Data Silos Consolidation - DataSelf / Tableau

Hi, I'm Johnny Girardi. Let's talk about data silos and decision making. Well, what are data silos? Let me give you some examples. If you have a computer system like an ERP system, sometimes even inside of the ERP system, you might have several data silos. Let's say that you want to see a cash flow projection that needs to bring data from your open receivables, open payables and cash on hand. Today in an ERP system, typically those three pieces of data come from different transaction tables and they can be considered data silos inside of the ERP system because bringing them together sometimes is not so straightforward. Overall, organizations nowadays they have several data silos. They usually have an ERP or enterprise resource planning system. They might have a CRM system for customer relationship management. They might have point of sales, independent payroll systems, marketing tools. They might have a multi company. You know, many organizations have acquired other organizations over time and they have different systems and you need to bring and consolidate all the financials and all the transactions together. You might have social media and other data sources. And quite often what organizations want to do is they want to have a consolidated view out of all these data silos. So for management they want to see all the data together. Like in this example, we have a 360 degree view of the business. It's a dashboard that brings, let's say cash flow projection on the top left corner, orders to ship, opportunities from CRM, website, visits from Google Analytics, financial information from the ERP system, inventory information from the inventory system. No matter where the data is being captured, decision makers need to see information easily across all of these data silos. Now how organizations typically go about bringing the data together, a very popular way is manually. In Excel is one of the most popular ways that I've seen. Over there people just, you know, export data from different systems, different data silos, they manually connect the data and they make it happen and it works. However, for many organizations, the manual approach is pretty slow. I mean usually takes hours, sometimes days and even weeks. For the techies, the consultants or the, the people putting the reports together to assemble the data, it's error prone. You know, every time you have people doing things, sometimes people make mistakes and then decisions are made based on incorrect data and usually proves to be expensive in the long run. You know, every month or every quarter people have to go through those procedures and fix the errors and double check to be everything is being correct. So manual approach is very popular. But again it's slow, error prone and expensive. The alternative is doing that automatically. There are many tools out there that can actually consolidate the data silos, make things completely automatic, fast, automatic and reliable. Once you tell the computer what to do and in what frequency, the computer will do it and there's usually no problems, no mistakes. I'm going to be talking now about how Data Self does the automatic, fast and reliable approach. I'm visiting dataself.com if you come to solutions and click Architecture, you'll see this page. This page shows the architecture of Data Self analytics in a nutshell. In the far left we have the data sources, meaning the organization's, let's say ERP system, CRM, Google Analytics point of sale system payroll. Any of the data silos will be represented by these source databases. What we add is first of all a data warehouse framework powered by SQL Server. This data warehouse framework is being designed to easily and quickly bring data together. From every single data source we can break the silos and combine the data. Like when I mentioned about the cash flow analysis, we can easily bring receivables, payables and cash on hand today all together. But of course being a data warehouse we can bring any data source inside of it and combine it to have a 360° of the business. This is a framework so some organizations have a single data warehouse to do the whole consolidation. Some organizations we use a data mart approach, meaning we can have a little data warehouse or a simplified data warehouse for each data source to focus on that particular data silo characteristics. And eventually we might have an additional data warehouse to bring all the data together. Those are more tacky discussions that we have with organizations. But anyhow we do have an enterprise level data warehouse framework to really tackle in an automatic and reliable way data source or data service consolidation. Then we use an analytics platform. By default we use Tableau, but we also have support to Excel and Power bi. And the idea here is to give a user interface that is easy, that is fast and that empowers decision makers anytime, anywhere, using any kind of device like a computer, a web browser or mobile device to access the reports and dashboards quickly and easily. If you do have any of these ERP and CRM systems, I have great news. Our framework has been already pre mapped out of the box to these systems. So pretty much in a matter of hours we'll deploy the solution that will cover a lot of reports and dashboards needs for organizations that use such ERP and CRM Systems. In the 13 years we've been in business we have built more than 5,000 reports, dashboards and KPIs, looking at many different metrics in business areas such as sales, inventory, purchasing, financials, payables, receivables, services, CRM, opportunity, Tech support. There's a lot of things that organizations might need to analyze out of their data silos that we already have covered out of the box. So instead of taking weeks, months and years to build and consolidate your data silos, we have a solution that plugs and play and get you hitting the ground running in hours, not in a much longer time. If you want to learn more about our approach or overall how data consolidation can be done, you can find here my contact information as well as website. Thanks for watching.