Skip to main content
Version: Next

Data Governance

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

  • Define Data Ownership.
  • Set the Scope of Data.
  • Agree the Guiding Principles.
  • Set the Rules for Managing Data.
  • Establish an escalations Decision-making body (Data Governance Council)
  • Set up the Data Governance Team to support the business with the implementation of the rules.

Define Data Ownership​

This establishes a consistent approach for organisations to define and apply data ownership.

The key principle is that ownership must be assigned at the point of data creation or ingestion—as this is the only stage where issues can be effectively identified and resolved before inconsistencies spread across systems.

Therefore, the process or function that generates or introduces the data into the organisation is responsible for owning and maintaining its quality from the outset.

Set the Scope of Data​

This Data Lifecycle applies to all data that exists within or enters the organisation, including:

  • Newly created data generated internally.
  • Data acquired or purchased from external sources.
  • Data embedded within applications purchased by the organisation.
  • Data generated through artificial intelligence (AI).
  • Data produced by predictive analytics models.
  • Data derived from machine learning algorithms.

This comprehensive approach ensures that all forms of data—regardless of origin—are governed consistently throughout their lifecycle.

Agree the 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 Rules for Managing Data​

Procedure​

This document outlines the mandatory requirements that must be met at each stage of the Data Lifecycle within your organisation.

It addresses the "What" and "Why" of data management, establishing the rules by which data will be governed. These requirements serve as the foundation for ensuring data is handled consistently, securely, and effectively across the organisation.

The Data Governance Team is responsible for monitoring compliance with these requirements and offering support where improvement opportunities are identified. Issues that require further action will be escalated 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 “How”) 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.

Establish an escalations Decision-making body​

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

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.