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IDC: Investments in Big Data Will Support Both Cost Reduction and Growth Objectives

By Alys Woodward, Research Director, Worldwide Advanced & Predictive Analytics, European Business Analytics, European Social Business

(PresseBox) (Frankfurt am Main, ) Top Line: IDC forecasts the Big Data market for technology and services will grow by 24.6% in Western Europe over the next 5 years

According to IDC's Digital Universe study 2014, global data volumes are sized at 4.4 ZB in 2013, with exponential growth to 44 ZB by 2020. Western European organizations are catching up rapidly with their North American peers in terms of analytical maturity despite later adoption due to smaller datasets, a challenging economy, skills shortages and greater privacy concerns.

IDC has just published its Big Data Technology and Services report for Western Europe with current market sizing and a forecast until 2018 by country and segment. IDC expects the Big Data technology and services market in Western Europe to grow from $2.3 billion in 2013 to $2.9 billion by the end of 2014 and $6.8 billion in 2018, representing a compound annual growth rate (CAGR) of 24.6%.

IDC research indicates that in 2014, European ICT buyers saw growth-related priorities (growth, acquisitions, and product innovation) as significantly more important than in 2013. Inward, optimization-related priorities (product and services quality, long-term cost reduction and optimization) were still at the top of the list, but as many European economies move away from recession growth is back on the agenda. The good news is that Big Data systems can support both: from finding places to optimize internal processes and find ways to reduce costs, to identifying new customers, products and market segments.

Bottom Line for ICT Buyers:

1. Big Data is a very broad umbrella term; one size (technology) does not fit all (requirements). Different workloads, data types, and user types are best served by technology that is purpose built for a specific use case to reflect the right mix of data types, latency levels, storage needs, and business user interactivity. Organizations should start by focusing on what business outcome they need from Big Data, then look at which specific technologies and service resources they require.

2. Gaining value from information is a journey; while successful use of information has a snowball effect in that it encourages further use of information, an organization that is struggling to find value from information may see its analytics projects stagnate. Focus on where your organization will find measurable business value. Customer-based projects are a good place to start, because there is often a lot of measurement already in place around customer loyalty, basket size or order size, or revenue per customer, which makes it relatively easy to measure improvements from better data.

3. Some Big Data use cases are about exploring data and understanding its value, not just adding data to existing operational processes. Exploration-based use of Big Data can deliver great value but this value may not be monetary in the first instance. Focus on what you want to find out from the data, is it buying patterns, correlations, or causal factors to drive specific behaviour? Make sure these projects are measured based on achieving project goals rather than with vague expectations that they will deliver financial benefits, at least in the near term. All value is not monetary.

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