Why does data quality need a catalog?

Focus, distil and amplify the benefits of data management with a data catalog

Forrester recently reported that 25% of companies don’t know how much poor data costs them. With data volumes increasing exponentially, data estates become ever more complex and being able to control data to ensure it is accurate and fit for purpose is both vital and a key challenge for modern businesses.

Data quality technologies have long been recognised as a valuable means of improving data, but with data complexity increasing, tackling quality issues in isolation can limit the overall effectiveness and impact of data quality programmes.

The missing piece of the puzzle is oversight of the full data estate, which provides understanding of data quality issues and initiatives in context and brings control to the end to end management of data. This is where a data catalog comes into play.

Significantly enhance data quality programmes with a data catalog

What is data quality?

Data quality at its simplest looks at how reliable your data is, with the aim to support rather than restrict business ambitions. This can include looking at accuracy, completeness, consistency, uniqueness, validity and more, with the focus on achieving fit for purpose data that enables business success.

Data quality technology helps businesses to improve and maintain their data – from validating contact data, to profiling and assessing data completeness, to deduplicating customer records – and beyond.

Good quality data is the foundation for any business to be able to operate effectively, so data quality initiatives are vital for ensuring this foundation is solid.

Key components of a catalog include:

The benefits of a catalog in action

One example of data quality technology adding value could be in the management of credit data, where it can be used to ensure high quality data can be produced in an efficient manner. Firms that submit data to a credit reference agency (CRA) could use data quality rules to automate the preparation of data for submission to help ensure it meets CRA standards, improving efficiency through the process, monitoring on the standard of data quality and reducing manual effort and intervention.

However, is the process understood, documented and controlled or is it the remit of a sole team or individual and so a single point of failure? Adding a data catalog to the use case introduces that oversight and control.

The addition of the catalog transforms the submission process into something that is fully understood, documented and trusted. It contextualises and becomes a single source of truth for data – where critical data items, processes and programmes are documented for business wide understanding and oversight. It elevates data quality initiatives, democratises data and transforms culture to become data driven.

Best practices for implementing a data catalog

Implementing a data catalog requires a willingness to invest resource and time in harvesting metadata, populating the catalog and then maintaining it. It can be a complex, challenging process but with considered planning combined with leveraging robust technology and expertise, organisations can achieve a well populated catalog that enhances control, understanding and accessibility, and by extension overall data management.

If you’re considering amplifying your data quality practices with a catalog, here are our best practice tips to maximise your investment:

Define your purpose: make sure you’re clear on the goal(s) driving the investment into a catalog, on the types of data to be included and on the audience you want to influence

Identify and involve key stakeholders: harvesting metadata and onboarding a catalog takes commitment and time, so involve the right people from the start to gain their buy in and ensure the right outcomes are delivered
Pay attention to sensitive data: identify and consider how sensitive data will be managed early in scoping to minimise risk

Catalog your data in phases: start with critical or high priority data and expand from there to prevent the project from becoming unmanageable. Lean on stakeholder knowledge and expertise, and capture full and complete metadata including descriptions, ownership and relationships to maximise the effectiveness of the catalog in improving discoverability and understanding across the business.

Establish data governance policies: consider the controls, standards and measures that need to be in place to maintain the catalog and protect the investment in it

Document and implement security measures to protect data against unauthorised access and breaches
Monitor, iterate and update: consider the catalog as a living entity and evolve it with your organisation’s changing data landscape

Amplify your data quality efforts with a data catalog

A data catalog is a powerful tool that significantly enhances data quality. By providing a central source of truth and repository for metadata, it makes data easily discoverable, understandable, and accessible. This unlocks the ability to govern data, comply with regulation and reduce risk. The catalog will facilitate collaboration, enabling business users to work more efficiently and make informed decisions based on accurate data. Ultimately, integrating a data catalog alongside data quality initiatives supports improved data integrity, accuracy, reliability and trust.