A unified approach to data modeling and data mapping could be the breakthrough that many data-driven organizations need.
In most of the conversations I have with clients, they express the need for a viable solution to model their data, as well as the ability to capture and document the metadata within their environments.
Data modeling is an integral part of any data management initiative. Organizations use data models to tame “data at rest” for business use, governance and technical management of databases of all types.
However, once an organization understands what data it has and how it’s structured via data models, it needs answers to other critical questions: Where did it come from? Did it change along the journey? Where does it go from here?
Data Mapping: Taming “Data in Motion”
Knowing how data moves throughout technical and business data architectures is key for true visibility, context and control of all data assets.
Managing data in motion has been a difficult, time-consuming task that involves mapping source elements to the data model, defining the required transformations, and/or providing the same for downstream targets.
Historically, it either has been outsourced to ETL/ELT developers who often create a siloed, technical infrastructure opaque to the business, or business-friendly mappings have been kept in an assortment of unwieldy spreadsheets difficult to consolidate and reuse much less capable of accommodating new requirements.
What if you could combine data at rest and data in motion to create an efficient, accurate and real-time data pipeline that also includes lineage? Then you can spend your time finding the data you need and using it to produce meaningful business outcomes.
Good news … you can.
Automated Data Mapping
Your data modelers can continue to use erwin Data Modeler (DM) as the foundation of your database management system, documenting, enforcing and improving those standards. But instead of relying on data models to disseminate metadata information, you can scan and integrate any data source and present it to all interested parties – automatically.
erwin Mapping Manager (MM) shifts the management of metadata away from data models to a dedicated, automated platform. It can collect metadata from any source, including JSON documents, erwin data models, databases and ERP systems, out of the box.
This functionality underscores our Any2 data approach by collecting any data from anywhere. And erwin MM can schedule data collection and create versions for comparison to clearly identify any changes.
Metadata definitions can be enhanced using extended data properties, and detailed data lineages can be created based on collected metadata. End users can quickly search for information and see specific data in the context of business processes.
To summarize the key features current data modeling customers seem to be most excited about:
- Easy import of legacy mappings, plus share and reuse mappings and transformations
- Metadata catalog to automatically harvest any data from anywhere
- Comprehensive upstream and downstream data lineage
- Versioning with comparison features
- Impact analysis
And all of these features support and can be integrated with erwin Data Governance. The end result is knowing what data you have and where it is so you can fuel a fast, high-quality and complete pipeline of any data from anywhere to accomplish your organizational objectives.
Want to learn more about a unified approach to data modeling and data mapping? Join us for our weekly demo to see erwin MM in action for yourself.
