6 Easy Steps to Win at Data Governance
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About this course6 Easy Steps to Win at Data Governance e-Book
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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
Big data introduction
Instructor’s edit: On the origins of “Big Data”
So it turns out that my association of the term “Big Data” with Doug Laney is not entirely accurate. As I was being corrected on this point, I thought it was worthwhile doing some digging. Here’s an article by the New York Times that dives deep into the origins of the term and gives credit where it’s due.
It seems Doug himself credits John Mashey as being the original person to coin the term. As the article points out, Mr Mashey is not particularly bothered in any case:
I was using one label for a range of issues, and I wanted the simplest, shortest phrase to convey that the boundaries of computing keep advancing.
John Mashey
This doesn’t discredit Doug from coining the 3 V’s that we talk about in the video. These have since been expanded on (almost to death) by people desperate to add more simplicity but seemingly making the world increasingly complex.
Rather than re-record the video and airbrush out my own error, I thought it would be an interesting aside for anyone keen to go further down this particular rabbit-hole.
Data, master data, metadata, now BIG data?
What’s all the fuss about big data? Well, big data really is a term that came about in the early 2000s. I believe it was coined (edit – popularised) by Doug Laney, who started talking about the explosive growth in the amount of data that we were able to capture once people started to carry around smart devices and things that connect us to the Internet.
The 3Vs
So what was it Doug was coining (edit – thinking) when he came up with the idea of big data? Well, he gave it the 3 “V”s as a definition, starting with volume.

Volume
Historically, you would have had large transactional data sets. These days, however, everybody’s carrying around smart devices. There are various different sensors and things like that. Social media interactions allow organisations to compile and pull in much larger volumes of data than they did in the past. They can also store that at scale relatively cheaply with cloud storage and data links.

Velocity
Then there’s the second “V”, the velocity of data. Velocity looks at the speed with which data comes in and the timeliness of it. Think about that in the context of transactional data. Just looking at the data you can see what transactions are being driven across your organisation and can we detect anything in real-time to perhaps issue coupons or price codes to our shoppers at checkout?

Variety
Lastly, let’s look at the variety of data. Previously, we discussed structured data. In the next lesson, we’ll talk about unstructured data. These are things like emails and videos. But there’s a whole wealth of different data types that can now be pulled in and you can run analysis and comparisons across these different data sets, hence “variety” of data.

To sum it up..
If it helps, Cognopia’s logo happens to be a nice Venn diagram. Our slogan happens to be “Complex data, simplified” too. – A happy accident.
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Checkout now!Origins of big data:
https://bits.blogs.nytimes.com/2013/02/01/the-origins-of-big-data-an-etymological-detective-story/