Data Governance

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Time
7 hours 15 minutes
Difficulty
Intermediate
CEU/CPE
8
Video Transcription
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>> Hi there and welcome to our next lesson, data governance.
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In this lesson we'll
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talk a little bit about what data governance is,
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some issues around data management,
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data quality and as an auditor,
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what you need to look out for.
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Let's begin. Data governance,
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basically, the data environments
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become really complicated.
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Organizations live and die
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basically on the data that they store, maintain,
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its a company asset,
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it is value to the data just
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like any other physical asset.
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Data also exists in many locations.
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Gone are the days of data being
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stored in a single server room in a single building.
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Most contemporary organizations will
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have data stretched across multiple locations,
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multiple countries, even in the Cloud,
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and wherever they make
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sense for them from business perspective.
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Data will also come in many forms.
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Too numerous to really go into or mention.
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But it is essentially anything that can be
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recorded in a one or a zero that will drive the business.
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What data governance does,
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it ensures that stakeholder's needs
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are met first and foremost.
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The data drives the business and so the business needs
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have to be met by the data governance activity.
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Data information management capabilities
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it's a feature that needs to be
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maintained as well as perform to
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compliance of these resources.
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In other words, basically,
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data governance ensures that the data is looked after,
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what's the data stored on a managed by
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is maintained and kept up to date.
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Data management is a component of data architecture,
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which is just one key component
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of enterprise architecture.
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It's a way of looking at
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the enterprise architecture from
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a data-centric point of view,
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which can be important,
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particularly in a complex environment.
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The planning execution,
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policies practice and projects that acquire control,
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protect, deliver, and enhance
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the value of data and information assets.
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That's basically a definition
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from the data management body of
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knowledge that defines exactly what data management is.
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Just like any other asset,
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data needs a life cycle
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like data quality needs a life cycle.
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If we're talking from an organization perspective,
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we need to plan exactly what data
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we need to drive the business,
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we need to design a methodology or a container
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or services that we'll actually use that data,
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we need to build and acquire those services,
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we need to use and apply them,
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we need to monitor to make sure that they're
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running efficiently and effectively
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to support the business,
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and we also need to dispose off that data.
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A good example with data life-cycle,
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particularly in recent years with GDPR and a number of
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other privacy legislations
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coming into different organizations.
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Organizations have had to think
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about the life-cycle of the data,
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particularly when it comes to privacy data.
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If they don't need to keep the data,
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then that's an overhead that they need
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to follow from a compliance and legislation perspective.
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They look at their data and determine what they need,
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when they need it and how they need it.
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If they don't need it at all,
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then that's part of the life cycle.
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As an auditor, what are the issues you need to look for?
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First and foremost, meeting strategic objectives,
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so is the data governance and
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data management actually achieving
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what the business needs to achieve?
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Also need to capture and process to required standards.
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Some data is covered by
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legislation as we just spoke about, such as privacy.
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Configuration of database infrastructure is
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organized to support the strategic objectives.
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For very large organizations,
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database infrastructure can be quite massive and complex,
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and it needs to be organized in such a way that
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comes back to those original business objectives.
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Of course, archive retention and destruction policy.
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Managing the life-cycle of the data needs to
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be evidenced by those types of policies.
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That's basically our lesson.
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We've looked about data governance, what it is,
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we've have looked about data management along
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with the definition of what data management is,
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issues around data quality,
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and also issues that you as
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an auditor needs to be mindful of
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when examining these issues.
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I hope you enjoyed the lesson
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and I will see you in the next one.
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