The new DataSelf Analytics 9 - Smart Meets Fast!

So who needs business intelligence? Who needs analytics? Well, business people are the people who understand the threats and opportunities of the business and quite often they are in meetings, they are visiting clients, vendors and they have new questions about their business threats and opportunities and quite often they don't have answers, they don't have reports or that was ready for those questions. And then they have to make a decision. Sometimes they have time to wait, make the decision, sometimes they don't have time and have to just make a decision with whatever information that they have. Typically in the mid market people need an expert in reporting dashboarding, so business people have to rely on those experts and quite often they cannot make decisions in a timely fashion. So people who really need business intelligence are people who are managing people managing processes, selling, buying, building things. And quite often they don't have information anytime, anywhere. Thanks for joining us. My name is Johnny Girardi. I'm the CEO and founder of dataself and today I'm very excited to talk about the new release Data self analytics version 9, which is powered by Tableau version 9. And we're going to be covering a lot of interesting things here today. So let's get forward showing the agenda. I'll spend a few minutes in a PowerPoint showing some concepts. I'll spend most of the time showing the product and I'm going to build a little story around the product and how it can solve those challenges and then we're going to open a Q and A at the end. So first of all, what is Data Self Analytics? What is Tableau? What is this all this stuff that we've been talking about? I know we have many people here, we're existing customers, we have some new prospects, resellers in our audience here. So I want to give you content for all of you, but I'm going to be focusing most on the business benefits. So first of all, this slide here is about Gartner. BI Magic Quadrant. Gartner is one of the most reputable companies doing technology assessment for Fortune 2000 companies. And every year they release an assessment of how BI and analytics are doing for Fortune 2000 companies. This report came a couple of months ago, so it's fairly recent. Make a long story short, Tableau right now is considered the leading company when it comes to reporting analytics, dashboarding and self service PI. They're like the gold standard when it comes to ease of use empowerment of decision makers. Microsoft is one of the leaders when it comes to BI infrastructure and tools overall. So what about these upper market vendors? What about Data Self. Well, what Data Self is, is actually is nothing but using the best BI tools that Fortune 2000 companies can afford. So we have Tableau, which is the leader for three years in a row in ease of use and self service. Bi. We have SQL Server as the foundation for bi. But then we add our own secret sauce that makes those high end technologies simple to install, simple to maintain. And we have added more than 5,000, yes, 5,000 reports, dashboards and APIs out of the box. So not only you're getting what's the best out there from a technology standpoint, but there are a ton of reports and dashboards that fit the needs of most organizations or at least is a great foundation as a starting point. So this technology we provide is fast to deploy. Usually it takes hours or maybe a few days depending on your needs. We've been working with enterprise grade BI and mid market, ERP, CRM and data sources for over 15 years. So we know your kind of challenges and we know how to connect with this great technology. And overall this technology costs a fraction of the cost that if you try to build a solution from scratch for yourself. So that's what we provide. You know, Data Self is nothing but using the gold standard of technology for BI analytics for the open market. We make it easy, we make it fast, made it expensive for mid sized companies. So let's take a look at it. All right, version nine, I'm going to be showing a lot of things, but in order to keep it something you can follow, going to follow like a story. So I'm the VP of operations of this business that I'm going to be showing and we have weekly meetings with management where we discuss all the topics and issues that we have. My management team, including myself, we're very data driven. We like to know the facts to make decisions. Yes, we use our opinions, we use our gut feeling, but we love to know the facts so we can make better information, more informed decisions. These areas that I'm listing here are typical topics that we cover in our weekly meetings. We want to see what happened in the last weeks as far as sales. Sometimes we dive into customer sales, product sales, what we sold to these customers, what the invoice was, how much it was, how many we shipped, average price, and we get a lot of things. So I want to build something to address a review of the weekly of the last week sales. Also we have our marketing that was doing a lot of website campaigns and we're trying to keep track of how our marketing efforts is influencing sales. So I Want to build some kind of dashboard solution that shows website visitors versus sales and see if they are related somehow. Hopefully. So also we sell all over US and Canada and typically we ship small, medium large packages of sales of invoices. And I want to see how it is distributed by region, by state. Also, big topic of conversation our meetings is clients who are declining the most in sales. Either big sales decline or no longer buying. We need to know who they are, what's going on. So I also want to see that kind of information. These first four areas of information is something that we do every week. And currently we have our IT team, we have two people in our IT team that poor guys, they are doing all the it, keeping the network running, the computers running. And we, because we're data driven, we ask them reports left and right and boy, you know, they struggle. I mean they have a lot of things to do. Quite often we ask reports and dashboards and it takes hours, sometimes days and weeks for them to put them together. It's very complicated. We understand that and that's why we acquired Data Self. You know, we heard that with Data Self we management will be able to be empowered and be able to do these things by ourselves so we don't have to be bugging it all the time with new reporting requests. And actually we just acquired dataself. I just went through training and hopefully today I'll be able to tackle many of these needs by myself and offload it from some of these needs. Reality is I asked IT to tackle some of these reports, but also I'm going to be building some of them myself so I can show you how it works. So anyway, these first four topics, some of them I'm going to build myself because I've been trained and I kind of know how to use the tools. Then we have some new areas of focus. Well, we've been growing our business a lot for the past few years and we're just pushing sales, sales, sales and we get a great, great progress. But now, you know, the board told us, well, we need to look at profitability and we need to be sure we're addressing profitability needs. And we have no clue from an operation standpoint, which is my area, I'm the peer of operations. We have no clue right now what's going on with profitability. So I want to see if I can start digging into profitability so when I go to my weekly meeting I can start talking about it intelligently, showing facts and coming up with what should we do in order to address those profitability issues if we have any and become a more profitable enterprise. So I'll do some ad hoc analysis looking from a gross profit standpoint. So finally once we put all of these things together, I want to show how to share information, how to collaborate with other people and then I'm going to make some remarks and now it's going to be put back by Johnny, CEO of Data Self of Solution from a performance standpoint and administration standpoint and how version 9 makes it better. So we're going to see a lot of things but hopefully the story is simple and you'll see that this kind of story is common for many mid sized organizations. They have challenges, they have opportunities and business people should be able to tackle them, put them together, shorten the time it takes to put things together and increase the time it takes to analyze the data and actually proactively acting on them to increase your efficiency. Are you ready? I'm definitely. So let's go for it. So let's start with this week's sales details. So one of the areas is weekly meetings. We need to see sales by customer, product sales invoice, number things of that nature. So a lot of my analysis will be centered around sales. But we cover, you know, the technology covers sales, purchasing, inventory payables, receivables, financials, pretty much whatever you have. We have a lot of out of the box more than 5,000 reports and KPIs for different areas. But this can cover any data source, CRM, Excel and other data sources. In this example I'm going to be working mostly out of my sales. We call the sales connector right now the sales connector. It with Data Self installed for my business and is already connected to my ERP system and also to my Google Analytics data. When I see sales and website visitors so it's all already connected. It is so happy that now they have this great technology that they can just work their expertise on the back end which is really it and hopefully now reporting data analysis we the business people can take care of. So anyway IT and data self install this and we have here my sales connector where I can see my dimensions which are things like customer products, invoices, salespeople ship to, so forth and my main measures or key performance indicators all available for me as a business person. Now overall this tool helps decision makers stay in the flow as we call or SW calls stay in the flow means you don't need to get out of it and call people to help you. You drag and drop, you right click, point and click and the Tool should help you analyze your data without being complicated. It must be easy and intuitive. So let's be in the float and build this information. So weekly sales. So let's start building, dragging, dropping. I want to see sales. So I'm dragging my sales to my report. That's the total sales of the whole company. And I want to see my customer. So I expand my customer list. And this is a sample of customer parameters. In a real production environment we have a lot more but for presentations that we only have a smaller set of customer parameters. So let me drag customer to my report. There it is. I have all customer total sales. Well, typically I want to see information on a time basis by year, by quarter, by fiscal period, by week, you name it. So let me drag invoice date to my columns. Right there I see customer sales by year. I could expand from year to quarter, I could expand quarter to months and so forth. So very straightforward. I could just expand. But I want to see only weekly sales, my last week's sales. So let's actually let's filter this report to only show last week's sales. Filtering is very easy and again stay in the flow. I want to filter so I'm going to take invoice date and drag into my filter shelf. When I do that I have options to filter my data by different buckets. I love the relative data approach because I have all the buckets and I want to see weeks and now I choose this week. So from now on I no longer need to worry what week I am. It's always showing this week. So let me click OK here and let me put my filter on the right. So it's showing this week and I can quickly show and change my filter if I want to here. But then I want to show what week number I'm looking at because I want to be sure I'm looking at the right information. Well here on the date if I drop this pill, I have all the possible date format that I can show information by. And if I want to see week, I just choose week number. There we go. I have week 17 which is the current week. Awesome. So right there I have customer sales by week. Well, you know we want to see product, sales, quantity shipped, you name it. Stay in the flow. I want to see product, I just drag product to my report. So there is by customer, I have sales by product. I also want to see actually quantity shipped. So let me drag quantity shipped to my report. So right now I have quantity sold and sales amount. Very good. Now I also know in Our meetings, we want to know the average price sold and we just installed it itself. And when I look at my list of metrics here, I don't have an average price sold. Is that a problem? Do I got to call my poor IT and ask them, can you please build a new metric out of this? Do I need to export Excel? Yes, I could, but do I need to stay in the flow? You can actually do that right here. So I want to create a new metric which is the division of sales by quantity sold, which will give me the average price sold. So what I do, I just double click and I make a calculation when I see the sum of sales divided by the sum of quantity sold. So I just build this new metric and the new metric is right here, which is also called in this way here. And actually let me add this average price amount to my list of KPIs and it's going to ask me what the name I want to have is. The average price sold. So I just created a new metric called average price sold and it shows a number. I want to show it as dollar amount because it's price. So let's change the average price sold to show as a currency approach. There you go. Now I have average price sold as a currency. How awesome is that? I'm in the flow, I'm in the zone. If I didn't have the technology, most likely I have to call it and ask them, hey, can you please build this average sold price and just wait. And it could take days because I know they're busy. Because I'm using this very easy to use tool. I was able in a few clicks to just double click write an expression and I built a new KPI right here, right now. That was awesome. Okay, well sometimes in our meetings we want to know invoice, date, invoice number. We just stay in the flow and we just keep on dragging and dropping. I want to put invoice number. I put it over here. There it is. I want to see invoice, date. I drag and drop, just whatever I want. And there we go, invoice, date, invoice. Maybe we want to put product at the end of the expression here. There you go. As you can see, it's easy, it's drag and drop. You don't need to be a highly trained person to do these things. Actually, I have seen many of our users, data self users that have learned how to build reports like this just by looking at presentation like this. It's very simple. Of course there's a lot of Options. So it takes time to learn all the tricks, but the basics are drag and drop, filter, point and click. Very simple. All righty. So that was my first part of my challenge was this week's sales details. And I'm so glad I was able to build the average price sold without calling for it. This is really empowering me, which I'm excited. I knew and I heard about it itself being able to do that, and I'm happy to have done. Let me call this sheet weekly sales. All right, first down, first done. Next. Well, I want to see if my website visitors and my sales are somehow related this dashboard, in the past for it, they could only give us once a month because it was so much work for them to combine good analytics data with sales and so forth. Well, let's give it a spin because they already combined both information on the server. So I'm going to build a new sheet now, and I want to see sales. So let's start with sales first, which I'm more familiar with. I want to see sales by month. So let me put date in my columns and choose month as the approach. So right there, by month, I have sales growing over the years. All right, now I also want to see website visitors from Google Analytics, and I already have here as part of my sales connector. Let me just drag this to my rows. So these are website visitors, and let me put bars to tell them apart. So website visitors are bars and sales is aligned. Now I want to see if they are related to each other. And because they are a little bit far from each other right now, it's not so intuitive. Well, let me see if I can put on a dual axis. And oh, look at that. Website visitors are bars. Let me make the bars a little smaller, hopefully. So website. These are bars and my sales is aligned. And now this is very insightful. Hopefully I can see how my website visitors are maybe affecting my sales. And I think this is a great starting point for my weekly meetings to see how these two metrics are going side by side. So awesome. This was a simple one. Took me like, I don't know, a minute. Let make here call this marketing. This is sales and website visitors. All right, that was easy. That was very impressive trend analysis. The next one that I want to look at is regional sales by deal size. Well, let's make a new sheet for that and regional sales. I want to see sales by state, how big my invoices are by state, and put everything on a map. So I'm going to choose customer state for my bill to address. It could be shipped to information. Anything that has an address we can plot on a map. Then I want to see invoice sizes and then sales amount. And I want to put everything on a map. So I want to click to see the mapping capabilities. And right there I have a beautiful map. Let's make this a little bigger bubbles. So bigger bubbles, bigger sales. Now because I have sales in us, in Canada by default, the tool already put me the whole map of both countries and I can see my trends. Overall, I like to focus on US which as the VP of operation right now is my main focus. So I'm going to click here and search for United States continental. And when I do that, I'm focusing only on the continental area of usa. Maybe you know, if I was looking, let's say at the city level, you know, let me drill to the city level. And then if I was, I want to see, let's say sales in a specific state, let's say Florida. Florida. Now the tool goes and zooms right into Florida. And let's say if I was interested in information in that state, I could see how things were going. Very easy, very intuitive, searching for different areas. You can enter a state, a country, a county, any kind of regional information and the tool will zoom right into it. All right, beautiful. Stay in the flow. Okay, so actually I want to see the state level. So let me drill down to the state level. Awesome. I mean, that was it. I can see bigger bubbles, bigger sales, and then the bubble slides by. The aggregation of large invoices, medium and small. That was simple, man. It struggles a lot with this report. And again, it took me a few minutes to build it. So sales by region. Now these two last the sales and website visitors. Sales by region is something that my marketing team is always looking at. So actually let me put them together on a dashboard and call a marketing dashboard. So now I'm going to create a dashboard. I'm going to make it automatic and I want to see sales by region. So I just drag and drop. There is my sales by region in sales and website. And then I'm going to drag at the bottom of my report. There it is. That was it. This is going to be my marketing dashboard. Awesome. And by the way, I want to make this sales by region a filter. So I'm going to choose S to use as a filter. Meaning if I come here, let's say, and I choose an area, when I select that, it changes the bottom. Or maybe if I only select a few states, let's say I only want to select certain states for my analysis because whatever the reason is, when I select them it changes and then the report at the bottom only shows for whatever I selected. And I know that marketing does that a lot. They're looking at state and customer, they go crazy. And I think the marketing manager will love this dashboard as a starting point for our weekly meetings. And I'm sure she's going to be thrilled to learn how she can do it herself so she doesn't need to call it all the time for asking how she can analyze her website and social media and all the stuff that she's really good at. Awesome. Okay, so we have covered already these three part of our analysis and as you could tell, I stayed in the flow. In the flow. I was able to build things, slice and dice and go left and right and I didn't need to call it. Heck, I even built a new metric, the average price sales without it. I'm really excited. Now the next topic is sales decline. Fortunately, Data Self provides more than 5,000 reports, dashboards and KPIs and many of the sales decline needs that we have are already covered by the out of the box. But I want to see if they are a good starting point for my weekly meetings. So now I'm going to actually go to my web portal. The way that most users consume information is through a web portal they can consume using. I usually have my iPad. I'm on the road all the time. I'm visiting all the people, all my people visiting clients. So I use my iPad a lot so I can access my dashboards on my iPad and I can easily slice and dice them and change on the fly. Now let me see if I already have no sales cannot report. So I'm going to click no sales and yep, we have out of the box no sales. And this report here shows customers with no sales in four different time buckets. No sales the last 30 days, no sales in the last 60 days, no sales the last year, the last, maybe my business, I only want one or two. But I'm glad that as a starting point I have this dashboard. So I don't need to build it from scratch. I'm just going to show it as part of my presentation at the weeklies meeting. So that's one part of the sales decline showing customers who are no longer buying. What about customers who are still buying but are declining a lot? Well, in the same dashboard here I have this top customers by sales change since last year to date. How about that? The bigger the bar here the bigger the sales change. These customers are growing the most in sales since last year. This is not a problem. I'm sure they're pretty happy. Salespeople are working closely with them now. What about these customers who are declining the most in sales since last year today are being taken care of. Is there something wrong? Well, knowing who they are is the first step. And I'm so glad that I don't have to build this dashboard. It's already available out of the box, so, boy, that was even better. This whole sales decline, it took me one minute to just look, find they are there. It's just part of my story tomorrow. Awesome. So, such a great news. It took me about 20 minutes explaining things here to just cover these four main reporting areas. I'm on the flow here. I'm very happy. Now comes the uncharted waters. The new focus area, gross profit. I have no clue from a detailed standpoint or from a fact standpoint what's going on from a gross profit standpoint. So now I'm going to create a new set of reports, start to slice and dice dashboards and see if I find out some interesting gross profit issues or opportunities that I want to share with my team tomorrow to begin the conversation. So let's go for it. Let's create a new sheet here. And first let me start with looking at sales. Just get my whole sales. Now, customer group is something we do a lot in our analysis. So let me just drop my customer groups here. So these are my customer groups and also territories. So let me just put customer groups and territories as a starting point. And right now it's a little hard to read this report. Let me actually put it. Let me pivot it and see if it's easier. Oh, I like it. So customer groups and territories and how we're doing. All right. Well, actually, when I see gross profit, is gross profit different among my customer groups and among my territories, I don't know. Well, let's dump gross profit into my report. Just drag and drop and see what happens. Oh, that's something interesting. I have here the color being represented by gross profit percentage and very green is very profitable. And not so green is almost not profitable at all. Now what I can tell is clearly my sh customer group has very low profitability while all the other customer groups are fairly profitable. And from a region standpoint, let me just reverse here. From a region standpoint, doesn't matter. Actually, the issue is customer group sh particularly. So let me remove my territory because it does not matter for my gross profit it does not. I'm going to remove out of my query. I'm just looking profitability by customer group and clearly SH is low in profitability. Let's dig into it and see what's going on. So I'm going to click, right click and choose keep only sh. I don't care about the other ones. I only want to see sh. By the way, if I put the mouse over I see the little pop up window showing this 9% profitability for this 50% here, 57% here, 54%. So by far sh is really low. And what's going on? Let me right click and keep only this one. So right now 9.11% for sh. Maybe some products are not doing so well. So let's drag products into my query. I don't know. Let's check it out. I'm going to drag product and then we have all products here. Let's sort descending. Whoa, look at this. So these are my large products and by far the very top is not so profitable. Now I don't care about those that are profitable. I hate to know that we have so many reds and reds meaning not profitable is below zero. How can we be losing product money with these customers in these products? Well let's keep on digging further. I just want to see the non profitable items. I think my management team will be crazy about how many non profitable items I'm going to take gross profit and drag into my filters now. So I only want to see non profitable and then I have this very intuitive wizard. I can see a range of values. In this case I want to see at most zero meaning breaking even. But I want to see everything else that are not. They are not profitable. Let's click. Ok and there you go. Now I only have unprofitable items and look at this. Some of my top are in the millions of dollars. It's crazy. It's crazy. I'm so glad we're finally having the time to analyze profitability and I'm so glad I have data set because I am doing it by myself and I'm glad that it doesn't have to be bugged by this. Now let me add here to this report my customer group as a filter. I'm just curious if we have all products, let me remove customer group from here. If I have all products, these are my looking at all customer groups, all products in only the non profitable ones. If I remove SH from the list, let's see what happens. SH is the not so profitable group. If I remove. Wow. I Only have a few items that are not so profitable and they are like 40,000. If I add sh, I go to the millions. Boy, this is so insightful. So I really want to focus on just my sh is the area that I need to focus and get this fixed now in preparation for my weeklist meeting. This is such a critical problem that I want to take my top product. I'm going to right click and choose View data. I want to see the underlying records of all of these apples specifically for SH customer group, why they're not so profitable, why we're losing money. And These are about 9,000 records worth of losses with invoice number, customer name, invoice date, all the details. I could export this information to an Excel or something and email to my project manager and say hey Mr. Peter, I just figured out our profitability for these items are worst. Can you please take a look at for this customer group and see what's going on? So we start discussing our weekly meeting. There will be a collaboration way. And so we got to the meeting. You know, we have more answers than right now. But boy, this is such a critical insight. So let me put here GP gross profit by gross profit, Losses by product. Well, I'm having insights into my profitability and it doesn't look good for that particular slice. Now is this changing over time? That's usually a pretty important question. I don't know. Let's try to figure it out. Let's do a trend analysis, seeing things over time. So let me add first of all sales and I want to add invoice, date. When I do that, when I just double click the tool knows that if I put a line it shows me the trend. And as I can tell, I've been growing a lot year over year since for the past few years. Let me expand this to the month level. So I have for every year I have a different pane showing how the sales are. So there it is. I'm looking sales, monthly sales by year. And before I add profitability, I'm enjoying this. Let me see how sales is growing on a year to date basis. Right now this is monthly sales. I want to see sales growing throughout each year. How can I do that? Well, if I didn't have data, sales call it and weight. Here we have, I go to the sum of sales and I choose quick table calculation. Quick table calculations are very popular because they address common type of aggregations. Like I want to see year to date, I want to see growth over time. I want to see growth since last period. Averages and things like that. So I don't need to learn how to build those things. I don't need to call it. I just come here and I choose a different quick table calculation. For instance, if I choose year to date total, what I'm doing is I'm adding sales and I'm accumulating sales throughout the year. So there it is. Look at that. Very interesting. Now how is this going across the years? Am I always growing or sometimes I'm declining? Well, let me put years as part of my row, see what happens. I couldn't get much out of this, maybe year on my colors instead. Wow, that looks interesting. So now for every year I have a line and then I see how they're, you know, how I'm doing on a monthly basis. And I can see that this year I started below last year 2014, but I test in about February and I'm taking off. Yes. So excited. Very interesting. And it just takes a few clicks to drag and drop. And I see year to date growth. Maybe I want to see year over year growth again. Quick table calculations are an awesome way to do that. If I choose year over year growth, what this is showing now is in a percentage basis how much every month grew since the prior year. And sometimes it was a decline. And that could be important for my data analysis, but not today. Boy, I have to look at the gross profit. So let's go back to my gross profit analysis. But it's so much fun. This so easy. It's just stay in the flow and you find new trends that you never thought about before. Okay, gross profit backlog, gross profit. Let's drag gross profit to my report. Just drag and drop. And now I have my lines and they have a color schema here showing things over time. Now I'm just thinking that actually my low profitability specifically is with SH customer group. Well, let's add SH customer group to my report as a filter. And I only want to see sh. There it is. Now I only have sh and I'm seeing some trends now. That's what I want to see, trends. So red is not so profitable. And look at this. In November last year I have negative profitability. That's not good. And look at this. In the prior year I had negative profitability about the same time. In the prior year it was pretty low. Maybe it's a problem, maybe it's a seasonal thing. Around the end of the year, those products for those customers may be unprofitable. And maybe I have to change my vendor or something. But Boy, this was very insightful. Now sometimes changing the way that the query or the chart shows can be more insightful. I'm using the automatic approach, but I can control it. I can come here, maybe choose bars. Now in this particular example, bars will be even more informative because I can see clearly unprofitable about unprofitable low profitability. So sometimes just changing here to different approaches can be more informative to what you're looking at. Let me go back to the bar approach. So back to my problem. I need to see trend analysis and profitability and boy, I can see that there is a trend, a seasonality to my low profitability for my sh customer groups in those time periods. Very insightful. Now some of the things that DataSoft analytics version 9 also provides is this analytics tab that was not available in prior versions. And I can add, let's say average lines. So right here I see the average per year and it's kind of going up every year, which is good. Maybe I want to see how I'm doing the last four months versus the average. I just select them and now the last four months are even higher. Awesome. Well, also we have forecasting. Let me drag. Actually let me change this to lines which I like better for forecasting and drag my forecasting. And now the tool projects for the next until the end of 2016 what the likely sales is in the band showing the precision of my forecast. Awesome. So I like this. I'm going to rename and say GP Trends. All right, great. So now I want to actually share this information with my folks and I can build a story specific about the GP issues. Let me put here automatic. So I want to show my losses by product and I'll say loss by product. This is part of my story. I also want to say here, change customer group to C SH So I'm just using collaboration ways so when people open this story, they'll know what to do. And then I also want to put my trend here. And this is GP Trends. I'm going to call this my GP trends. Oops. GP Trend and losses. Awesome. So I just built all of this solution, all of these views. I'm going to publish the server, the web server. I only want to publish the trends in the marketing dashboard in my weekly sales because I'm going to be using those pieces in my weekly sales. So I publish them, publish them. And then now I go to my web portal, I refresh my web portal and now I'm going to click Oopsie. Views. And what did I call it, I think it's GP will do it. There we go. Now we have this GP trends that when I go to my board meeting I have loss by product. And then here I have this note to tell people change customer group to see what happens. And everything that I do here is just like I was doing before as I was building. So very easy for now for my board meeting to get these people to get to this story and change if I go to the trends and I see the same kind of information. So what's quick was easy and now I'm prepared. I'm prepared for my meeting and I think it will be a big success because we're going to have a lot more conversations and likely during the meeting if they ask new questions, I may be able to answer on the fly. All righty, so let me go back to my PowerPoint and resume my presentation and talk about performance. So just closing the product presentation per se. As you could tell being a VP of Operations, I was able to build a lot of things from scratch, share information with people. People could access those dashboards using web mobile devices they could receive by email or we could even export them to PDFs and images in Excel and get people to collaborate more quickly. Now Data self analytics version 9 has major performance improvements. Let's take a quick review about them. The data engine is much faster. This particular query which was tested by Tableau has been queried against a data extract with 173 million records, not thousands, millions. It's a huge database. What happens is before Data Step analytics was already super fast. It would take about 7 seconds to run. Now with version 9 it takes about less than a second. It's 10 times faster. Much faster. The data engine is so much faster. Querying and crunching data. Query fusion when you're building this dashboard, sometimes you have several queries that you have to hit the data to get information out of it. This particular Query here has two queries that with version 8.3 you would take 1, 2 queries and about 3.7 seconds to run. In version 9 because both queries use about the same kind of data, it does a fusion. Only one query can do the job and then there's about a two times faster performance improvement in the engine because of version 9. So much better because less queries are hitting the database. Parallel queries. A dashboard like this has several different queries that has to be rendered to build a dashboard like this. This dashboard was query against 157 million records and with version 9 it takes nine times faster because it does queries in parallel and they are faster. It's so much faster. Finally, the caching in version 9 is so much better as well. And the queries like this, which is the same as the prior one, it will run 50 times faster. In a nutshell, version 9 is super fast. That's awesome. We always like because we're always in a rush from an administration standpoint, this will be completely for IT people. There are much better ways to do group and user security in how to monitor the system and how to monitor usage. For instance, this is how people see users and group security. You see the groups here, you see individual users and then you see the different rights that they have. Green is granted, red is not granted and white is not available. So very easy to map people and see what they can do and what they cannot do. Monitoring the status of the system. There are many views now that will help you do that as an administrator. This one shows we call the three W's. This is what has been seen. So view counts by date and this by time. These are, I mean, I'm sorry, this is when the resources required by time, by date and by hour. Here is what queries were seen the most, what views were seen the most. And here who have been hitting the most the system. So we can know when, what and who and how they are interacting From a resources standpoint for server side and if we did more servers, more RAM or cpu, this kind of monitoring can help a lot. What action have been doing are people viewing dashboards, drilling down slice and dicing, downloading. This is the kind of, you know, monitoring status that we can have available. In a nutshell, what the main benefits of data self analytics in particular version 9 are first of all and the most important is as you could tell as the VP of operations, I was in the flow and I was able to do things by myself in a drag and drop intuitive way without calling it. So I was empowered. I could have done those things on a web and mobile device, most of those things. So empowering decision makers is the most important benefit of data soft analytics. The way we empower is twofold. We one is because we use Tableau as the reporting tool which is self service user centric bi and it's an enterprise grade. It's really the best one available right now. And we have more than 5,000 reports Dashboard KPIs that will go out of the box. That's how we empower decision makers. Easy to use technology with a lot of out of the box Reports. This tool will also automate a lot of the report data crunching and distribution. More than 80% of the labor intensive tasks that you may be spending today will be completely automated by this technology. So it cuts costs from a reporting standpoint by a lot. And of course having the gold standard of analytics is awesome. I, as a user I'm super happy because now I can go about my business, I can make timely decisions and I can focus on working on the threats and opportunities and not so much trying to figure out what they are in. Is so excited that they're not going to be doing reports all the time, one at a time, but they're going to be focusing their efforts in what is it? It's server side high end technology and now they're also using tableau engines and they're so excited because it's such a refined and polished technology and those are the benefits. So thank you very much for keeping up with me here. We're going to open a Q and A session. We don't have much time, but if you have questions, please use the GoToWebinar panel and I'll be addressing right now. Oh boy, we have a lot of questions. So first question here from Jennifer. Does dataself have the capability to export ERP general ledger data through the ETL to create financial reporting in financial statements? Jennifer, thank you very much. The answer is yes. This technology can address pretty much all reporting areas, of course, when it comes to financial information. Actually let me switch gears here and show you some financial information here. Most of the time when people come to us, they have financials already tackled by the ERP package. They have balance sheet and property losses that are already working. Some people come to us saying, hey, we're spending hours, days or weeks per month or per year putting our financials together. Quite often we can automate the process completely. Most people that ask US financials, they actually want to see financial dashboards like these revenues and projection and consolidated weekly and bars and charts, looking at the ratios of my sales by payroll, things of that nature. So for financials we tackle the three areas. Balance sheet and product and losses can be budgeting, it can be plain dashboarding. All right, so I hope I have answered the question. Thank you. By the way, Jennifer, next question. So, Oscar, what is the price structure, components, current or named users, etc. From a price standpoint, The ideal is to talk on a one on one basis because every company has different needs. What I can tell you is the entry level solution. You can literally start for hundreds of dollars per month. So if you go with the very basic, let's say a couple of users, 3, 5 users and you just want the very basics, you can go with this technology for hundreds of dollars per month. So it can be very inexpensive. Of course, if you are a large organization with dozens of users, maybe hundreds of users, it can go up. So I read the talk with you on a one on one basis to give your specific needs, but this is not going to break the bank and the benefit is so great. Oscar, thank you for your question. The other question here is for Carl. What ERP packages do you cover out of the box? Carl, thanks for your question. Let me go back to our website and if you go to solutions by ERP and CRM, you go here and you're going to have the out of the box solutions that we have. So we have several ERPs and CRMs that we cover out of the box, but if you have a different one we can also work with. Folks, we are running out of time. We have more questions but we will address them individually. I hope you have found this webinar informative. By the way, this webinar is being recorded. So if you come tomorrow back to our website in Resources under Webinars, if you go over there you can find more webinars registration but also the recorded webinar button. If you click here you're going to find this webinar being posted. We will also email it to you so you'll have that information. I also recommend you to come to our website and look at the 2 minute demo. So if you want to share this information with someone that doesn't have one hour available, the two minute, it's a great next step and absolutely give us a call. We love to do one on one presentations. We love talk specific needs even if it's just for your education to see what the options are, how we compare with other BI solutions, what are the benefits, the pros and cons. So here you have my cell phone, my email and my Twitter account. I hope you have a happy Thursday. Thanks for joining us and have a great.