Automated metadata harvesting, data mapping, code generation and data lineage
Data makes the world go ‘round, and it probably makes your head spin too – trying to find it, understand where it came from and then use it strategically. According to Gartner, curated internal and external datasets for a range of content authors doubles business benefits and ensures effective management and monetization of data assets in the long-term if linked to broader data governance, data quality and metadata management initiatives. The erwin Data Catalog (DC) automates enterprise metadata management, including data cataloging, data mapping, data quality, code generation and data lineage for faster time to value and greater accuracy for data movement and/or deployment projects. Harvest metadata from various data sources and map data elements from source to target, including “data in motion,” and harmonize data integration across platforms. With this accurate picture of your metadata landscape, you can accelerate digital transformation projects, including Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., without heavy reliance on technical resources.
Efficiently integrate and activate your data in a single, unified data catalog in accordance with business requirements.
Easily scan metadata from various operational systems, catalog and synchronize it with core data management and governance capabilities and artifacts in real time.
Speed up data movement and transformation projects, code generation and data movement documentation, reducing errors and delivery timeframes.
Schedule ongoing scans from the widest array of metadata sources and targets, including reference data and code sets, enabling automated metadata harvesting to update the catalog while leaving enrichments in place. Combined with reference data management, data profiling and lifecycle management, these capabilities keep your metadata current with full versioning and change management, reducing expensive manual tasks and rework.
Use source and target system metadata to accelerate the creation of source-to-target, metadata-driven mapping. Our drag-and-drop approach and auto mapping feature eliminates manual work and costly errors that are usually seen with a traditional Excel approach.
ETL/ELT and code generation for other data integration components can be automated and customized to meet customer-specific requirements with plug-in SDKs to accelerate project delivery and reduce rework.
Generate end-to-end lineage between repositories and view data flows from source systems to reporting layers, including intermediate transformation and business logic. Instantly identify the impact of changes to business terms or physical data before you make them.
Data Intelligence: Empowering
the Citizen Analyst
The Value of Automated Data
Mapping & Preparation for the
Solving the Enterprise Data Dilemma
The Regulatory Rationale for
Integrating Data Management
& Data Governance
2018 State of Data Governance
Data Governance Is Everyone’s Business