Acumatica - Empowering Data Heroes with DataSelf Analytics, 2412

Alrighty. Good morning everyone. We're here to talk about Acumatica empowering data heroes with Data Self analytics. My name is Johnny Girardi, Data Self's founder CEO. Tom, if you please introduce yourself.

Tom Fitzpatrick, BI Solution engineer with Dataself.

Thank you Tom. I'm a big data geek. I was a software engineer in my early career, became a business person and for the past 20 plus years I've been helping mid size organization, small and midsize organizations do better when it comes to Reporting, analytics and KPIs. This is my license plate, it reads Data Geek. Anyhow, the agenda today is we're going to be talking a little bit about why some companies, many companies using Acumatica don't feel the power as when it comes to reports, KPIs and dashboards. We'll show a little bit of, you know, the product demo, how the solution works behind the scenes and at the end we'll talk a little bit about the promotion for people attending the webinars. So hang up, hang around in case you want to know about some promotions. Data Self analytics and reporting covers multiple industries, so pretty much no matter what your industry is, we can help you. The ones listed are the most popular in the Akumatica world with dataself. By the way, we've been working with Acumatica since 2017, so we have about seven, almost eight years of experience helping Acumatica do better from a reporting standpoint. And the main reason that people go for Data Self primarily is because by investing in Akumatica you pretty much you are developing and nurturing a data driven culture. You know, you want people to make more informed decisions, you want people to make from decisions anytime, anywhere. And many companies find that Acumatica has all the power that they need. You know, there's a lot of, you know, reporting tools built in the Akumatica framework. So many companies are happy with it, they don't need anything extra. But many companies still feel it's not enough. Our decision makers are still not happy, you know, we're still taking too much effort, effort. And they say, you know, the data heroes need more power when it comes to reports, dashboards and KPIs. And that's when I'd be talking about why that's happening. Why even though with Acumatica some people don't feel they have the power to do better reporting, the main reason is not Ecumatica's fault. Ecumatica, like any OLTP system, OLTP means online transaction processing system, erps, CRMs, payrolls, all of the systems, they are oltp, they do have reporting. And the reporting that they have is what we, the data geeks call the microscope reporting. You know, is a reporting that is amazing when you are looking at staff problems, staff reporting problems, when it's transactional focus. I want to see what I'm going to be shipping today. I want to see what's being posted to my GL transactions today. You're working with small data sets, so a lot of those needs that you have for transaction focused reporting, the microscope reporting built into ERP systems and OLTP systems are usually pretty good. The problem is when you start hitting things that are not the focus of the microscope reporting. We call the telescope reporting. And that's what BI based reporting is for. You know, pretty much when you're looking at management oriented reporting, pretty much you're looking at, you know, big data, you know, not only today, but you know, weeks of worth of data, months, quarters, years, consolidation. If this management reporting, quite often you're working with a strategic predictive type of analysis and quite often you're working with large data sets. And quite often the microscope reporting doesn't do well. And the telescope is what really is the solution for that kind of problem. Putting a little bit in more practical terms, the challenges of the microscope reporting, one of the most important is just slow. If you press the refresh button of reporting, it takes more than 10 seconds. That's too slow. Many decision makers, they won't wait if it's taking too long to run or maybe they can only get a certain report once a week, once a month, once a quarter because someone else has to do a lot of export. Excel didn't massage or not for many businesses waiting for that, you know, waiting for the next week or next month, next month is sometimes no longer acceptable. So it's not timely. That's one of the main challenges. The other one is learning the microscope reporting means usually you need to spend a lot of hours to learn how to modify reports. It's technical, you need to be a business analyst. Many decision makers, they cannot create reports, change reports or create a gi. For instance, creating GI is not for the faint of heart. You need to be very technical, you need to know the tables. So difficulty of report customization is also a complaint of many data heroes that are business users. Many times a lot of manual processes, export Excel, run a bunch of macros, validate the data, putting different reports email to people you know, it can be very time consuming to run certain reports using the microscope reporting approach. And finally if you're getting data out of Acumatica for reporting using tools like Excel reporting services, Chris and whatnot, quite often you might be emailing reports to people and then you might have data leakage. Oops, I emailed the report to the wrong people and once it's sent the email is too late. So there are also challenges when you have management reporting and you have to email Azura Vacuumatica. What data here really wish for is well, reports should run fast, anytime, anywhere I press show me this data you want to see it usually in seconds. BI based reporting delivers in that kind of speed no matter what how much data you have, multi company, multi currency. If you're consolidating data from acumatic and other systems, doesn't matter, you want to run reports in fast automatically. It must be easy for business users to change the reports to slice and dice the reports without calling the experts. It should be easy for the experts to actually automate and streamline the process without doing a lot of manual work. So helps decision makers and business analysts do the work a lot more effectively. The idea is quite often people are saying they spend 80% of the time doing data prep and only have 20% of the time to do data analysis. The idea is to flip that order, spend little time 20% doing some data prep that only humans can do and spend most of their time actually analyzing data and finding opportunities interest that otherwise are not seen in analytics. And BI based reporting provides a lot more layers of security so you can control who, when, how they can access the data and quite often avoiding dramatically making it safer to avoid data leakages. We'll show next how data heroes use Data Self analytics from a business standpoint. And then after the Tom's demo we're going to show a little bit about the back end how business analysts can customize that part of the solution. Tom Great.

You all should be seeing my screen now. So first what I want to call out is the fact that Data Self can be embedded inside of your Acumatica instance. Okay, so you could have it be a separate site or you can have it embedded inside of Acumatica via the site map. Data Self does support single sign on. So when you log into Acumatica you would also be logging into Data Self from a demo. Just to give you a line of sight as to where we're going, I'm going to show you three separate templates really to that involve the sales aspect of your businesses really just to highlight the features and functions that are going to be within Data Self across all of our templates. And then I'll spend a handful of minutes thereafter just highlighting a variety of other reports that cover various business areas. Okay, so where I want to start is our slicer template. So as the name would indicate, this is where you can very easily slice and dice your data. It's built to give you quick answers to ad hoc questions. On the right hand side we can see our filters. So if I wanted to do comparative analysis of my sales data across multiple years, I just simply point, click and apply. And now I can see 2028 through 2030 sales information. I can also drill down into this data if I'd like. So if I want to drill into my 2030 data across the various months, I could do so leveraging the filtering functionality, I can easily again just point, click and apply. And now I can just see Q1 2030 sales information. Up at the top here we're looking at, these are our slicers. So this is how you can slice and dice your data. When I select this first slicer, right now we're looking at our sales broken down by the item. This is just a default listing of data points here. Data Self can train you how to add additional data points. Or we could add those for you. But I do want to highlight that within Data Self we are going to have the ability to pull in really an unlimited number of custom fields, user defined fields, attributes from within your acumatica instance. So even if you have a heavily customized or personalized acumatica environment, we can still leverage the data from those custom fields, those attributes, those user defined fields for reporting. Continuing on here, I'm just going to simply select salesperson. And here in just a second or two, now you can see we're looking at sales broken down by salesperson. Okay, maybe I want to expand on this. At this point I can just simply expand. And now I'm looking at sales by salesperson, by customer. Maybe now I want to pull in that item information, simply expand, select the dropdown and my item. Okay. And that data is going to automatically render for me. So the nice thing here is this slicer, it has a look and feel very much like a Excel pivot table. But we like to call or joke that it's like an Excel pivot table on steroids. And that's because this data is going to be automatically refreshed at a refresh frequency of your choosing. So it could be, you know, daily, hourly, even down to the minute if you'd like.

Okay.

You're also going to be able to Slice and dice this by various metrics. So right now we're looking at it just by sales. But this is a multi select dropdown. We could have it by commissions, by, you know, gross profit, net profit variances, quantity sold, etc. So again, just point, click and apply. And now we're pulling in our profit percentage with our sales data.

Okay.

Ultimately the slicer template, super easy to learn, very intuitive. At Most it takes 5 to 10 minutes to train users on how to leverage the slicer template. It's not the sexiest of our templates and not what people think of when they think of business intelligence, but from a functionality perspective and ease of use, it really delivers specifically as it relates to the Acumatica ERP ecosystem. Really every click that I've gone through here on the slicer side is like creating my own generic inquiry. Nice thing here is I don't need to understand how those tables link together, how they join together. That all is being handled in the background within Data Self's enterprise level data warehouse. So we have data modeling and data warehousing that we're leveraging with these reports as well, which we'll speak to in just a moment. But really, really empowering business users to take control without needing consultants or business analysts to build this for you. Johnny, anything that you'd like to compliment?

Yeah, just a quick note. One of our clients before Data Self, they had almost a thousand GIs that they had created over time that the business analyst was greater over time to tackle different kind of questions from the business people. And about a year later, once they were fully immersed in Data Self and I asked the business analyst specifically for him, usually what Tom showed is what business people take advantage of. They just go there and they find the answers to their questions without calling an expert. Then I asked the business analyst person, so how is it working for you specifically? And he thought a little bit and he said before Data Self he was writing GIS left and right, mean pretty much every day, sometimes more than once a day. He was, you know, someone would ask a question, they would have to wait for him, read a gi, send to the person, the person goes back and forth and eventually be ready. In many times the gis when it was ready was too late. You know, sometimes put the information now, not an hour from now. Anyhow, he was saying before did a self I was writing GIS all the time and now I haven't wrote the GI for almost forever. You know, it's been since Data Self I stopped running gis and actually I'm a lot more productive. I'm helping a lot more people make more informed decision more quickly. So the idea of the business analyst not having work because something like Data Self would reduce is usually the opposite. You know, the more information you give to people, the more they need, the more the business analysts will have to work on the back end of the things. Customize the data models and letting decision makers be more independent by finding questions, answer their questions using something like the slicer. Thank you, Tom.

Next template that I want to highlight here is our natural language query. So artificial intelligence machine learning is certainly very popular in the tech space right now. It's, it's, you can't avoid it. It's everywhere. This template here is just one use case of how Data Self is going to leverage artificial intelligence in machine learning. And this template really kind of has a look and feel similar to an interactivity, similar to ChatGPT if you've interacted with that tool. So just like in ChatGPT, you ask a question, it's going to give you an answer based off of what you've asked Here in our template set, you ask a question and it's going to spin up a report that previously did not exist based off of the data that you have within our data warehouse. So this is where we can say sales by salesperson in 2024. Okay, once I have that typed out, I just simply press enter and here now you can see our sales broken down by our salespeople in a descending bar chart order in 2024. Okay, now just like in ChatGPT, maybe I don't like the answer or I wanted to add or expand upon what I initially asked. I can certainly do that as well in Data Self. So I can just say, all right, I want to see this now broken down by month. Once I have that typed out, I hit enter. Now I can see that that data is rendering for me in a line chart view. But we're seeing our sales broken down by our sales people by month in 2024. Okay, Tom, maybe I don't want to see this as a line chart. I can come over here, select this dropdown, and maybe I want to see this like a text table so that Excel like look and feel. I have the ability to do that as well. Okay, so again, just a, a one example of how you can leverage natural language query. I will highlight that. It's not a magic wand. It's not going to be able to answer everything for you, but it is an example of how you can. Just an early example of how you can leverage artificial intelligence to answer some of those low hanging fruit questions that you have as it pertains to your business. That's only going to become more and more impressive as as the the architecture is built out better as you begin to interact with with this platform, it's going to understand what it is you like, what you don't like. So it's going to correspond. And so there's certainly a lot to like and is very we're finding it very easy to use for, for some of those low hanging fruit questions that you may have within your business. Johnny.

Yeah, just complimenting quickly AI machine learning. It's usually think about specialized tools like you know, self driving cars. So there's specific AI for self driving car for every brand per se in the report dashboards and KPIs. That's our focus. If you guys think that you want to get your journey of AI to improve decision making because of reports, dashboards and KPIs. Our framework has layers of AI already built in as well as supporting a lot of different AI models that can be plugged to our open architecture of SQL Server, data warehousing on the front end tools like Tableau, Power BI and Excel, all of them they already have AI kind of built in. So we have been helping many clients start to use AI machine learning for better decision making. When it comes to again reports, dashboards and KPIs. This is one example, but there are multiple. Back to you Tom.

Next I'd like to show an example of a dashboard within dataself. Now we know that Acumatica has real time drillable dashboards. Really where Data Self differs from Acumatica is that when you drill down into any data point it's still going to leave that dashboard look and feel for you. So really the vision behind Data Self dashboards is for whether it's business, users, decision makers, C suite management to quickly and easily identify any outliers so where you're doing well, where you're not doing so well and then drill down into that data point. But within Data Self still have that dashboard look and feel where you can further analyze, identify additional outliers, drill into those. Ultimately Data Self is going to support unlimited drill down capabilities as well as the ability to drill across which we'll show in just a bit as well as drill down into the underlying data which which would be consistent with a generic inquiry look and feel. So just to give you a high level understanding of the, you know, lay of the land here again this is a A dashboard related towards sales, but could be leveraged for DL financials, purchasing, project accounting and so forth. But here we can see this year, prior year, the variances broken down as a bar chart, we can see our sales trended over time. As a line graph, we can see our sales broken down geographically.

Okay.

And then we're pulling in customer and product service information prior year, this year in the variances.

Okay.

Now you're going to be able to configure this template however you, however you would want. This is just an example for demo purposes. So I'm going to pick on New York here. We can see that New York has a 25% sales growth this year compared to the prior year. It's a great accomplishment. We should certainly be celebrating and cheersing to that initiative. When I drill into New York to understand why that's happening, you can see now my dashboard's only showing me data pertaining to my New York customers. Okay. And While we're growing 25%, you know, we want to identify those outliers. What's really grabbing my attention is the fact that my third largest customer prior year is down almost $900,000 this year. Why is that happening when I select that customer? We can now see that this dashboard is only showing me data pertaining to this customer. Okay. What are the products or services that are driving this decline? Well, I can see it's these items here. When I highlight those, I can say show me the details. Okay, Now I have that underlying data here where I can see the invoice information, the customer name, who the salesperson was associated with, item descriptions and transactional information as well. Please note that data self is going to be able to include that hyperlinking within acumatica. So this is where I could drill into that invoice and memo that AR source document here. So if I wanted to look at this deeper, I could simply just select this hyperlink and it's going to pull up my invoice and memo page where I can further take action if needed.

Okay.

So again, these dashboards, they're built for decision makers, business users, C suite management, to really understand high level how we're performing quickly and easily identify any outliers and then be able to drill down further to understand why something may or may not be happening and be able to drill into the underlying data where if something doesn't look right, you can actually drill into that source document and either take action or further review. Okay, Johnny, comments and questions.

Yeah, just I think a quick use case that a client was Telling why they love the data self dashboard so much better than the Acumatica which are pretty, you know, Akumatica dashboards are pretty good. He said that before when they were having meetings, management meetings and were coming with the Akumatica dashboard showing the KPIs we were super happy because the prior yearp sucked. They didn't have anything similar. So Acumatica brought the KPI through dashboards and they were all happy meetings to see the KPIs. But quite often it would happen something like this, hey, why is that number? Fill in the blanks. Too bad, too good. And quite often they would click in that number, they would go to GI and then they would say okay. You know, the meeting would either stop because now they have to export to Excel and start to sift through the Excel file to find what caused that KPI to be good or bad. They would usually just say okay. No, they would ask, they would task the business analyst to try to find why that KPI was weird. Then the next meeting they would have the report and he said no. Sometimes they would say hey, but now that we need to find why this customer is growing or declining then pretty much it would take forever to come up with a perspective that now like Thomas showed pretty much from a dashboard. You can keep slicing dicing at the KPI level at the year, quarter, month, whatever the period you're looking and only when you want to see the most detailed level when you want to see the GI at that point to say I want to see a GI looking drill down now and then you can go to that level when you want. And he said that was a major game changer for making decisions at the meeting. Not who knows in the future when the business analysts would be able to find out what what was going on with their their data trends. Back to you Tom. Great.

So that was just a high level overview of of some of the consistent features and functions within our dashboarding or within our templates from an interactivity perspective. Now I just want to highlight some of the additional templates, some of the the various business areas that they'll they'll cover. So migrating over into our financial side of the house data self is going to leverage a variety of different financial reports. Here's an example of a profit and loss with our budget included. There's going to be multiple different iterations of a P L but here you can see real time budget to actual information in the variance if you'd like to always going to have consistent throughout all templates. The filtering functionality to do comparative analysis or drill down into at the branch level or maybe if you're leveraging the segmented sub accounts to slice and dice however you would like. Here we have our cash flow projection. So really the vision behind this dashboard is looking at money coming in against money that's going out. And then with this black line being to forecast or project where you will be from a cash on hand perspective at any point in time into the future. Okay, now this will support kind of that what if analysis so you can add money or remove money based off of projected sales and whatnot. We can also include and configure this to include additional data points like lines of credit or loans. But at its core, looking at money coming in against money coming out and forecasting cash on hand projections from an operation perspective. You know Acumatica does a nice job in the inventory summary gi of giving you a look at this information that you're seeing here from you know, inventory on hand perspective and projecting out. But really what Data self adds on is the ability to see all of your items listed here. Have it sorted by the demand level. Is that a high demand, moderate demand, low demand and then just through using simple color coding. So red are my items that are going to be in a shortage based off of the time period that we have here. And then those items that are in black, those are going to be whose inventory items that are in excess. So very quickly, just from analyzing it on a color coding, I can understand that for this item here, I either need to create new production orders or purchase orders in order to meet my fulfillment needs on any sales orders that I have. Okay, so just one example of how you can leverage the inventory projection. We can also leverage or if you're more seasonal, we can have this built to handle your your seasonality requirements as well.

Okay.

From a services or those that are on the construction side of the house here we have a standard WIP reporting. And just like you've seen in some of the other templates here, it is going to be interactive. So this is where you can drill down into it. This WIP report can be configured however you would like, but this is where I could drill into this project, for example, and down below now I'm just going to see the various tasks that are associated with this project. Okay. Then I can even drill down further and say, all right, I'm going to drill into this task. And now I can see the transactions that are associated with this task here all in one screen.

Okay.

Additionally, within data self you're Going we're going to be able to leverage and help you on the resource management side of side of things. So being able to have visibility into a Gantt chart view broken down by your individual products or individual workers associated to a project and so forth.

Okay.

Lastly here I just want to highlight the the ability for what we call our 360 degree view dashboard. So this could be leveraged for how I'm showing you right now is more built out for C suite management but this could also be built for you know, department heads. So those that are in, you know, sales or purchasing operations, financials where ultimately what it does is it gives you in a single pane view multiple different dashboards. Okay. Or key performance indicators that you could further analyze. And then if you want to explore further at that point you could drill across into this detail on the left hand side here these are going to be your leading statistics. So these are more forecasts or projections. This center pane here are more of those lagging statistics. So looking at today and then a, you know, looking back x amount of time into the past, so maybe it's three, six 12 months into the past how our performance has been. And then on this right hand side here, this is where we're starting to pull in additional data sources. Okay. So within data self because we leverage an enterprise grade data warehouse, we can leverage not just acumatica data but we could leverage data from you know, additional data sources or third party data sources. So whether that's a point of sale, e commerce, Google Analytics, really we can work with any data source and have that incorporated with your acumatica data and have that rendered here in this 360 degree dashboard as well as some of our other templates if you'd like.

Okay.

But again really meant for you know, decision makers, department heads, C suite management to really have a good understanding as your of your company as a whole. Okay Johnny.

Yeah. Years ago we had a CFO that when, when, when she started the data self journey she set herself to build her own 360 degree view. You know she had access to all the business systems and one of the challenges was not only the ERP data but bringing data from the inventory, from the payroll and having this kind of visibility. And the interesting thing was like a 90% of the dashboard she was able to build it herself and she was not a technical kind of, you know, report creation kind of person. A lot of the widgets that she assembled in her 360 degree view dashboard was already part of the out of the box you know, she took something from sales, from one of the reports in plug in, plug in a widget. Then she took, you know, something from financial, something from receivable, something from inventory. She mostly needed some help, you know, bringing data from other data systems like you know, the payroll and whatnot. But it was fun to see, you know, when, when people understand the business, understand the, the where the challenge opportunities might lay and you start to build this 360 degree view dashboards that sometimes some people run daily or weekly or monthly or quarterly or yearly. It becomes amazing, empowering for them. One thing also Tom, that I think you should show quickly is how people usually use Data Self to distribute reports automatically to users. Sometimes users, sometimes people outside of the organization. Board members would show there that please.

Yep, it's not in this tab here there's a button that's normally it's the subscribe button. So this is where you're going to be able to subscribe or distribute this report to an individual or a set of individuals, a group of individuals at a frequency of your choosing. So whether that's daily, weekly, monthly. So we understand that you have members of management that they need to analyze or consume the data, but they may not be the ones that are in the weeds day to day actually analyzing this data day to day or building their own reports, but they still need to consume that data. So that's one way in which we can leverage, through subscriptions, sending those reports to a user or group of users to consume.

Yeah, yeah, and I'm just complimenting many clients that come to Data Self is because they have this kind of management report that before Data Self they were pretty much writing gis, exporting to Excel, doing manipulation Excel and then emailing people reports in Excel. It was manual, it was time consuming, it was error prone. Security is a concern if people email the reports to the wrong people. And what Tom just described is pretty much once you do the logic, the single version of the truth of these reports in the BI framework you can completely automate anything that is repetitive, can be automated by the reporting tool including to whom to send the reports to and when. Pretty much many of our clients they were spending dozens of hours per month for report compilation distribution. And that part of the work that is mechanical usually can be automated with the Data Cell framework.

Yeah, just to answer a quick question here from the Q and A, what formats are supported to with report send, PDF, Excel, CSV can even have them exported into PowerPoint, you know, for maybe a C, you know, for a presentation that you have those are some just off the top of my head that that are supported so the main ones PDF, Excel, cs, CSV and so forth.

Okay, all right.

Hand it back over to you, Johnny.

All right, let me share my screen now again. All right, just a few slides extra. So how does the technology works behind the scene to provide this kind of functionality, this kind of value? So before data self the challenge that we're talking about before, you know, limited KPI visibility, conflicting data, slow reports. The way we solve them is with a three step process. Step one we already kind of alluded for alluded to is the data warehousing primarily is to replicate the Acumatica data. If you have a schematic in the cloud, if you have a commatica on premises, no matter where the ecumatica is, we replicate the akumatica. Raw data in a SQL Server data warehouse of your choosing can be in our cloud. Your cloud on premises where the SQL is doesn't matter. You know, it's a place where there's going to be replicated. So step one is just replication. Step two is apply transformations to the to the data from Acumatic and other systems to be sure that when you're querying it, it's easier and faster to come up with your reports, dashboards and KPIs. We use ETL plus to do pretty much all of this process. ETL plus is a no code, low code, full code extraction transformation lobby tool, ETL extraction transformation learning tool and it's an easy way to deploy and maintain data warehouses without knowing data warehousing per se. So you don't need to know data warehousing to actually have an amazing data warehousing working for you. I'm not going to get too much into the weeds. I'm just going to give you this perspective that it solves a lot of the problems performance, automatic data transformations and defining the single version of truth in a SQL Server database of your choosing. Step two is pretty much designed for business users and we support a lot of different reporting tools. These three are the most popular. Tableau, Power BI and Excel. If you choose any of these three, we have an amazing way to make them even better. If you use other tools like Qlik domain whatnot, we can also help you. But Tableau and Power BI and Excel are the most popular in the Acumatica ecosystem. Super easy to use Tabloom Power BI compared to Excel. If you're a business person, you'll find that Tabloom, Power BI are usually easier, faster, more empowering in Excel but if you love Excel, you want that in Excel. Absolutely. We can make Excel reporting significantly more automated and faster. The last step is the templates. We have data warehouse templates, Tableau Power, BI and Excel templates that plug and play into your system. And this deployment usually takes about a day. And on day one, day two in this case, once the data is refreshed in your data self system, there are. If you go with the top tier set of templates, there are more than 8,000 reports dashboard, KPIs covering AP, AR, GL, you know, P and L, balance sheet, inventory, purchasing, sales, sales order, project, accounting, field service. There's a lot of CRM opportunities, CRM contact management. There's a lot of reports in Dashboard that will be ready on day one. You can just start using them in what Tom showed like a handful or so. They are part of the 8,000. You can customize them, you can delete them, you can recreate new ones from scratch. It's completely customizable. But your journey with data warehousing and tools like the bulletproof BI in Excel would start with a very robust starting point. At the end of the day with data self, decision makers will have a 360 degree view of the business much more easily. Maintaining the single version truth across all data silos from the data warehouse is usually more robust and scalable than using different systems to maintain those those those single versions of the truth. It's automated, streamlined. Reports are running seconds if it runs more than 10. If it takes longer than 10 seconds to run the report usually call us, we can check it out, turn the dials to be sure reports will run automatically in seconds. Anyhow, I'll move on. This is the ETL that I talked about that does the heavy lifting. Data warehousing again no code, low code, full code on the left side you can add your ecumatica using OData version 3, data version 4. Connect directly to the Medicare database if you have access to easy to add more data sources. Google Analytics, POS Systems, adp, MONOT in the center panel is what tables, DAC tables. You're mirroring from Akumatica into SQL database. You don't need to know any SQL. SQL will be built automatically for you for every table that you bring to the data warehouse. But if you know SQL you can even do more transformation using plain T SQL. One of the biggest advantage of data self when it comes to performance is the delta refresh. The first time they would take the data from Acumatica into your data warehouse and into Your BI solution. It might take a while if you have a lot of data, but after the first load we do what's called the upsert refresh, meaning we're only going to be refreshing on an ongoing basis, updating the rows that have changed since the last refresh and insert new rows into a table. So after the first refresh, the absurd will make the refresh process run super fast, usually in seconds. And that's part of why we can run reports in seconds no matter how much data you have. As I mentioned, deployment data cell for Akumatica usually takes about a day for the out of the box. And sometimes people spend more time doing testing, training, whatnot. But the out of the box comes alive pretty quickly. You have a pricing model that fits the budget of small, medium and large organizations. Usually the price of data itself is not a problem as long as the solution has a value. Usually our pricing model will fit the budget of your company because we have a pretty wide range of making it flexible and affordable. Because you're attending the promo, if you place an order in December, by the 15th you get 15% off our licenses. If you order by December 31st, you get 10% off. So if you're interested, you want to learn more, are you a good fit? How much going to cost you? You know, contact us or your var we can assess quickly and help you see if you can save some money by ordering quickly. With that in mind, we're going to open for questions. We can see that there are some questions being asked here. First question is we will be able to get a copy of the recording. Yes. In the next day or so we're going to be sending an email with a copy of recording and feel free to ask us more questions. Is there a managed service subscription for Data Self? So Data Self we offer managed subscriptions. So when you pay for Data self technology you're paying for in a SaaS model, unless you need to work with a different model. That's how we work about it is a subscription based framework and we can host your data. We work with AWS and Azure as the cloud providers or you can have your data self deployed in your framework, your private cloud framework on premises whatnot. So we have a very flexible architecture for deployment. Another question is how does this work if you're using Akumatica hosted environment pretty much is just to see how you have your akumatica and how you want to connect to data self. If you have behind your Akumatica behind a firewall because of, you know, let's say compliance requirements and you need to have everything, including Data Self behind your firewall. We can bring the whole stack behind your firewall. Most companies, they use part of our cloud framework, but our framework is like a Lego block. We have a bunch of Lego blocks that we can bring all of them assembled, you just use as needed. Or maybe you want to move a few of the Lego blocks into your framework. Or maybe you want to move all of the blocks into your framework. That's a discussion we probably should have one on one to see what your framework is and how our Lego blocks would meet your needs. There's one more question here. Last question I'm going to answer is from Jess. What is the difference between Netstock and Data Self for inventory planning forecasting? Good question, Jess. Netstock is an amazing inventory planning forecasting tool. If you have, you know, very sophisticated needs around those those reporting areas. Netstock, it's amazing. Typically Data Self is a better fit when people don't have overly sophisticated problems when they're doing a bunch of things in Excel and you need to automate that Excel manipulation. Inventory planning forecasting. We have an amazing framework to get people from out of out of Excel planning into a completely automated process for a bunch of things. So usually I tell people inventory planning is beyond my pay grade. I don't have enough knowledge to give you a specific assessment. If you're using that stock and is becoming expensive, give us a call. We can get one of our inventory planning experts to talk specifically about your needs, see how we can help if we can help and see if we can complement overlap Netstock. Some cases, some people came from Netstock to Data Self. Sometimes people go from Data Self to Netstock. So it's never an easy answer. Until we know your specific needs, we're going to wrap because we're running out of time. If you want to learn more about Data Self, you want to place an order, contact your Ecumenica board as soon as possible or us to discuss your needs. Will be here to help you make a good decision, a better decision, more informed decision. I hope you have enjoyed the webinar and I wish you a happy holiday season.