole analytics. These are the three software components we add to the puzzle. And this slide here is a very quick explanation why we shine. In a nutshell, this is the Gartner Magic Quadrant for BI and analytics platform. To make a long story short, the higher you are in this axis, the better you are executing your vision. These two are the top two vendors based on the latest Gartner Magic Quadrant Analysis tableau and Microsoft. Tableau is the king of the hill when it comes to data. Visualization techniques and Microsoft is the king of the hill when it comes to BI infrastructure. So where are we? What do we do? We simplify and we amplify. We took Tableau and SQL Server, we add our own secret sauce that simplifies these high end technologies and we amplify it, we eliminate programming from it so it's easier, faster, simpler and we add more than 2000 reported APIs to get you going quickly and easily. Easier, but better. So that's what we do from a technology standpoint. So what are the main values of business lpi? Well, first of all, easy, easy to use from any standpoint. If you are a decision maker, sometimes you're having meetings, maybe you're on the phone, maybe you're in a personal meeting with your people or with a client, with a vendor, maybe in a coffee shop, maybe at site. And you may need information to make more informed decisions. So what we provide is a framework that decision makers, anywhere, anytime they can get information. They can use a computer, they can use a mobile device such as a tablet or an iPhone and find information when they need it and make more informed decisions. So, so easy. Very easy. From an IT standpoint, easy as well. It enables them to support decision makers and provide them with information in a timely fashion without requiring extensive labor hours and expertise. So easy is one of the most important benefits. Second, as I mentioned is we amplify analytics. Over the years, 13 years my core team has been working with this. We have built a very comprehensive out of the box solution that comes with more than 2,000 reports, dashboards and KPIs out of the box. And when I go to the product presentation, I'm going to show some of them, but usually they're very insightful and they can help people focus their efforts in trains that are typically overlooked. So easy and comprehensive out of the box. And that's why we call our solution like a Ferrari in the sage market. Among the other analytics solutions, you know we call the other guys the Beamers, the Mercedes, the Porsches. Great solutions, great pricing. If you are a tight budget, if you're looking for something better, they are the way to go. We are really focused on user friendly, being fast and being really empowering business people in IT with the best of the breed technology out there. That's why we are like a Ferrari. So let's take this baby for a spin. Let's go for a test drive. I'm going to show three different things in our solution. First of all, I'm going to show secured access to data Self analytics how it works, then I'm going to show some of the out of the box reports and KPIs and then I'm going to do an ad hoc analysis. So let's do it. So this is how most people would access data Self analytics is through a web portal. They can access data self analytics using a web browser on a desktop or a notebook, or on a mobile device as well through apps like an iPad app or an Android app. So very convenient anywhere, anytime people have access to it, the information is highly secured. So only people who have the right URL address and user credentials can log in. So we use the latest and greatest secure technology to be sure your data is protected. This framework can be deployed on premises, behind your firewall or in the cloud. So we can do both deployments anyway. So once a business person connects or logs to their dashboard, then there's additional security layers that kick in. The first one is each user can only view their own dashboards. So if I'm a salesperson, for instance, when I log in I see the salespeople dashboard. If I'm the finance team, when I log in, I only see the finance dashboard. So that's the second layer of security. It's dashboards that are only relevant to the user credentials. The third level of security is user granularity. Meaning if I open a given dashboard, the system can be smart enough to only give me my own information. So let's say if I'm a salesperson from the rep for California and I open a generic dashboard, I would only see my own sales. While let's say Mary in Florida, she opens the same report, the same dashboard and she only sees her own sales, while the big boss opens the same dashboard and views the sales across all accounts because this person has full access to everything. So security works, having secure information, only your own dashboards, and it can be only your own individual information. Having said that and having explained how access works, let's see some of the out of the box dashboards we have available. So let me start with this one here. This dashboard shows is a sales dashboard. It shows top customers by sales on a year to date basis. We have bars that are represented by the sales amount. So bigger bars, bigger sales. The color of each bar is represented by this color schema, that is the gross profit. So just by looking at the color of each bar, I can tell how profitable each customer is. And again, if I'm the sales account manager for California, this could be only my own top customers. Mary in Florida would see her Own top customers while the big boss views the same dashboard and see the top customers across all accounts, all territories. Also here we have these black dots that are represented by the gross profit on this other axis. So very easy, very simple to view the information to make sense out of it and maybe realize some important trends. We have lots of top performer dashboards like this one. Let me show another sales dashboard that is really usually intriguing. This one here. This one is usually very important for companies who have recurring customers. Let's say if you're a distributor and manufacturer or a field service company, that you have customers that are always buying from you. Typically this report is showing the top growth in decline, in this case by customer looking from a sales standpoint. So top customer by sales change since last year. Today it could be quarter, today it could be month to date. This axis shows change since last year. So very positive means growing a lot, very negative meaning declining a lot. These are the top customers by sales growth. Most likely happy customers. Most likely salespeople are working closely with them. Everyone is happy. How about these customers that are declining the most in sales since last year's date? Why is that? Maybe there's a problem, maybe not. Maybe it's okay, maybe it's seasonal. But maybe some of these clients are not happy. Maybe competition is knocking the door. Maybe someone is not doing a good job and they're leaving your business. So knowing who these customers are and figuring out why it's going down, you may fix a problem in a timely fashion before it's too late. So usually looking at the top growth and decline from different perspectives, sales by different customer, product territory, maybe profitability, quantity shipped, quantity on hand, cost of goods sold, pricing changes, expenses changes. Usually looking at things or keeping track of the things that are changing the most is very important. In out of the box. We have lots of reports showing things like this perspective. So very valuable out of the box solution, easy to use. And as I mentioned, that's how we amplify analytics. Let me show another example. Looking from a similar perspective or interesting ways of looking at data. Sometimes it's very important to analyze things that are no longer happening. Let's say suppose you have recurring customers and then some of these customers are no longer buying at all. Or maybe they're buying much less than were buying before. Why is that? Is it okay or not? Well, usually knowing who they are is the first step towards realizing is there something you should do to try to reverse the trend. So this is an example. It shows me my sales by territory and on the left, I have my regular customers that were purchasing buy from us in the last 60 days, but not in the last 30 days. Maybe you can put here the last 90 days versus the last 60 days. You limit different buckets, doesn't matter. The point is we have this, what is called exception reporting that can help you find about trends that are no longer happening. Maybe looking at which items are no longer being sold, your city and inventory. Maybe look for expenses or from revenues, what's no longer happening and then find out trends that you should act upon. Anyway, so these are some of the out of the box reporting KPIs I want to show. We have lots of things, as I mentioned, more than 2,000. And here I have some samples. Inventory analysis, pricing strategy, purchasing analysis. We have a ton of that. Now let's go for the next part of the presentation. What I want to show interaction, how business people can actually be empowered by this technology in the next level. So I showed dashboards so far. Let me show how interactive these dashboards can be and how business people can get really slice and dice and analyze information extensively. So let me open this Johnny dashboard. By the way, this dashboard, what I'm going to show next. If I were to build this dashboard from scratch, I could do it in five minutes myself. Meaning business people with little training can build them from scratch very quickly with no support from it. So let's take a look at the dashboard here. This dashboard is showing geography analysis. Sales by state is also sales and gross profit by salesperson. So let's take at least a first look and understand what I'm looking at here. So I have a map showing for every state how much I'm selling. And I have bubbles. The size of the bubbles relates to sales amount. So the largest bubble is about $26 million. And I'm looking 2014 year. The bubbles are sliced in different colors which are represented by how big the deal size is. So you know, the blue color means the aggregation of all deal sizes that are considered large in my company. Large meaning above $10,000. And then on the left I have the salespeople and I have bars for sales amounts and bars for gross profit. And the color of the bars also are represented by the color. So I can easily tell this example that Jack Black is being very unprofitable. Maybe I have to talk with Jack and see what's going on. So right here, this dashboard, again, insightful, give me some interesting information. I could build from scratch in five minutes. But anyway, I got this dashboard on my iPad. I'M in a meeting with my. I suppose I'm the big boss and I'm meeting with the west coast team and I'm analyzing what's going on. Can I improve things? This dashboard can be very interactive. So for instance, I'm looking at 2014 data. I can come here and use this slider to change to 2013. I mean, I could have, you know, go back as many years as I wanted. If I have history for 10 years, I could go back for 10 years. I could easily change this to look at sales by quarter, by month, fiscal period, weeks, by moving windows like last 30 days, last 90 days, you name it. Anyway, I'm looking at the year right now. Now, in my example, I'm meeting with my west coast team using my iPad, for instance. And then I only want to analyze west coast information. So let's start analyzing this further. So as I mentioned, these bubbles, right now the biggest are $26 million. So I'm going to use my mouse. But if I was on my iPad, I could use my fingers to select the three states from the west coast. And when I do that, now I changed my dashboard, and this is showing salespeople that are selling to the west coast and how they're doing. So as you can tell, it changed because I selected on those three states. Now, if I want to see only the not so profitable salespeople, I could come here and click. Let's say Sam is not so profitable. You know, the color kind of reddish. So even though he's selling a lot, it's not very popular. So let me click on it. So what I did, now it changed the whole dashboard. And I can see that my legend now is from 26 million. Now is 2 million for each bubble. So Sam is selling about $2 million in California. And you can see that he's not selling large deals, and that could be an issue. Well, I can select more people. Suppose I select all the redis guys here. As I keep on clicking on it, automatically, the dashboard changes. So now the combination of all of these SalesPeople is about $4 million in sales. And I can make this very interactive. Let's say suppose I go back to Sam here and suppose I'm not on my iPad. Suppose I'm on a notebook. And actually I want to see sales details about Sam. I actually want to get what he's been selling. Put an Excel file to do some further analysis. How could I do it? Well, I could click on Sam and choose this button, which is View data. When I click view data I can actually go to the underlying data and see everything that Sam has sold in that particular year or quarter, whatever it is. So these are all the sales transactions. I see the items, the invoice number, the invoice date, the customer information, anything. I can even download this information and then I can have an open on Excel right off the bat, that information. So it only took me a few clicks to get information from my dashboard, but dump it into my, let's say computer and open it Excel, very easy. Business people can do that sometimes with no training or very little training. Now I can do a lot more. What I showed so far is how we call the average users would consume information. They open dashboards on their desktops, on their mobile devices, they can set the filters, they can click here and there to find out more information. Now some of the users may be more sophisticated and they may want full ad hoc capabilities. Let me show an example of full ad hoc capabilities. So suppose I'm in a meeting with my west coast team again and I'm a fairly sophisticated business person and I want to get this salespeople analysis here. You know, sales and gross profit and start seeing customer sales, product line sales, and you name it. I want to do it right now, on the fly. So I would have this edit button available because I'm a power user. I click on it and now let's say my iPad becomes a power user tool. This power user is very easy to use and it's very fast. The the engine behind the power user tool was actually designed by Stanford University professors. These Stanford University professors, they studied how business people look at data, business data, and how they can get insights from it. When you are analyzing data, it's usually a journey, it's a discovery process. You may know where you want to go, but until you view the information, you don't know exactly. That's why when a business person asks for another person, like a consultant, an IT person for a report, it takes usually several interactions until the report is ready. Why? It's a journey, it's a discovery. People ask, oh, can you show me xyz? So the other person goes, brings back great, but can you please filter this way, sort it that way, change the color, change the summaries, and then it takes back and forth until the report is ready. Now reality is several times people, business people have to make decisions on the fly. They're on a call in a meeting and they cannot afford to call someone else to ask for some new information. This is really designed for those people. So this tool has been designed to really empower decision makers to do it themselves. And that's what I'm going to show now. So let's take a look how this works. I want to go to the sales and gross profit by rep report that is part of my dashboard and I want to change it extensively. Let's say I want to see numbers instead of a chart. Maybe I'm a numbers person. Well, I can click the show me button and this show me button is one of the features of this smart engine. Based on the data that I'm looking at, looking at sales growth strategy and salespeople, it gives me what kind of data representation techniques can be used to inform me of what this information can be. So I can just pick and choose a different type of option until I find something that is insightful for me. In my example, when I see numbers, so there it is, I see sales by the penny. Now I want to see sales aggregated by customer, what product line they've been buying and by year I want to see that. Well here on the left I have the data panel. And the data panel is also very user friendly and very intuitive. So as a business person I come here and see, I want to see sales by salesperson by customer. Well I can come to the customer, expand my customer entry and then I see customers subcomponents. And as you can tell there's these pop up windows that can explain what these parameters are. So the account manager here is the rep currently assigned to the customer. So let's say if I was doing a salesperson analysis, this particular component would show me sales historical sales based on today's customer assignment. If I go to the salesperson at the bottom here, this is the rep recorded on the invoice header. So if I were doing sales analysis by salesperson looking sales two years ago, you would see the salespeople that were assigned two years ago. So anyway, these pop up windows tell decision makers information in real time so they can choose the right parameters when they're doing that analysis. Anyway, so back to my example. I want to see sales by customer, by rep, by customer. So I can take the customer name here and I just drag and drop into my roaster instance. If I'm using an iPad, I use my fingers to drag and drop. So there it is. By salesperson, by customer, sales and gross profit. Very easy. How about sales by salesperson by customer, by product line? Same thing, I go to my data panel, I go to the product find product line and I drag and drop to my roaster instance. And there it is, by salesperson, by customer, by product line, sales and gross profit. Maybe I'm going to reverse the order of things. Drag and drop. So let's take product line, drag right here. So I have now by salesperson, buy product line, by customer. Very drag and drop. Very easy to do. What about time? Same thing. I'm going to take document, date and in this case I'm going to drag to my columns, for instance. So buy, salesperson, buy customer, buy from the client. Sales and gross profit. Very easy, very intuitive. Business people with little training can do it. We have several CEOs, COOs, Presidents, VP of Sales, Salespeople, CFOs, Controllers, Accounting Managers, purchasing managers, people out there that before were relying on an IT or consultant to do their analysis reports. Today they're doing it by themselves. On average, more than 70% of the customer reporting needs of the average business user can be tackled by themselves without IT support. Very easy, very intuitive. All right, so this is my Ferrari. I hope you have enjoyed the ride. Let's go back to PowerPoint and wrap the presentation. So how about pricing? Well, before we talk about pricing, let's talk about return on investment. In our experience, once we give decision makers people who can move the needle, a tool like this where they can make more informed decisions on the fly, anytime, anywhere, what happens? More informed decisions usually drive better decisions. Better decisions by business people usually drive bigger business or better business or more profitable business or more win win business. What happens? You move the needle. They move the needle. So on average in our experience, when companies start to use their self analytics, they improve their bottom line by 1 to 5% easily. So if you are a company selling, let's say $10 million a year or more, 50 million, 100 million. How much 1 to 5% represents if you improve your bottom line, how much is that? That's the way that we look at the cost of analytics. It's how much more business you can get. And now look at the cost. Is it worth it or not? Typically, the return on investment in data setup analytics many times is install it. View the out of the box reports that I was showing before and right there. If you reverse of a trend, let's say of a recurring customer that you are losing, if nobody knew right there, you may pay for the investment in itself Analytics. Sometimes it's that quick hours on average, it takes weeks or months, but overall it's very quick. So how much is that a setup analytics? Well, it can vary significantly depending on what system you have. What's your erp? What's your CRM? How many users you need? Do you have a multi company? There are many components that factor into the price. Do you want to go and buy our solution? Do you want to subscribe? We have subscription so depending on your needs it may be a four or five figure investment. Regardless. Typically you'll get the return in weeks or months. Right now we have some year end incentives and because you participated in the webinar it's a little bigger. So Overall we're offering 3% off for the end year incentive. But it's you, because you took the time to learn from us, you place the order this year, you get an extra 2%. So we have 5% off licenses. If you are an existing customer or if you have competing products and you want to upgrade or go to Datastaff analytics, we have also upgrade credits. The point is contact us as soon as possible so we can talk and see if our solution is a good fit and if it is, you may be able to save some decent money. So contact us if you're interested. Alrighty. Thank you very much for sticking around and learning about Microsoft Analytics. Now let's open the Q and A session and for that what I'm going to ask you is because we have so many people in our webinar, please use the GoToMeeting panel. There is a chatting panel on the GoToMeeting and then you can make questions and I will address the questions as needed. So let's see here we have some questions. All right, so the first question is a quick comparison between Data Self analytics and Sage Intelligence. Very good question. So Sage Intelligence, we've been working with Sage for a long, long time and Sage now has the best analytics solution so far. They actually have two different options, the Sage Intelligence Reporting and the Sage Intelligence Enterprise. Both of them, they are great solutions, great pricing. We call them the Bimmers, the Mercedes, the Porsches. If you have a smaller budget, it's definitely the way to go. The way we compare with them is more like the Ferrari. And the reason is because we're actually taking Tableau in SQL Server and we're simplifying it and amplifying it. So we really using best of the grid, widely supported technology, making it simpler, making it better. So again if your budget is smaller, I would definitely recommend you to keep with, you know, take a close look at Sage Intelligence. If you're really looking to give your decision makers and your IT the best of the breed, something that can become really productive and cut time infrastructure Take a look at us. I believe we can help with that. Good question. More questions. Is it possible to edit and create metrics and measures on the fly? Very good question. So yes, when you are slicing your dashboards, depending on your user rights, you can actually create new metrics on the fly. So let's say suppose you want to create an average price sold per product and assume that this measure would not be available out of the box. It is, but you see it was not. In a few clicks with no programming required, a business person would be able to come up with that calculation on the fly and add it to the framework. That's a very popular way of doing it. Some other people, they actually download the data into an Excel and there they can also create their own metrics on the fly. So both ways that people use when they want to create metrics that are not available in the framework supported. Very good question. Other questions, let's see here. What about the price per user? Good question. The price per user also can vary dramatically. We have different types of user licenses, from the powerful full blown license up to a module that can distribute dashboards to an unlimited number of users. So it varies and again it depends if you're purchasing or if you're subscribing. Just to give some thoughts, if you're subscribing for the yearly subscription, the most powerful user is a few hundred dollars per user, while the list can be. So the price depends on kind of user, kind of pricing model. You go. All right, there's one more question here. Good question. Can this application import data from other data sources? Absolutely. This framework here, let me see if I can put quickly the architecture, This is the architecture of the solution. We can port data from any data source as long as it's a tabular format. We can import from Access, From Excel, from SQL Server, FoxPro, Oracle DB2, you name it. We can bring data into what we call the ultralight data warehouse. Combine that data with your ERP and CRM, push it to the analytics platform which can be again on premises or in the cloud, and then at the end of the day, consumers will see information through desktop, web and mobile devices. All right, looks like those were the questions. So let's wrap it up people, I really appreciate for your time and interest learning about data self analytics. You can find here my complete information, my cell phone, my email, my Twitter handle. If you want to learn more about us, give me a call, shoot me an email. We're going to be sending you later today, some emails that we'll have links to the recording of the session, so you may forward that to people to watch it later on. Also, we have like a quick survey, like a 30 second survey. We would really appreciate if you answer that. And we're here to help. If you want to learn more about us, if you want to learn more about some other companies doing analytics and data intelligence, business intelligence, you want to get our opinion, we're here to educate you. We hope that you make the best decision. We're here to support you and we're here to live a happy life. Thank you very much, people. Have a wonderful Thursday and looking forward to connect with you in the future. Again, thank you.