Business Intelligence and analytics: Conquering Big Data

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The rapid expansion of business data poses challenges for companies across Europe, especially in the UK, per Aberdeen Group’s research report Business Analytics in the UK: Transforming Data into Business Insight .

However, these headaches pale in comparison to the potential business value that new, complex, and varied data sets can deliver to the enterprise. Creating this value involves three essential steps:

 - Identifying the data sources that can contribute to an organisation’s data repository
 - Building a strong, scalable data management foundation
 - Layering new analytic tools on top of the data to provide new insights.

Aberdeen’s January 2012 research study on Data Management for BI included 99 organisations with at least five terabytes of current, active business data, and, that had implemented an official, enterprise-wide Big Data initiative.

The strategies and tools being used paint a picture of the current data management requirements and emerging solutions in the market.

Interestingly, the most popular data source used in Big Data initiatives has the smallest data footprint.

Related:

Structured data in relational databases, such as transactional information, while growing at over 36 per cent year-over-year, shows nowhere near the growth of other, internet-based data sources.

However, 93 per cent of organisations reported that structured data is important or very important to their overall Big Data initiative (see Figure 1).

This information forms the core of their projects, with other data sources used to supplement or add perspective to this reliable repository of sales, customer or product information.

Other popular data sources include the collection of internet-use and social media behavior statistics, which provide insights to consumer behaviour and the success of products or services.

Also, as wireless bandwidth speeds now fully support streaming video and audio, consumers now access more information in more formats than ever before.