How to combine Data Vault automation with data governance & data quality

Automate your Data Vault 2.0… and achieve good data governance along way

Increasing digitisation and the need to become more data-driven mean that effective data governance is recognised as being key in many businesses and organisations. A survey by data governance experts Erwin, found the subject among the top five priorities for the businesses quizzed – while 91 per cent of the sample, placed it among their top 10 business and technology priorities for 2022 and beyond. The Data Vault User Group listened to a presentation by Erwin’s Richard Adams and Paul Kinnier on the subject of ‘Combining Data Vault Automation with Data Governance and Data Quality.’ They explained how erwin’s Data Intelligence software will both automate the process of creating a Data Vault and help ensure good data governance and data quality along the way. The need to ensure your data governance policies not only cover where data is generated, stored, moved and how long it stays there, but also include data inventories that delineate exactly who owns the data – who has access to it, and who should not be able to access it – has never been greater. In doing so, businesses and organisations – large and small – can ensure they comply with regulatory requirements, such as the management of Personally Identifiable Information, reducing risk of facing costly legal action and possible resulting fines, or avoidable compensation claims. Less than one-in-two companies that erwin contacted in last year’s survey believe they have a fully implemented data governance program. But if you are behind the curve, what can Erwin’s solution offer? Richard Adams, erwin’s DI solution strategist, explained that within erwin’s Data Intelligence Suite, the Data Catalog features cover metadata, mapping, reference data and a resource manager. erwin Data Literacy uses artificial intelligence combined with the Business Glossary and the business user portal gives all stakeholders access to data relevant to their roles within a business context. Data Intelligence uses data connectors to harvest and analyse metadata by collecting, mapping and standardising data attributes. ensuring data is curated and managed to optimise its use through its entire lifecycle. Most importantly teams across the business interact with data governance in one place – and crucially in their own context. Paul Kinnier, erwin’s Data Vault principal engineer explained how the Data Intelligence product delivers Data Vault automation that meets the Data Vault 2.0 standard. He then explained the roles of smart data connectors using auto identification of business keys, and auto-generation of hash keys, timestamps, and source field records. It also takes care of ETL (extract, transform and load) and ELT (extract, load and transform) orchestration and generation. Richard explained how erwin’s RapidDataVault Automation bundle generates a raw vault from a bottom-up and top-down perspective while generating metadata into fully functional data definition language (DDL) and generates Data Vault mappings into fully functional ELT/ETL processes. It then automatically creates the business vault mappings and metadata to generate the business vault layer, incorporating hubs, links, satellites, point-in-time and bridge tables. The software automatically provides data lineage insights and documentation from the data source through to the report. You can watch the presentation above.