Hey there. Welcome to What's New in Erwin Data Modeler 21 R1, the latest release of our industry leading data modeling solution. For those of you that are not aware, data transformation is well underway. We just recently did a piece of research on the state of data governance and had some really eye opening figures here that I thought were a great way to sort of open up this topic. First off, we always talk about what organizations need from their data, how they perceive their data, the things they're trying to do with their data, but this really kind of breaks it down into a great set of numbers, that really show how important data is to the organization.
So when you look at the question, please rate your level of agreement with these following statements. 84% of people are realizing that data represents the best opportunity for their organization to be competitive and to be successful, moving forward in this dynamic business environment in which we live. And 75% of them think that if they don't get their data house in order, that they are at risk of being disrupted by the competition who are doing very much the same thing. And when you look at it, to make the most of their data, they're realizing that they need to improve all aspects of their data capability throughout the entire lifecycle, Devops their ability to understand and leverage data but also their ability to protect that data as well.
Now if we look at the state of data today in organizations, in our reference, an IDC study as well as Gartner studies here, where we see that 95% of organizations have at least six different types of data, that they're managing across 10 different types of data management technologies. And that across a wide range of organizations and industries. So those numbers go up as you get into large, complex organizations. And 94% of them are doing that across some sort of hybrid environment, where they have some amount of on premise solutions, as well as solutions out in those cloud environments. And sadly, 85% of the time that their data native workers are spending is still on finding and preparing and understanding data and 15% of that in terms of actually delivering value to the business. And then finally Gartner, recognizes that 50% of the organizations out there, lack the sufficient AI and data literacy skills to really fully achieve the maximum business value that they want from their data. So this is the environment in which we live in. And this is in the environment in which we need to find solutions, that are going to help us again across all aspects of our data capability throughout the entire lifecycle, making sure that we don't just have things like governance in place but that the mechanisms that create and define and deploy new data can handle those that wide ranging environment and all of the capabilities behind making the most of that environment.
So with that, we'll take a look at Erwin data modeler. As I said, it's an industry standard, industry leading solution, where we have all of the capabilities that you need from a data modeling perspective, so that you can get the most and optimize your database design, documentation, metadata management, Data Intelligence and governance. This is a combination of tools that starts with our data modeling tool, where you can do conceptual logical on physical models for all of the databases out there including big data, NoSQL, cloud databases. It comes enabled repository based addition that allows the data modelers to collaborate very, very effectively together and integrate well into an agile approach to development and DevOps, that's called our work group addition. We have a web portal that allows you to publish all of the good work that they do in this environment, out to all of the stakeholders that would want to be able to see and understand that. And then, of course, we have other tools that allow us to get into a deep understanding of the structures and metadata behind all of the major common off the shelf solutions like SAP, all of the Oracle solutions, Salesforce, Microsoft Dynamics. So all in one solution, you have your capability to start visually modeling, documenting, and then actually deploying data sources out into your environment using this solution.
So getting to what's New in 21R1, is a fairly major release where we've brought some significant capabilities to really expand the reach of Erwin data modeler across your organization. Very, very important, is our new native modeling and engineering support for NoSQL databases coachbase, MongoDB, Cassandra, as well as JSON and AVRO data sources. So now you can model those in the same solution as you do all of your traditional relational databases, your big data sources, things like that. We've included data vault 2.0 modeling support, for data warehouse modernization and agility. So data vault is an approach to creating a much more agile aggregation layer, for all of your data to support all of your BI in analytics. Built into the tool, now we have more guided denormalization that helps you move from the design paradigm of say a relational or entity relational diagram, out into document based databases, because it is very much a different type of modeling and the tool will support you moving between those design paradigms.
We've updated support for some of the traditional databases that we have there. So now support for the latest versions of Oracle, MS SQL, SQL server as well as Microsoft Azure environment with Azure SQL and Azure SQL synapse. We've included more JDBC - connectivity for a number of different solutions, to have more capability and easier access to those when they're sitting out in the cloud. We've really done a great job of enhancing the interface to administer that collaborative work group data modeling governance solution, that's
20:32