Data Strategy

A guide

Data is the new gold!

Companies have access to a torrent of data, either from their own proprietary products, customers or from a range of open APIs meaning that the potential for data analysis to provide strategic (and tactical) insights is significant. Many businesses around the world are turning to ‘big data’ as a strategic asset to drive business value, and are reaping the rewards. This has been the reserve of larger enterprises historically, but with a range of flexible data system components being made available a data strategy is in reach of all businesses, meaning that smaller and medium sized business can and should be capitalising on on their most important asset to drive business growth.

However, most business don’t have the resources to design and build a data strategy, others simply don’t know they need a data strategy. Therefore very few businesses have a robust approach to data. This means that insights are either missed or take a long time to uncover making it genuinely impossible to be data driven in business decision making.

Data strategies should therefore be strategic priorities for all businesses of all sizes. Businesses need a strategy that enables data analysis to occur across an organisation, performed by all business users and not only those in highly specialised roles.

The end result of a data strategy is the ability to perform insight analysis and gain business intelligence, which means you have to ensure you have your data framework and database management system setup correctly. But with a well designed and implemented data strategy businesses can fuel their growth with insights about their product, customers, advertising channels or the market in general.

Below is a list of a core components when thinking about the design of a data strategy:

  • Data Identity
  • Data Storage
  • Data modelling and analytical formats
  • Data visualisation
  • Data transformation
  • Data enrichment
  • Insight Analysis

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