An agile expose of enterprise data using Data Virtualization as a Platform

Today’s financial organizations are completely complex trading environments & relaying absolutely on business intelligence systems for their strategic business decisions as well as to help gain their competitive advantage in the emerging markets. Few hours of downtime or delay in extracting & transforming the data causes the huge impact.

The pressure from the stakeholders & business team to the IT team is such that they do not want the ETL tool to take time to extract, transform & load it to the Datawarehose & the BI reports to fetch the data from the Datawarehose. Which is totally a time consuming activity. All they need is just in time in one click. This is not the complete replacement of the Data Integration but the complementary solution & agile way of exposing the enterprise data. But most of the time it is seen as Data Marts Vs Virtual Databases. I Could say, Data Virtualization is a disruption in the data science & it’s going to be the next wave in entire data technology.

Virtual Databases are built with views on top of views in it (Base Views, Derived Views etc). Virtual Databases uses the VQL queries, Syntax & structure similarly like SQL. Each virtual database will be having it’s VQL shell –a command prompt where we can execute the VQL statements on the virtual database to query the data. We can also export the individual view structure & entire database as .vql file.

From the organization’s perspective, It is not going to be the big burden & huge transformation to move their critical BI DataMarts from Data Integration to Data Virtualization, It just a mindset change & architectural decision. From the Developer’s perspective, today’s DV tools are more user friendly, Developers can create data sources & export the table structure from the underlying database to virtual database as virtual tables or views, They can also build their custom views & can do the below operations to create their business logic.

Developers can also use the below functions to handle & covert the data to their respective data types.

Below are the major advantages of the DV tools & platforms.

1.    Integrated MetaData lineage capability.
2.    Web Service Deploy.
3.    Abstraction of underlying data structures.
4.    Single consolidated unified view of enterprise data.
5.    Faster data access from virtual database in memory.

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