The Big Data Enterprise

Data volume in the enterprise is set to grow fifty times year-over-year through to 2020, with new data sources encompassing social media, mobile, web and machine generated data.

These are presenting both a challenge and opportunity for enterprises across the world.

While organisations see potential to enhance business growth and decision-making, big data is often difficult to collect, analyse and interpret to gain valuable insights.

A recent study by Forrester Research says that most companies analyse a mere 12% of the data they have. “Repressive” data silos and a lack of analytics tools and skills are two reasons why companies ignore the remaining 88% of their data.

Forrester maintains that “it’s often impossible to judge what data is valuable and what isn’t”, and that “data that might seem completely irrelevant to your business now, such as mobile GPS data, might be a gold mine in the future.”

As enterprises realise the value of big data, jobs in this area are growing. Demand for big data talent has risen by nearly 50% according to surveys, and is set to rise even more in the coming decade.

Implementing a Big Data Strategy

According to Gartner, a staggering 85% of Fortune 500 companies will be unable to exploit big data for competitive advantage next year. While there is burgeoning interest in this area, there is what Gartner has termed “an information strategy gap” which introduces the risk of over- and under-investing in big data.

Gartner maintains that five business strategy essentials are important to implementing big data. These include:

  • Acknowledging that big data initiatives are unique – big data initiatives differ from other business and IT initiatives and are a game-changer owing to their “unprecedented agility”, “targeted personalisation that generates goodwill and revenue boosts” and “previously impossible product and process innovations.”
  • Generating big ideas for big data – asking key questions that were never before possible and changing existing business processes to adapt to large quantities of data are pivotal in the implementation of a robust big data strategy.
  • Identifying new and valuable data sources – within the enterprise environment there are an array of data sources. Gartner has identified five distinct types of sources: operational data, dark data, commercial data, public data and social media data.
  • Belief in big data from the business leadership and boardroom – successful big data initiatives need boardroom buy-in and an intimate involvement from business leaders.
  • Becoming pragmatic about investment – according to Gartner, enterprises need to be “pragmatic about information-related investments, considering the formal costs of acquiring, administering and applying information asserts versus their economic benefits.”

Join Whitehall Media for its 5th Big Data Analytics conference on 19 June 2014 at the Hotel Russell in central London. Click here to register your place to attend.

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