Technology

Decision Support Application Development Platform

Data governance ensures data accuracy, consistency, transparency and security. It should not be limited to the data warehouse.

“There is an error in the spreadsheet!” We have all experienced embarrassment, frustration or concern in learning that the data that we are using to make decisions is unreliable. What may be more damaging is the inappropriate use of secure data that once downloaded to users desktops is ungoverned. With the advances in mobile computing, data governance becomes more critical.

eiVia extends the data governance of the data warehouse architecture by minimizing the data files that are downloaded and managed on users PC. In the process, eiVia improves secure user collaboration and provides a more powerful multidimensional modeling engine. eiVia easily supports large collaborating user communities analyzing hundreds of millions of rows of data.

eiVia is not a spreadsheet in the traditional sense. eiVia does not store data in spreadsheet cells. Large data files are not downloaded to users’ desktops. eiVia does not store formulas in cells of the Spreadsheet. Formulas are part of a metadata layer.

What’s left is a browser accessible lightweight app that mimics the familiar row and column interface. Users access this virtual spreadsheet with nothing more than a URL and password.

Of course, users are no longer sending spreadsheets as email attachments. Users are essentially exchanging a URL and only authorized recipients of this virtual spreadsheet can view and interact with the data.

eiVia relies on a dual data caching method for performance. The data warehouse or data mart is the single consolidation point for data that is originated by users. To support interactive analysis, eiVia creates a temporary shared cache (file system) and a private instance of this cache (in-memory) is created when a user begins an analysis session. These caches are temporary workspaces. Data entered by users or created by the application’s analytic models are written back (added) to the data warehouse or data mart when the data must persist. By writing back to the data warehouse, critical planning benchmarks are available to BI reporting applications.

Decision Support for Every Decision