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The big shift to Big Data: a daunting undertaking

By Shannon Williams
Thu 11 Feb 2016
FYI, this story is more than a year old

Businesses who are transitioning to big data environments need to consider what a daunting undertaking the change can be.

Experts at CenturyLink says organisations need the right combination of analysis and correlation tools to make the change comfortably.

The company says that while big data can lead to accelerated insight, improved decision-making, and better products and services, the transition to putting data-driven insight at the centre of a business is a big task.

“Big data is called big for a reason,” states Martin Hooper, big data & predictive analysis expert, Asia Pacific, CenturyLink.

“It involves huge volumes of data and requires extensive analytics capabilities to make sense of it all,” he explains.

“There are a number of ways companies can gain these capabilities and adopt a big data culture.”

Hooper says bringing the technology infrastructure and know-how needed to embark on a data-centric journey in-house is often beyond the means of many businesses.

“This is especially true in the case of processing power, of which big data analytics requires an enormous amount,” Hooper says. “Importantly, there is an increasing array of outsourced services that can fill this role. “

From external data center storage space and server instances to fully-blown managed outsourced analytics platforms, businesses can now obtain a variety of services that fit the needs for a data-driven future, says Hooper.

“State-of-the-art big data and advanced analytics capabilities provided as a managed service can enable data scientists, IT professionals and developers to deliver innovative and monetise-able insights thereby allowing data to become the source of truth and competitive advantage,” he explains.

“Once the systems are in place and the insights from data start to flow through the business, it is only a matter of time before the organisation understands its value and the internal culture begins to become more data-centric,” Hooper says.

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