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Build Your Data Governance Career

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  1. About this course

    6 Easy Steps to Win at Data Governance e-Book
  2. Who this course is designed to help
  3. The basics of data in your organisation
    What is data and why care for it?
    7 Topics
  4. Why data matters
    What "data-driven" means and how to use it to excite stakeholders
    6 Topics
    1 Quiz
  5. Why your organisation struggles to become data-driven
  6. What does bad data look like, and how do you find it?
    How to identify bad data and identify its risks and costs
    3 Topics
    2 Quizzes
  7. How to fix bad data with good governance
    Defining what good data means
  8. The importance of business process data touch points
  9. What is governance anyway?
  10. Where governance and data collide
  11. Kicking off your data governance initiative
    Data Governance explained - 6 easy steps to win at data governance
    6 Topics
    1 Quiz
  12. What are the basic features of a Data Governance Framework?
    8 Topics
    1 Quiz
  13. Five critical data governance deliverables
  14. How to Implement Data Governance in your firm
    Let's start Governing Data - the Cognopia Methodology
    14 Topics
  15. Data Governance case studies - winning with data governance
    9 ways data leaders are winning with Data Governance
    1 Quiz
Lesson Progress
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Unstructured data vs structured data?

What’s the difference between structured and unstructured data? If we look at structured data – that which you’re most familiar with, it’ll be similar to that of an excel spreadsheet. You’ll have columns and rows. Most of us are very used to that and we can navigate it relatively easily. The metadata in the column headings also helps us understand the content that sits within the rows.

Spreadsheet courtesy of our business glossary – this is an example of structured data.

Unstructured data are things that are more like images, audio or text where there’s no structure there that allows us to interpret the data easily and we have to use different techniques in order to unlock value from it.

One of these is a visual of unstructured data and the other is a visual of structured data – no points for getting this right!

Healthcare again

The health care industry is a great example of why we need to do more with unstructured data. It’s estimated that around 80% of the medical record data that is captured about us is unstructured – things like handwritten physician’s notes, scans and the various different medical images that we might be getting in X-rays. Google has given a great example of how you can use this kind of data to drive better outcomes for, in this case, patients. They took some mammograms and other scans that looked at that medical images and using AI with it, they were able to detect breast cancers more quickly, more accurately, and with fewer false positives than trained medical doctors can do.

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