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April - 2015 - issue > CXO INSIGHT

Unified Data to Define Value of the Cloud

Manish Gupta, Chief Marketing Officer, Liaison Technolgies
Friday, April 3, 2015
Manish Gupta, Chief Marketing Officer, Liaison Technolgies
IDC now forecasts that we will generate 44 zettabytes of data by 2020. That number is hard for most people to even comprehend. To put that in perspective, a single zettabyte equates to 36 million years of HD video.

With the amount of information capture on the rise, cloud is more important than ever as it will be where these massive amounts of data will reside and flow through. This data needs to be organized - through data integration and data management - in order to produce valid results for advancement and efficiency gains.This needaffects all industries and touches every business. It is truly universal.

Today big data is pulling businesses in conflicting directions, with data technologies and tools fragmenting just when they need to converge. The enthusiastic adoption of innovative cloud-based applications coupled with the need to sustain legacy infrastructure further strains the data model. Finally, the need for streamlined processing and management of data is further exasperated by the insatiable drive for business insight. Companies need a data-centric approach that flexibly delivers broad perspectives drawn from a synthesis of traditional structured data and a rapidly expanding universe of free-form data.

So how did we get to this place? Enterprise data technologies evolved in a much simpler era, with separate disciplines emerging to address the basic challenges of data integration, data management, and data analytics. The actionable business intelligence comes from the analytics, but the analytics are only as good as the data normalized and delivered by the integration and management solutions.

A very old computer aphorism is still quite apt: Garbage in, garbage out. As enterprises struggle to cope with the growing data deluge, they need to optimize the data feeding their analytics engine, and this means taking a fresh look at how data is integrated and managed.

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