UPDATED 11:23 EST / MARCH 03 2011

Big Data Buries Old School of Thoughts

Entering the age of Big Data is like welcoming a new chapter. Organic. Inevitable. Fresh. Hopeful. While data warehouses claimed so much attention, this mode of data management is already outdated, especially when volume of data passing through enterprises shows no sign of slowing down.

Bert Latamore, analyst and Wikibon contributor, clearly knows the disparity of the glory days compared to the present day, saying, “For big data things are different. Traditional DW/BI is largely incremental on a month-to-month basis – i.e. 10% more data at month’s end. Big data is different – it’s operating on huge data sets every time an analysis is done.

“The mindset is often very intense short project windows, lots of experimentation, more likely to outsource to the cloud/services and organizationally it’s outside the traditional DW/BI world (while the  traditional group will try to claim it because some of the data exists inside the DW today). Often big data projects won’t end up in the data group because the data are so dispersed.”

The incessant growth of data in every organization now requires system tweaking around processes and frameworks to structure and manage data chiefly to benefit the business.  Biggies like IBM went out of their way and introduced the concept enveloping Big Data to urban spaced via City Forward.  The company also encouraged industry frontiers to engage in differentiating big and small data as a starting point of adaptation and adoption.

While Big Data presents tough hurdles for management, it also presents new opportunities for vendors to explore, and thrive. Adoption drivers for Hadoop and NoSQL databases are now grabbing attention, indicating a growing need around open cloud tools for large scale data management.

Indeed, Big Data is not just for Google anymore, nor it is the usual extension of the traditional data warehouse, which is now akin to the dinosaur age. Even if data warehousing carries on, it will just be continuously be disrupted by appliances, and consolidated through the stack, on aspects that include computing, storage, hypervisor, DB, Middleware and sometimes the app itself—a hot topic which was extensively discussed during the recent Wikibon Peer Incite research conference.


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