6 Easy Steps to Win at Data Governance
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About this course
6 Easy Steps to Win at Data Governance e-Book -
Who this course is designed to help
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The basics of data in your organisationWhat is data and why care for it?7 Topics
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Why data mattersWhat "data-driven" means and how to use it to excite stakeholders6 Topics|1 Quiz
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Why your organisation struggles to become data-driven
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What does bad data look like, and how do you find it?How to identify bad data and identify its risks and costs3 Topics|2 Quizzes
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How to fix bad data with good governanceDefining what good data means
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The importance of business process data touch points
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What is governance anyway?
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Where governance and data collide
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Kicking off your data governance initiativeData Governance explained - 6 easy steps to win at data governance6 Topics|1 Quiz
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What are the basic features of a Data Governance Framework?8 Topics|1 Quiz
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Common Data Governance Misconceptions
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Why are you kicking data governance off in your firm?
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Data Governance vs Data Management
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Choosing a Data Governance Framework - Cognopia vs DAMA vs DCAM
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Establishing Data Governance is a lot like trying to win the World Cup
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Data Governance vs Data Quality
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What common errors should you avoid when setting up a Data Governance Framework?
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Data Governance is NOT a project
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Common Data Governance Misconceptions
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Five critical data governance deliverables
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How to Implement Data Governance in your firmLet's start Governing Data - the Cognopia Methodology14 Topics
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Establish the Scope of Data Governance
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Evaluate your environment
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Choosing your Operating Model
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Translate Data Governance Principles into Practice
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Building the Data Governance Team - an overview
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The Data Owner
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The Business Data Steward
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The Technical Data Steward
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The Data Custodian
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Organising the Data Governance Roles
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Define your Data Governance Forums
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Communicating the change
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Understand end user's data struggles to create better communications
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Sustain and Improve
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Establish the Scope of Data Governance
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Data Governance case studies - winning with data governance9 ways data leaders are winning with Data Governance1 Quiz
Participants 216
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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