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Business Intelligence 2.0 by Krish Khambadkone
Krish Khambadkone is a Client Architect at Infogain with over 18 years of experience in architecting and building systems. He is currently focused on Middleware and SOA integration both at the Strategic and Tactical levels, mainly in the areas of SOA evangelization and governance.
A few topics have been crying for attention lately and chief among them is Cloud computing. This is a very interesting area and is only going to gain momentum and grab a lot of headlines in the coming weeks and months. |
The face of Business Intelligence has changed dramatically since the advent of Web 2.0 technologies and the proliferation of the NOSQL movement. Some web sites now generate Gigabytes of data every day. Some have grown into the Terabyte and even the Petabyte territories. Having to deal with such enormous amounts of information has led to some radical rethinking in the way data is stored, mined and used. Hence the advent of virtualized storage infrastructures like Hadoop, BigTable and Cassandra which are essentially algorithm driven virtualization environments for storing these oceans of information. This now falls under a realm that is called “Big Data”.
So, how does this relate to Business Intelligence? While companies were in possession of such vast amounts of data, there was always a need for turning this data into useful information and useful information into actionable intelligence. The traditional mechanisms that were in place for gaining such intelligence were Transactional Data Warehouses, Master Data Hubs and Business Intelligence Tools to slice and dice information contained in these data silos.
One of the major challenges has always been the scattered and distributed nature of information within organizations. This was further compounded by M&As where additional such repositories were inherited. Maintaining Data Integrity was always an issue. The advent of Data Cleansing tools like Trillium and Hyperion only helped to a certain extent. While the goal was to gain meaningful intelligence out of this data, all that could be obtained was information. The tried and tested methodology was to run BI tools like Cognos, Business Objects or Oracle BI against these data stores and obtain reports. However, with today’s real-time and agile internet, these reports are becoming obsolete before they even hit the reviewer’s desk.
In came real-time analytics. The future of BI—which I am calling BI 2.0—will be increasingly driven by real-time analytics acting upon non-traditional data stores such as these virtualized environments. The BI landscape has undergone a sea change. In this article we will talk about the various ways in which BI is being perceived and handled in the current IT landscape.
If Traditional BI = Data Warehouse + Reporting Tools
Then BI 2.0 = (Past + Present) Data/Analytics + Future Business Analytics + Reporting Tools.
I have used this simple equation by way of demonstration: BI 2.0 is all about studying and analyzing Past, Present and Future trends within Transactional data (as opposed to Master Data) using archived and real-time data feeds and then turning this data into knowledge for stronger decision-making.
Given today’s requisite business agility, the true and trusted mechanisms of the DW-driven mode of acquiring BI is now considered almost prehistoric. This is not to say that these technologies are obsolete; they certainly are not. They do have their uses. But, this model is being increasingly supplanted by more agile and real-time mechanisms like Business Activity Monitoring (BAM) and Complex Event Processing (CEP).
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Posted by Krish Khambadkone on 18 April, 2010
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