Acumatica Data Warehousing & Analytics

Started. Hello everyone, my name is Johnny Girardi. I'm Data Sales Founder and CEO. Thank you very much for making the time to learn about data warehousing and analytics for Acumatica. We're going to jump right into the session. By the way, I've been doing analytics and data warehousing for about 20 years. I'm a big data geek. I love what I do and I love helping people make more informed decisions from their data. That's my journey. Before we get started, let me talk about Acumatica Inc. The company who actually designs Acumatica and they use Acumatica as their own erp. Nigel their cfo Sat Data warehousing and tableau analytics dramatically improve the time to insights. So if they're using data warehousing in Tableau out of their own Ecumatica in other systems, should you do it as well? Hopefully we'll talk about it and you can make a decision today or at least get to think about if you should from an agenda standpoint. First of all, we're going to talk about the business challenges that data warehousing and analytics can tackle and can solve. We'll talk about the pros and cons of data warehousing. We'll talk about Tableau in Excel tools using out of a data warehouse instead of out of Acumatica directly. Then we'll talk about specifically Tableau natural language query as well as drag and drop data analysis compared to how table people do without this functionality in Acumatica. We'll talk about if you decide to embrace data warehousing in tools like Tableau, should you do it yourself from scratch or should you get a vendor that provides you some of the components ready to go? Then we'll talk about Data Self. You know we are a BI vendor providing all this technology and to tell you about how it works, time to deploy, pricing and things of that nature. And then we'll open a questions and answer session at the end. If you have questions, please write it down. You can use the Zoom Chat or Q and A panel to post your questions and we'll address them at the end of the session. All right, let's move on. What are the business challenges that data warehousing and tableau analytics fulfill or tackle? The biggest value is pretty much nowadays we see a lot of decision makers that they want to see the facts before they make decisions and the time it takes to have a question and find the answer can be challenging. So a big value is the time that it takes to make more fact based decisions In a nutshell, if you don't use data warehousing analytics and you're just using the Acumatica business built in functionality, it's great. I mean, compared to many other ERP systems, it's better than many of others. But if you're having challenges, you know, the report is, there's complex in reporting, knowing the GI's, how to use the report editor, the dashboard editor in Acumatica, if you find those things challenging, that's a hint, you might stop, you might, you might, you might look at other options like data warehousing, performance issues, you know, it's taking time once you have a question, until you see the answer. It takes time to build the reports, it's time to run the reports, it's time to export the data out of Acumatica into an Excel. If it's taking too much time to run or you have to run the reports out of certain business hours, that might be an indication you might need to get out of that framework into data warehousing. Single version the truth. We see many clients that when they come to data self and they talk about this, they have GIs all over the place and they get out of hand, okay, what is the right way to calculate my metrics? And then with data warehousing in analytics, it's easier to manage and to define how your metrics should be calculated, how your revenue should be calculated, how your gross profit should be calculated, how your cost of sales, how your, your payroll metrics, your financial metrics. Everything can be defined in a single place to make the single version of truth easier to enforce. So the main challenge is that people, they start to see these problems and they start to think, how can we improve our reporting out of Acumatica? So let's talk about how data warehousing tackles or help to tackle those issues. And let's talk about first the benefits of data warehousing. What is data warehousing first of all? Right, well, pretty much the Acumatica is a source, we call a source database. In Acumatica database is highly optimized to do what to do erp, to do enterprise resource planning, to capture invoices, to capture your purchases, your sales orders, your GL transactions, your receivables, your payables. The, the database is optimized to do that and it also supports reporting. Yes, but is not optimized for reporting. And that's why we use a data warehousing or data warehousing is so valuable. You get the data out of Acumatica into a Separate data repository. You optimize the separate data repository for reporting purposes and then you can use other tools like Excel, Tableau, Power, BI to make reports out of it. So that's the mechanic of how a data warehousing works. So what are the benefits? Well, the most important benefit to understand is acumatica. Database is not designed for reporting, is designed for erp. Every ecumedica competitor, other ERP vendors, they have the same thing. We work with dozens of, actually about a dozen different ERP vendors, they all have the same thing. Database is great for erp, not so great for reporting if you're more sophisticated or if you have a lot of data. So the main reason why data warehousing is so great, because it's a reporting database versus the ERP database that makes report complexity go away. With a data warehouse, you can optimize the data structures to be easy for reporting. It runs fast, usually reports you running seconds. No matter how much data you have, no matter how back in history you go, you should run the reports really, really fast. Eqmedica, you can bring data together from different data sources. Yes you can, but there's still just tables sitting on a database. If you need to pull reports, if you need to get a report, bring data across different tables out of your ar, your sales, your sales order, your purchasing or inventory on hand, all of those things are all separate tables. And you have to know how to pull them together. It's complicated. With the data warehouse you can glue the data together. You can even glue data from other data silos. Maybe your CRM is outside, like Salesforce or HubSpot. Maybe you have a payroll system outside and you want to bring it together. Maybe you have some point of sale system you want to combine with Akumatica. So with a data warehouse, it's easy to bring any data together to do reporting. In the data warehouse, you can also define the single version of the truth. How do you calculate your KPIs? You define the single place. And now when you run the reports, no matter how many reports you build, how many dashboards, you have, your sales going to be always looking the same perspective. Your gross profit, your revenues, your cost of sales, everything will be pulled from a single location, the data warehouse. And when you change the metric, it changes all reports automatically. So much easier, better, faster way to maintain a single version of the truth. And then automating data preparation. You can combine data, you can aggregate data. Things that people doing gis in Excel can all be done by the data warehouse. So you don't have to be doing data prep outside of Acumatica. Some of our clients, you know, when they started Akumatica and many still do, they love gis. It's simple and easy. You can get the data out of Acumatica, but the clients will become more sophisticated and they need to do more elaborate, you know, data extraction. They complain the GIS are, you know, it's not as empowering. They're easy, they're slower, more complex, it's hard to debug them. And if you have a lot of GIs, it's hard to go to them and figure out which one do you should use. How is the rule behind this GI versus the other one? So GIS is good to get started, but in the long run, if you're having challenges with gis, data warehouse may be the next step. What are the cons of data warehousing? Well, there's an actual layer in your platform, so we pull the data from Acumatica into a separate data repository and then you do reporting. So there's an extra layer. There's usually actual license cost. In the past, data warehousing would be very expensive. Nowadays you can start data warehousing sometimes for free, there's free trials, and sometimes you can start with very little money on an ongoing basis because the cost came down significantly over time. So there's still some cost, but it's usually small. Well, when working with data warehousing, you need additional skill sets that understand how to extract data out of Acumatica, put in a data warehouse and do the magic. So yes, you need more skills in your team. It takes extra time to deploy, to maintain it. So there's actually some overhead and it's also near real time data. So typically you're not refreshing, you're not seeing data in real time. You're seeing slightly delayed, sometimes a few minutes, sometimes hours, sometimes even days, depending on what you're trying to see. So these are the cons that come with the benefits of data warehousing. A very quick perspective of a data warehouse. In this presentation, I'm going to go from business concepts high level to a little bit of technical. Don't be scared. If I go into the technical side, it's going to be short and very high level. So even if you're not technical, you should be able to get the hang of what's happening as a data warehousing for. So let me switch gears now and show a data warehouse for Acumatica. And I'm going to be using SQL Server as a Data warehousing platform, which is very popular in the Acumatica in the mid market as a data warehouse platform. And the idea is you pretty much bring your Acumatica DAC data access classes into a data warehouse through the GIS or not. And then when you go to this tool, you can actually see your Acumatica tables. They're all there, very easy. And then you can manipulate, you can add more metrics, you can add more indexes, you can do the data geek magic. For these tables to be easier, faster to get the data out. You can also bring data together using Views or some kind of SQL statement. And this is where usually when you do the framework optimization and gluing the pieces together, this is kind of, you know, you need to be more technical to understand the upper panel. But once you do this data gluing together and you run the query, what you get as an output is beautiful, well described fields that has all the, all your data, anything that is relatable can be glued together in the data warehouse. Make this data set that when you want to build a report and dashboard, you're no longer working with these complex things as a business user, you just pull the data out, you do the report and you run with it. We have some clients that then when they were not SQL Server people, they were millennials working with GIS and kind of liking it, but finding some challenges. When we showed how they could do the same things in GIS in here and using Tableau, they were like, no. Oh my God. This is so much more empowering. It's easier, it's faster. This is amazing. That's the kind of excitement we like seeing our clients giving you tools that is easier, faster to get data analysis done. So that was a quick overview of how a data warehouse looks for macumatica. And I use SQL Server. Let me show you now. Or let me talk about the benefits of using a tool like Tableau in Excel out of a data warehouse instead of out of Akumatica. If you do not use data warehouse, you have to use GIS or you have to export to Excel, I mean export the data from Akumatica into an Excel file. Everything is manual. You gotta wait. If you have a lot of data, it can take a while. If you try to export data through old data and you have a lot of data, good luck. It's gonna take sometimes hours and even days to make a full extraction. So without a data warehousing, pulling data directly out of out of Akumatica can be challenging. So with a data warehouse Again is a reporting database that is live. The data is there, you just run things, you see the data. Super easy for data analysis. Just like I showed you here, when you connect Excel or Tableau, you're going to see this. Not all the things behind the scenes. And when you run a refresh, the data comes right off out of it very quickly. So easier data analysis, faster report time. Overall, the recommendation is if you turn the dials of the solution, typically every single report should run under 10 seconds. That's usually something you can do using data warehousing, Tableau and Excel technology. You do the data consolidation behind the scenes. So when you're doing the reporting, the data is together. We have a client where we brought CRM data along with Google Analytics data, along with no receivables, sales order sales all together in a single data set. The user just have to run the reports, slice and dice it, and all the data behind the scenes is linked in the data warehouse. So data consolidation, big value in data warehousing. Single version, the truth already talked about. So you're just pulling the data out and you don't need to calculate the metrics they already pre calculated in the data warehouse, automatically refreshing the data. So with a data warehouse you can do procedures to automatically extract the data from your acumatica every minute, minutes, hour, days. So when you run the reports using Excel or you know, Tableau, the reports run quickly with all the data because the refresh is being automatically done by the data warehouse. Data governance. With data warehousing and tools like Tableau and even Excel, you have a lot of ways how to control the data. Tableau provides even better ways to control the data. If you're really paranoid about your data, Excel might not be a secure way to distribute reports because Excel is an Excel file. If someone has a bunch of Excel reports on their hard drive on a notebook, and the notebook is stolen, guess what? All the data is there. If someone stole it in their, you know, the competitor, they can see all of the data. With tools like Tableau, you can actually control if people can download the data or not, or they can only see the information on the web, you know, only on a browser. And if you close the browser, it's gone. So if someone steals the computer or not, they're not going to see your data. So from a data governance standpoint, using data warehousing and tools like Tableau, you have a lot more ways to control who can access, when they can access, what can do with their data. And that way you're more secured From a data governance standpoint, let's take a quick look at Excel pulling data out of a data warehouse. So let me open Excel here. And by the way, if you're looking to go with Excel only out of Acumatica, I encourage you to look at Velexo. It's a great Excel add on to pull data out of Acumatica. They kind of use some kind of, you know, simplified data warehousing technology behind the scenes. That might be enough for you if you want something a lot more robust with a lot more options. That's what I'm going to be covering here, you know, using a full blown data warehousing and the functionality anyhow. So in this case I am in Excel and I'm going to get data from my data warehouse. In my example, I'm going to continue to use SQL Server as a data warehouse platform. You can use any Data Warehouse, Oracle, DB2 and whatnot. Let me put here the credentials to this data warehouse. Even though what I'm doing right now is a little bit technical, but in a production environment these steps here can be done by the business analyst. As a business user, I just opened my report and press refresh and the data is refreshed automatically. So I'm just showing you a little bit of the mechanics of how to get the data from the data warehouse into Excel. And from that point how you distribute Excel is usually a simple discussion. So let me connect to the data warehouse, which by the way is what I showed you before. You know, these are the data warehouse in SQL that I'm connecting. And now in Excel when you connect with, you see exactly all the tables you have pulled from Acumatica, the GIS or the tables are going to be listed here. And then including those things we can aggregate in data warehousing using Views or using ETL procedures, you can glue the data together and you could decide. As a business user, when I open my Excel, maybe I only see this because it already gives me a nice descriptive name so I don't see everything else. The feeding tables, I don't care. Maybe so you don't give me access to them. You can control that using security in your data warehouse framework. But once you select a table or tables and you click load, the data will come to your Excel very quickly. No matter how much data you have, you're not using your data anymore. You're using SQL connection to Excel or whatever the database is. And that's usually super duper fast. And now in Excel you can do your magic. Whatever you do in Excel. So that's just a quick overview of how to get the data warehouse data, all that magic into Excel quickly and easily. All right, how about tableau Natural language query in drag and drop reporting? For many people, Excel is complicated. You know, they find it hard to use it find to build things and they, they want something easier to use. Well, let me show an example of tableau as natural language query and drag and drop. So the same thing that we did with Excel to pull data out of the data warehouse can be done using tableau Power bi any reporting tool. And once you have that data into your, let's say tableau, this is how these tools can help you get data to different users. Natural language query, it's like searching the Internet, like with Google and Bing, where a user asks a question and the tool will build an instant accurate report on the fly. For instance, right now I'm using natural language query out of sales out of acumatic. I'm going to say show me sales by oopsie got reloaded sales by salesperson in 2020. So I ask a question, the tool give me hits just like in a Google search. You, you select the heat that is the right answer to your question. When you click builds from scratch. An instant accurate report. So by salesperson is showing sales in a descending order in 2020. It's that easy. You need to know English. And if you articulate the question correctly and you choose the right answer, if it comes with an answer, you get the report right there. Let's say I want to break it down this by month. You type by month, the tool give you the hits, you find the right one and there it is by salesperson. It gave me a line chart showing sales with the months in 2020. Very empowering. Maybe I don't like charts. I want to see like a grid, like an Excel table. Sure. I can select tax table, the same report showing sales by salesperson in 2020 by month. And maybe now an export to Excel. Very popular. People want to find information, get it to Excel. Sure. You can select the data points of your report. You tell the tool, show me this data in a separate format. I actually want to see every single line, all the invoices, all the details of this particular report export to Excel. And now I got the data into Excel. There it is. I got all the data, those data points into an Excel format. All right, so this is the natural language kind of functionality. Natural language is about five years or so old, so it's fairly new. Amazingly empowering. But it's not a magic wand. You will answer simple questions. Sometimes not so simple, but more sophisticated data needs. You still need people who know databases, tables, how to link them and how to use the report editor. So this is more for quick and easy ad hoc questions and answer anytime, anywhere. What I'm going to show you now is the report editor. The drag and drop in this report editor that I'm showing tableau is amazingly empowering and it's super easy to use the basics. Like 80% of the reporting that people need, the custom reporting is just drag and drop. Let me show an example. Right now I'm connected to the data warehouse showing my sales information and if I want to see sales by customer for the past two years I find the customer here. I drag to my rows. So these are my customers I want to see sales I drag to my report. So this is total sales for all my customers. Well when I see by year I add my invoice date to my columns and by default it shows all the years. No matter how much data you have, it's all there and I only want to see some of the years. So I make a filter out of my invoice date and I tell only show me the last two years. So in a few minutes I built from scratch a new report. Drag and drop, point and click. There are many clients of ours that I've seen that many business users they just saw a demo of Tableau and they learned to do a lot of reports and dashboard by themselves with no additional training. If you know how to drag and drop, you can also do a lot now to build more sophisticated reports and dashboards. Yes, you need training and if you're going to be an expert, it takes a lot of effort to become a really an expert. But the 80% of the needs you only need about 20% of the of the features that are very easy to learn and to become self sufficient. So that's a drag and dropping out of tableau which is very empowering and very easy to use. All right, so I just covered data warehousing, how tableau in Excel work pulling data out of a data warehouse, how you can use natural language and drag and drop to do better reporting out of acumatica. Now if you are intrigued by maybe you want to do this, should you do it yourself from scratch or should you subscribe? What are the pros and cons of both sides? Well if you do it yourself, typically be sure you have the people and that's not a person that is usually more than one person that can actually connect the dots. Typically you'll need skill sets that know ecumatica, gis and tables that know data warehousing. It doesn't need to be a programmer per se necessarily, but knows how to get the data out of Akumatica into a separate database. And then building reports and dashboards is usually a skill set for business analysts. So typically you have a second person, there is a business analyst that once the data is available for them, they will know how to use tools like Excel and Tableau to do better reporting. So typically if you do it yourself, you might need two people skill sets from two people to actually do the job well done. There are people who can do everything by themselves. Absolutely. If you know some that are available, I'm hiring so let me know because we love to find those people that can work more than one layer of a BI tool. But overall, if you're doing it yourself, you might need more than one person, not full time, but you need more than one person working together to get all the dots connected and working seamlessly. You need to decide the tools, okay, what's going to be the warehouse platform, it's going to be SQL Server, going to be Access, it's going to be DB2, Oracle, OneNote. So you got to decide those things. You got to decide which reporting tool should you use, tableau, power, BI, QlikView, whatnot. So you got to go through that selection process. It takes time, sometimes time to find the people, to train the people to find the tools, to know which tools to look for, which ones are certified by Akumatica. Do you care? Should you care? So it takes time to get the hang of getting all of those pieces components working. And ultimately at the end of the day is there's an roi. You know, you have control, everything is there, it just takes longer. Sometimes it takes a lot of money to get the business connected and you may figure out it's worth it. My main recommendation, if you decide to do it yourself, do your best to retain the people. Because if you have these people doing all this work for you and they leave the company and you got to get someone else to maintain it, it can be challenging when you change the people supporting your BI solution. So do your best to find good people and keep them in your business for your long term data analysis continuation per se. That's my main recommendation out of this whole process. It's about people at the end of the day, right? If you go subscription, there are many companies out there that provide BI tools, sometimes just a component, two components out of the box. Typically when you look at these BI vendors out there, typically you can get a much faster roi. Typically instead of taking weeks, months, years to get the value, you can get the value in minutes, hours and days. So usually the return on investment is faster. You'll be paying for it, so you're going to pay someone else to do that job, but you get the result faster. An important recommendation is also ongoing support. Most likely you're going to have some of your people, sometimes one or more people that are going to be the ones doing the internal work, but they're not going to be experts in the acumatica databases, in data warehousing, in tableau, whatever the tools are. So count usually on the vendor to give you personalized support to your team to be successful. And if someone leaves from your company that are supporting, typically these vendors should have services to kind of, you know, fill the gaps and help you go to these transitions where people are in, you know, family leave or they left the company or not. And then the BI vendor might be a way to outsource some of your needs temporarily. So ongoing support can be a very important value of going with the vendor. Another thing that I tell that is very important in my perspective is business change. Business required business grow significantly. And the BI solution tends to be one of the most critical components of a business in the long run. So be sure that if you decide to eventually transition the whole BI for doing it yourself, you want to have the whole control, you want to hire more people, you want to have everything behind your firewall. You don't want to use a third party vendor. Check for vendors who provide you ways to take full control of your BI and make it easy for you to transition it out. Many BI vendors, they don't do that if you discontinue their service, you have to scratch everything away, all the investment is gone and now you have to start all over from another vendor. So this is also, I would say is a big decision point of selecting a vendor that transition easily into your business and easily out in case you decide to take full control of the BI solution. All right, I just covered education so far about options. Let's talk about Data Self analytics. As I mentioned, we've been in business for about 16 years now. We started the business with Acumatica in 2018, in early 2018 and at the end of 2018, Acumedica Inc. The company decided to embrace Data Self. So let's talk about Data Self and what we're bringing to the table here. So first of all, what is Data Self? So Data Self is an architecture where we bring data warehousing and our data warehousing SQL Server, which is one of the most popular out there. So we absolutely leverage all the bells and whistles of SQL Server. We pull the data out of Acumatica in any data source into the SQL Server database, can be in the cloud, can be hybrid, can be on premises. So we have full support of whatever deployment architecture you want. We use our own ETL tool. ETL stands for extraction, transformation, loading, which is the mainstream technology to the data warehousing. And we'll talk more about it in a minute. So it's easy and fast to deploy and maintain the data warehouse. Then we connect tools like Tableau and Power BI. We've been working with Tableau for about 10 years now, with Power BI about two years. Our solution is so much more comprehensive out of Tableau, even though we are building also mappings on the Power BI solution out of the box. Typically we can plug and play to Acumatica in minutes. Actually you can do it yourself in minutes. You deploy Data Self and your management can start seeing a lot of things that I showed you today out of Data Self. Out of this initial investment, we have an entry level version that comes with dozens of reports and dashboards and we have an enterprise version that comes with thousands of reports and dashboards in Tableau looking at financials, payables, receivables, inventory, purchasing, sales, sales order, project accounting, CRM. There's a lot of things if you go with the enterprise, but that's what we bring out of the box. Plug and play. You don't have to call Tableau, you don't have to call Microsoft. We can be the one stop shop for all of your BI needs from a license standpoint as well as ongoing support services. We're just here to help you succeed in the data geek journey. So that's what the architecture is. Probably have heard about ETL and what's all the fuss about ETL plus Data Self at the heart is a data warehouse company and our initial product was an ETL or is an ETL we built 15 years ago. But three years ago we decided to build a new ETL from scratch because the old ETL was designed before the cloud world and now the cloud is changing a lot of things. So we decided let's crash the old, let's build a new one from scratch, an ETL that can leverage on premises and cloud store systems very efficiently and make the process much easier. That's why it's so amazing, it's fairly new product, it's amazingly empowering, it's easy to use and very, very efficient. Let's take a quick look in ETL plus. So now I'm switching to the ETL plus. Currently this ETL plus still requires a little bit more technical knowledge to use it, but we are building also UI that make it more wizard driven. Anyhow, on the left we can see the data source which is right now is OData. So we're pulling data from GIS and then in the center panel is actually the data warehouse tables. So whatever you decide to pull from the gis, you put it in the SQL data warehouse. And here's how you define the statement that will pull the data from each of these GIS. So you have source target and the SQL statement pulling those GI's. Now some of the things that are amazing here is you can pretty much replicate the data from GIS into the database if you have a lot of data. This ETL has what we call the update refresh. Update refresh means the following. The first time we bring data from Acumatica to the data warehouse, it brings everything. And if you have a lot of data, that can take many minutes, hours, even days. Some of our clients, when we brought this first time, it took days to do the first initial load. Now once we did the initial load, the update refresh means only refresh on an ongoing basis. The deltas, what has changed since the last refresh and what's new. So typically after the first load, refresh will run in seconds, maybe a few minutes. Because this update process is super efficient to extract data. This example is using OData v3 version 3, which still uses GI's. We already have ETL supporting OData v4 and when you work with OData v4, which you need Acumatica 2020 or two or newer, you have direct access to the DAC framework. So the DAC is pretty much almost the SQL tables behind Ecumedica. And here you can see all DAC options available. You do not need to use the GIS to extract data out of Acumatica. This is going to be an amazing journey using OData D4. It's faster, more empowering for data geeks. Now data geeks love raw data because we can get the data raw data out and do a lot of reports and dashboards out in tools like SQL Server. So that's pretty much a main overview. The ETL plus. Oh, by the way, on the right side we Use SQL Server, I'm sorry, SQL statements as the way to manipulate the data. If you don't know SQL, you usually don't need much. You know, you just add a table, it goes straight into the data warehouse. If you know SQL statements then you can go over here and manipulate the data extensively. For those who know SQL statements or they know how to search in Google for the syntax, they'll find that there's a lot of materials out on the Internet supporting how to do SQL Server statements. It's an amazing. The amount of help you can find online nowadays to customize your SQL Server statements at the end of the day is data warehousing will give you more tools to be more self sufficient. All right, I'm going to do a quick demo of data self analytics. So if you go to data self analytics you can actually embed the data self dashboards which are typically right now tableau dashboards inside of Acumatica. So when a user logs in they get the data self dashboards like they were Acumatica dashboard. So it's seamless. If you wanted to give some users access outside of Acumatica. Absolutely. You know our dashboards can also be accessed inside of Acumatica completely outside of Acumatica. It can bring any data. Like in this example we have Acumatica data, Salesforce Data Shopify, Google Analytics, HubSpot, more data, payroll data. It's all part of the container in the data warehouse. And I'm going to navigate some of the dashboards here. Like this year over year sales dashboard is out of the box available, very popular in our client base. Pretty much you can see year over year, sales by period, totals by customer, by product, by territory. Very interactive dashboards. So if I want to see for the whole year all the periods I press apply for all the periods. Now the dashboard shows me for the whole periods. And look, I have one of these customers that is declining sales since last year. Now this year 2.1 million. Last year was slightly less actually let's take this one, this year is 2.2 million. Last year 2.8. What happened with this customer? Right, you want to see from the high level. Now you want to go to more detail. I can click on this customer. The whole dashboard changes now to show only data for this customer. The totals, the trend analysis, what I'm shipping to and what products I've been shipping. So very easy to look at the high level KPIs drill into a subsection of it and maybe now I want to see the actual sales details. I can click now show details and then at the bottom it opens like a GI kind of framework where I can see every single detail behind those data points. And now I can export Excel if I want to do it to analysis outside of this framework. What I'm showing you right now would be available out of the box a few minutes after you deploy Data Self and after the data is loaded to the cloud. We have, as I mentioned, dozens of reports and dashboards available out of the box. Pareto analysis, Daily Flash. I mean there's a lot of things that can that would be plug and play in highly customized. When I showed you before, natural language query, drag and drop reporting, Tableau. That's what you get with Data Self. You get the Data Warehouse, you get the ETL plus to customize your data warehouse. You get Tableau as a tool to customize it with out of the box a lot of reports and dashboards. And with the proper user license, you can also get your data either export to Excel or go directly into Excel and pull the data out of the data warehouse. So all of those things are part of the Data Self Plug and Play framework. All right, so we're running almost out of time. Let's keep on going. How long does it take to deploy Data Self? What is the pricing? If you go with the entry level we call Advanced analytics, It takes about 30 minutes to deploy this solution and many things that I showed you today here are part of the out of the box of Advanced analytics. And the pricing starts at 299 per month. We actually have a free trial, so the first few months, I think three weeks is free and after you decide to Keep it is $2.99 per month to get started. We also have the Enterprise analytics, which is a much more robust there's a lot more reports and dashboards and give you full data warehouse capabilities. This version takes about 30 days to deploy and the price starts at 1499. Good news is most of our clients since we launched Advanced analytics, they continue to be Advanced analytics clients. So there's a lot of value out of 299per month on average. I think a quarter of those clients eventually move to enterprise. So there's a good chance that the Advanced analytics might be enough for many of you out there in this webinar in case you decide to go with us. A sentence from again from Nigel. They have been using dataself since 2018 as a data warehouse platform. With Tableau and the reports and dashboards, Nigel said dataself has the ability to quickly translate questions into solutions because of the expertise and data sets they already have established. What he's saying is we came with the data warehouse out of the box, we came with Tableau out of the box, we connected the system out of the box. We got a lot of reports and dashboards ready to go. But Acumatica has a lot of custom needs. So with our expertise of data warehousing, Tableau, Excel and the things we've been learning with Acumatica, we've been on an ongoing basis supporting Acumatica Inc. To help them be getting quick answers out of their questions so they can move their business faster, their business more quickly forward, and help their clients more successfully. So we're very fortunate to have Acumatica as one of our major reference sites. What's next? If you want to learn more, dataself.com has a lot of good content. Feel free to email us or call us. We are data geeks. We love to talk about data geek problems, give you some inspiration, point in some directions. And if you decide that Data Self is a good fit, boy you know we love it. We are a fun crowd. We do care about our clients. We have personal relations with our clients. You'll have our phones, our emails. We will do our best to help you succeed in becoming a little bit more of a data geek. You can order Data Self contacting your var. You can also order directly from Archimedica. You can order from dataself.com by the way, if you go to dataself.com this is dataself.com you can also go to Industries tab and if you choose one of these industries, you can see the webinars around how we bring value specific for your industry. If you scroll down you're going to have sample reports. What reports come out of the box out of Data Cell. So feel free to explore these materials to see if we can be of value to your business. We're almost running out of time so let me just wrap here with the next slide which is a Q and A and before I ask any check the questions, a summary of Data Self. What we provide is a pre configured data warehouse reports and dashboards in Tableau ready to go, pretty much 30 minute deployment. It's easy to use, it's easy to customize. We want you to do as much as possible run reports in seconds no matter how much data you have. It will automate data preparation and report distribution. And it's powered by Gartner endorsed BI components, meaning if one day you're using Data Self and you decide to take ownership of everything. You want to just do it yourself. You can get your SQL Server databases, you can get your tableau power BI tools, you can buy our templates and off you go. We don't keep you hostage our business. We're here to help you be more successful and we're using Gartner endorsed technology. So it's great technology out there, widely supported. Having said that, we have only one minute to go. Actually we are. One minute pass. Let me just see if there's any question here that I could answer quickly. There are questions. Let me pick one of them here that is easy to answer. Question from Laurie. How long does it take to learn data self? Laurie? It depends. As I mentioned, we have clients that they got no training and they became self sufficient with data self. So it's possible. Yes. No training. Yes. If you're self taught. If Search the Internet. Internet. There's a lot of training materials out there, including our website. On average we recommend 8 hours of training to learn the basics of tableau. And with those eight hours you can do a lot. But if you want to learn everything, data warehousing, etl, tableau, server, desktop, I mean there's a lot of things that can take quite a bit of effort. For enterprise clients, we typically budget at least 24 hours of training to cover all the components to enable them to be more self sufficient. Folks, we're running out of time. Actually two minutes after the hour, after the, you know, the 45 minute time slot. Thank you for sticking around. This webinar is being recorded. We're going to be emailing you the link for the recording session. Feel free to share with other people. If you want to contact me, you have here my email, my phone number. Thank you again for joining us. I hope you have a great day. Thank you.