Author: Kartik Patel

Handling large amounts of data for business analytics can be challenging. To defeat data overload and manage those mountains of data, you need smart aggregation and consolidation of relevant data encompassing appropriate contextual information over a relevant period.

New BI tools have made this job easier with deep dive technology that enables simple analytics and allows you to leverage sophisticated tools, in an easy-to-use environment so that you can not only report on your data but you can get to those hidden nuggets of data that will have the most impact on your organization.

There is lot of noise about Visualization of data in BI space these days. Simple charts, complex charts (few of them can not be digested by many business users 🙂 ), tons of properties and configurations and much more….

Yes, a great work has been done in these area by most of the vendors in the BI marketplace today, and all decision makers are enthusiastic about this, and that enthusiasm is reflected in the growth of this BI visualization tools market.

So, one gets enthusiastic about it, becomes internal advocate for visualization in the organisation and the whole process of exploring visualization for business benefits starts…. But before you get to the next level, some pointers here…

ElegantJ BI is the flagship product of Elegant MicroWeb, a software product and application development company, located in Ahmedabad, India and specializing in Business Intelligence and Corporate Performance software.

Starting Point is the Data Influx

Traditional business intelligence tools and corporate performance management solutions typically use an IO-based processing technique that makes the compilation and analysis of data a slow process. It limits processing and speed from hardware resources that use extensive IO to read and write to and from the disk. This challenge can be frustrating for users and for IT staff because it reduces productivity and can overwhelm systems during peak periods.

BI solutions that utilize InMemory Computing are able to load data into memory, and because the process of memory read/write is very efficient and fast as compared to IO-based processing technique, it provides superior performance. However, InMemory Computing requires a lot of memory to serve large data sets and a large user base, and that is an expensive hardware proposition.