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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 3 of 15
In Progress

What is data and why care for it?

What’s the big deal about data?

So why do we need to know about data and why do we need to know about the types of data?

Fundamentally, if we’re going to go and govern anything, we’ve got to understand it. This is a quick primer on 6 main types that you’re going to see as you go through the rest of this course.

So data is really just our way of recording things that we’ve observed in the real world. Types of data that you often think of are things like master data. That is a way of us describing the most important relationships our business has, things like customers, products, employees. And by defining exactly what we mean by those key business concepts, we’re able to capture the right information so that we can run our business properly. This gives context to the next type of data, which is transactional data.

Now, transactional data describes events. The way to think about transactional data can be whenever we make a sale, whenever we purchase something from a supplier, hire a new person and onboard them. These are all transactions, events that have occurred and we capture information about them so that we can service those different customers.

Metadata allows us to describe what that data means. So if I find a number like 97503525 and I don’t know what that means, it’s a number. It means nothing. I need to look for data to describe it. I’ll go and look in the column and the column header tells me it’s a phone number. So that allows me to use that data and to evaluate whether it’s correct or not.

Reference data is simply data that we go to whenever we want to look something up. So it doesn’t change very frequently, if at all. And it could be things like country codes, currency codes, ISO codes, information that we refer to when needed to perform some function.

Big data, of course, is very important and in vogue right now, but it’s really just about compiling lots and lots of data, putting it all in one place and then looking for insights that you might not be able to find if you had smaller amounts of data.

And then last but not least, unstructured data. So everybody’s very used to working with columns, rows and information of that nature – in a structured format. Unstructured data is more like text that might be in an email or perhaps images. Fortunately, we can use various techniques to analyse that and improve customer experience. For example, we might find that customers are getting frustrated and annoyed just by scanning through emails they’re sending to our support team. So it’s a very important type of data that’s well worth knowing about for anybody trying to manage their organisation.

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