The way most organizations go about building a business intelligence application is to build a separate data warehouse from which the BI application can be used to query data. The problem with that approach, of course, is that it’s expensive to build and manage all those data warehouses.
With the advent of modern Web applications, however, the need to build dedicated data warehouses for BI applications is about to be sharply reduced. Looker is a BI application capable of working against multiple sources of Big Data in real time.
Keenan Rice, vice president of marketing for Looker Data Sciences, says that because Looker has its own real-time processing engine that display results directly in the browser, it is part of a new generation of Web applications that are more efficient and cost-effective to deploy.
Most recently, Looker added support for both Amazon Redshift and Relational Data Sources (RDS) as data sources, which Rice says are becoming more popular as part of a broader acceptance of Amazon Web Services (AWS) in the enterprise.
After just raising another $16 million in financing, Rice says a Web-centric approach to BI will fundamentally change the economics of BI applications in a way that should make it significantly more affordable to deploy these applications across the enterprise.
Investing in Big Data is one thing. But finding a way to turn all that data into information that someone can use is quite another. The good news is that a new generation of Web applications that run directly inside a browser is finally poised to solve that problem.