Quest

Fig 2 - Built-in Data Observability to Ensure Data Reliability

Data owners can be assigned and the product supports workflow for data stewards, who curate and bring together technical assets with business assets such as business terms, policies, rules and more, manage data classifications, and manage requests for data access. Asset discovery and collaboration, including the recently released erwin Data Marketplace, provide consumer-like capabilities to allow end users to analyse, compare and share data products, datasets, AI models and other data assets, commenting on and ranking the usefulness of assets in a similar way that they might rank and comment on movies or products they have purchased on-line. Automated data value scoring for reliability and value can also be leveraged. Companies determine the weighting of these user ratings and reviews, of data quality scores and of data governance curation completeness to yield a data value score and visual indicator that can help make trusted, high-value assets quickly recognisable for data marketplace consumers and lay the groundwork for potential monetisation. The software can be deployed on-premises, privately hosted in a company’s own cloud instance, or deployed as erwin Data Intelligence Cloud, a Quest-hosted offering on Azure.

The software has automatic data asset discovery, speeding up the onboarding of data assets using techniques including fuzzy logic. The software can recognise a business term such as a social security number and can find all columns with that term based on column definitions, presenting that to a data steward. The product has visual displays such as knowledge graphs and mind maps to allow end users to easily visualise the relationships surrounding business and technical assets. Data elements can be classified as sensitive for personally identifiable information purposes. Data lineage assessment can be carried out right down to table and column level, and both business and technical data lineage characteristics can be displayed within the same all-in-one data lineage tool, with views instantly switched and filtered depending on the audience. Customers can define organisational terms, business and AI risk policies, regulations and processes and set up automated governance workflow processes to evaluate and authorise changes.

Data governance is more than just populating a standalone data catalog and business glossary. The governance process extends to data quality and reliability, and is not a one-off exercise but something that requires constant monitoring. erwin has long been the de-facto standard for data modelling, and so many customers may wish to use an integrated suite of tools, from modelling through to data quality through to catalog, data lineage and marketplace, rather than dealing with a series of tools from different vendors and having to interface these together.

The software automates many of the time-consuming aspects associated with data discovery, quality assessment, business contextualisation, governance guidance and organisational data literacy enablement and data accessibility.

The bottom line

erwin Data Intelligence is a full-function data governance product that can also leverage the proven erwin data modelling tool. It competes with other such products like Collibra and Alation, and should be considered for companies wishing to embark on enterprise-wide data governance. Its latest version shows considerable ongoing investment in the technology.