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Data Governance

To implement good governance at your organisation, there are some steps required to get there:

  • Set up the Data Governance Council
  • Agree the Guiding Principles.
  • Set the Scope of Data.
  • Set the Rules that must be followed.
  • Set up the Data Governance Team to support the business with the implementation of the rules.

Data Governance Council​

For effective management, this should be made up of the executives from each area of the business. This ensures that there is right level of buy in when decsions are made and actions are requested by the Council.

Guiding Principles​

These are the common Data principles from DAMA Data Management Book of Knowledge are enforced when you utilise CryspIQ.

Accessible​

Principle for Data accessibility:

  • Data should be accessible in one place and be searchable.
  • Common understanding of Data across the business using terms defined in mapping process.

Available​

Principle for Data availability:

  • Timely and up to date data is available for use.
  • Governed Data is shared and available for use.

Creation​

Principle for Data creation and acquisition:

  • Captured one, used many times.
  • Issues are fixed at source.
  • Ownership is set at point of creation as this is the only place it can be fixed.

Longevity​

Principle for Data longevity:

  • Data must be retained independently of the source system.
  • Data should ne destroyed when it is no longer required.
  • Only business relevant Data should be managed.

Open​

Principle for implementing Data restrictions:

  • Data is Open by default, restricted by exception
  • Data is secured based on its sensitivity to ensure it has the right level of protection.

Usage​

Principle to make Data useful:

  • Must be usable, of good quality for both primary, secondary and tertiary uses.
  • Metadata about the Data must be maintained.

Set the Scope of Data​

This Data Lifecycle applies to all Data that enters or exists in the Organisation, which includes the following:

  • All New Data that is created or exists within an Organisation.
  • All Data that is purchased and bought into the Organisation.
  • All Data that comes into the Organisation when an application is purchased.
  • Any Data that is created through artificial intelligence (AI).
  • Any Data that is created through predictive analytical models.
  • Any Data that is created through applying machine learning algorithms

Set the Rules that must be followed​

Procedure​

This document articulates the requirements that are Must be met in each stage of the Data Lifecycle at your Organisation. It answers the questions for β€œWhat” and β€œWhy” for your Organisation. It provides the rules by which Data will be governed at your Organisation. The Data Governance Team will monitor the β€œMust” requirements and provide support where opportunities are identified to improve. With an escalation point up to the Data Governance Council.

Visual Processes​

These are Process flow diagrams that provide a visual representation of procedure.

Work Instructions​

These articulate the steps required in the process flow and what is expected.

Guidelines​

These support the Procedure (Examples of β€œHow”) and provide extra information as a guideline to the more specialised areas of Data Management. The Business Unit can choose to use these to support their processes or they can define ("How") their own guidelines which help them meet the requirements set out in the procedure. Data Management Capabilities which are normally considered are:

  • Business Criticality,
  • Privacy Rating,
  • Data Sensitivity,
  • Master Data Management,
  • Reference Data Management,
  • Metadata Management,
  • Data Quality Management.

Questions and Answers​

Capture lessons learnt for any outlier scenarios to ensure consistency of application across your business.

Tips​

Start with the Data lifecycle and assign Data ownership / stewardship. Focus your business on one / two capabilities at a time and mature them. Rinse and Repeat until your reach the required level of maturity.

Sample plan could be:

  • Year 1 - Data Lifecycle and Ownership
  • Year 2 - Data Security / Criticality
  • Year 3 - Data Quality
  • Year 4 - MetaData Management

If you would like more information about Data Governance, please contact us.