data intelligence illustration

Given our focus on data as a key component of digital transformation, we have collected a series of posts designed to increase data intelligence. Since understanding about data is still not so wide spread and the field is evolving, the idea here was to start developing a common language around data so that business people, data scientists and technologists can work together more efficiently as part of the overall transformation of the business.

Asking the right questions

Data intelligence starts with asking questions like:

  • What do I want to know?
  • How will data help me answer the first question?
  • What kind of data do I need to answer the question?
  • How much am I willing to pay, not only in money but in time and effort to get the answer to my question?
  • Is it worth making the technology and business changes needed to get the right data in the right place and time to answer the question? (The answer to this question may surprise you)

Starting from these broad questions, senior leaders can begin to make more intelligent decisions about the role data should play in their organisation and how much they should invest in improving the organisation’s data intelligence.

Data intelligence and ecosystems

Another key aspect of data intelligence is the recognition that data is more than just technology, algorithms and pie charts. In order for companies to get the most out of their data, they need create an ecosystem that supports it. This ecosystem includes an enterprise architecture, business processes and strategic attention on the value of data at all points in its life cycle, from creation to insight.

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