Analytics Best Practices: The Analytical Sandbox

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Analytics Best Practices: The Analytical Sandbox

blog_sandboxSo this situation sounds familiar, and you are wondering if you need an analytical sandbox…

The goal of an analytical sandbox is to enable business people to  conduct discovery and situational analytics.  This platform is targeted for business analysts and “power users” who are the go-to people that the entire business group uses when they need reporting help and answers. This target group is the analytical elite of the enterprise.

The analytical elite have been building their own makeshift sandboxes, referred to as data shadow systems or spreadmarts. The intent of the analytical sandbox is to provide the dedicated storage, tools and processing resources to eliminate the need for the data shadow systems.

The key components of an analytical sandbox are:

  • Business analytics – contains the self-service BI tools used for discovery and situational analysis
  • Analytical sandbox platform – provides the processing, storage and networking capabilities
  • Data access and delivery – enables the gathering and integration of  data from a variety of data sources and data types
  • Data sources – sourced from within and outside the enterprise, it can be big data (unstructured) and transactional data (structured); e.g., extracts, feeds, messages, spreadsheets and documents.

For more on analytical sandboxes, including architecture design principles and options, see the white paper Analytics Best Practices: The Analytical Sandbox

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