New Zealand
Data Governance

Data governance is a grandiose name for something that has been done for decades, but with differences. It is essentially the management of an organisation’s data assets. What is new is that increasingly data is being treated as more than just something to manage, but a business component that needs careful, systematic governance.

In spite of the fact that data is not treated as a balance sheet asset, it is increasingly being seen as something that needs to be treasured and nurtured as an important strategic business resource. Information has always been important to organisations, but there are differences now:

Many organisations, having had both good and frustrating experiences with data warehousing, have recognised that they need to apply management disciplines to ensure that the use of their data, as a competitive advantage, is maximised.

The management of risk is now more prominent than it has ever been, and good data is a critical component of this.

The regulatory environment with respect to data is now much more prescriptive than previously. Depending on the industry, organisations may have local and central government reporting requirements that can contain severe sanctions for late or incorrect information. In addition, privacy regulations and concerns are gaining a greater prominence than has ever been the case before. From an audit perspective, organisations have to show that they have privacy controls in place to ensure that personal information is protected and preserved. In addition to regulatory considerations, privacy breaches are a threat to good customer relations and brand value.

Government agencies are subject to numerous reporting requirements; some regulatory, others as part of the political process. These require both the prudent management of data and the ability to provide accurate information at short notice. Because of this, Government agencies have been governing their data since formation, but there is now a movement to formalise this even more to ensure that it is robust and auditable.

The major benefits of effective data governance are:

  • User trust of reports.
  • Consistent corporate information.
  • Regulatory and audit compliance.
  • Increased use of information for marketing purposes.

There is no one way to undertake data governance. Some organisations need to focus on data quality, others on customer profiles or data privacy. Some organisations will want a very formal system, others a looser arrangement, depending on industry and regulatory environment.

IBM Cognos propose a 14 step process (not all steps are necessary), summarised below:

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  • Define the business problem.
  • Obtain executive sponsorship.
  • Conduct a maturity assessment. The aim of this is to identify where the organisation wants to be in the future and what steps are required to get there.
  • Build a roadmap for getting to desired state.
  • Establish a data governance charter to use when ruling on disputes.
  • Build the data dictionary.
  • Understand the data. Data governance staff need to understand the critical data relationships within the organisation before they can properly manage them.
  • Create a metadata repository. This is a one stop shop for metadata.
  • Define metrics. The purpose of this is to track the progress and health of data governance within the organisation.
  • Govern master data. Business critical information, such as one view of the customer’s interaction with the organisation.
  • Govern analytics. The management of data warehouse assets to ensure they meet organisational needs.
  • Manage security and privacy.
  • Govern the information lifecycle. How to deal with unstructured data.
  • Measure the results. The reporting of metrics to stakeholders.

CDP has experience in every step of this process, having both the technology and management expertise in bringing it all together.