There’s More to erwin Data Governance Automation Than Meets the AI
Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. The clear benefit is that data stewards spend less time building and populating the data governance framework and more time realizing value and ROI from it.
Industry analysts and other people who write about data governance and automation define it narrowly, with an emphasis on artificial intelligence (AI) and machine learning (ML). Although AI and ML are massive fields with tremendous value, erwin’s approach to data governance automation is much broader.
Automation adds a lot of value by making processes more effective and efficient. For data governance, automation ensures the framework is always accurate and up to date; otherwise the data governance initiative itself falls apart.
From our perspective, the key to data governance success is meeting the needs of both IT and business users in the discovery and application of enterprise “data truths.” We do this through an open, configurable and flexible metamodel across data catalog, business glossary, and self-service data discovery capabilities with built-in automation.
To better explain our vision for automating data governance, let’s look at some of the different aspects of how the erwin Data Intelligence Suite (erwin DI) incorporates automation.
Metadata Harvesting and Ingestion: Automatically harvest, transform and feed metadata from virtually any source to any target to activate it within the erwin Data Catalog (erwin DC). erwin provides this metadata-driven automation through two types of data connectors: 1) erwin Standard Data Connectors for data at rest or JDBC-compliant data sources and 2) optional erwin Smart Data Connectors for data in motion or a broad variety of code types and industry-standard languages, including ELT/ETL platforms, business intelligence reports, database procedural code, testing automation tools, ecosystem utilities and ERP environments.
Data Cataloging: Catalog and sync metadata with data management and governance artifacts according to business requirements in real time. erwin DC helps organizations learn what data they have and where it’s located, including data at rest and in motion. It’s an inventory of the entire metadata universe, able to tell you the data and metadata available for a certain topic so those particular sources and assets can be found quickly for analysis and decision-making.
Data Mapping: erwin DI’s Mapping Manager provides an integrated development environment for creating and maintaining source-to-target mapping and transformation specifications to centrally version control data movement, integration and transformation. Import existing Excel or CSV files, use the drag-and-drop feature to extract the mappings from your ETL scripts, or manually populate the inventory to then be visualized with the lineage analyzer.
Code Generation: Generate ETL/ELT, Data Vault and code for other data integration components with plug-in SDKs to accelerate project delivery and reduce rework.
Data Lineage: Document and visualize how data moves and transforms across your enterprise. erwin DC generates end-to-end data lineage, down to the column level, between repositories and shows data flows from source systems to reporting layers, including intermediate transformation and business logic. Whether you’re a business user or a technical user, you can understand how data travels and transforms from point A to point B.
Data Profiling: Easily assess the contents and quality of registered data sets and associate these metrics with harvested metadata as part of ongoing data curation. Find hidden inconsistencies and highlight other potential problems using intelligent statistical algorithms and provides robust validation scores to help correct errors.
Business Glossary Management: Curate, associate and govern data assets so all stakeholders can find data relevant to their roles and understand it within a business context. erwin DI’s Business Glossary Manager is a central repository for all terms, policies and rules with out-of-the-box, industry-specific business glossaries with best-practice taxonomies and ontologies.
Semantic and Metadata Associations: erwin AIMatch automatically discovers and suggests relationships and associations between business terms and technical metadata to accelerate the creation and maintenance of governance frameworks.
Sensitive Data Discovery + Mind Mapping: Identify, document and prioritize sensitive data elements, ﬂagging sensitive information to accelerate compliance efforts and reduce data-related risks. For example, we ship out-of-the-box General Data Protection Regulation (GDPR) policies and critical data elements that make up the GDPR policy.
Additionally, the mind map automatically connects technical and business objects so both sets of stakeholders can easily visualize the organization’s most valuable data assets. It provides a current, holistic and enterprise-wide view of risks, enabling compliance and regulatory managers to quickly update the classifications at one level or at higher levels, if necessary. The mind map also shows you the sensitivity indicator and it allows you to propagate the sensitivity across your related objects to ensure compliance.
Self-Service Data Discovery: With an easy-to-use UI and flexible search mechanisms, business users can look up information and then perform the required analysis for quick and accurate decision-making. It further enables data socialization and collaboration between data functions within the organization.
Data Modeling Integration: By automatically harvesting your models from erwin Data Modeler and all the associated metadata for ingestion into a data catalog you ensure a single source of truth. Then you can associate metadata with physical assets, develop a business glossary with model-driven naming standards, and socialize data models with a wider range of stakeholders. This integration also helps the business stewards because if your data model has your naming standard convention filled in, we also help them by populating the business glossary.
Enterprise Architecture Integration: erwin DI Harvester for Evolve systemically harvests data assets via smart data connectors for a wide range of data sources, both data at rest and data in motion. The harvested metadata integrates with enterprise architecture providing an accurate picture of the processes, applications and data within an organization.
Why Automating Everything Matters
The bottom line is you do not need to waste precious time, energy and resources to search, manage, analyze, prepare or protect data manually. And unless your data is well-governed, downstream data analysts and data scientists will not be able to generate significant value from it.
erwin DI provides you with the ability to populate your system with the metadata from your enterprise. We help you every step with the built in, out-of-the-box solutions and automation for every aspect of your data governance journey.
By ensuring your environment always stays controlled, you are always on top of your compliance, your tagging of sensitive data, and satisfying your unique governance needs with flexibility built into the product, and automation guiding you each step of the way.
erwin DI also enables and encourages collaboration and democratization of the data that is collected in the system; letting business users mine the data sets, because that is the ultimate value of your data governance solution.
With software-based automation and guidance from humans, the information in your data governance framework will never be outdated or out of sync with your IT and business functions. Stale data can’t fuel a successful data governance program.
Learn more about erwin automation, including what’s on the technology roadmap, by watching “Our Vision to Automate Everything” from the first day of erwin Insights 2020.
Or you can request your own demo of erwin DI.
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