Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata, or the data about the data.
However, most organizations don’t use all the data they’re flooded with to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or make other strategic decisions. They don’t know exactly what data they have or even where some of it is.
Quite honestly, knowing what data you have and where it lives is complicated. And to truly understand it, you need to be able to create and sustain an enterprise-wide view of and easy access to underlying metadata.
This isn’t an easy task. Organizations are dealing with numerous data types and data sources that were never designed to work together and data infrastructures that have been cobbled together over time with disparate technologies, poor documentation and with little thought for downstream integration.
As a result, the applications and initiatives that depend on a solid data infrastructure may be compromised, leading to faulty analysis and insights.
Metadata Is the Heart of Data Intelligence
A recent IDC Innovators: Data Intelligence Report says that getting answers to such questions as “where is my data, where has it been, and who has access to it” requires harnessing the power of metadata.
Metadata is generated every time data is captured at a source, accessed by users, moves through an organization, and then is profiled, cleansed, aggregated, augmented and used for analytics to guide operational or strategic decision-making.
In fact, data professionals spend 80 percent of their time looking for and preparing data and only 20 percent of their time on analysis, according to IDC.
To flip this 80/20 rule, they need an automated metadata management solution for:
• Discovering data – Identify and interrogate metadata from various data management silos.
• Harvesting data – Automate the collection of metadata from various data management silos and consolidate it into a single source.
• Structuring and deploying data sources – Connect physical metadata to specific data models, business terms, definitions and reusable design standards.
• Analyzing metadata – Understand how data relates to the business and what attributes it has.
• Mapping data flows – Identify where to integrate data and track how it moves and transforms.
• Governing data – Develop a governance model to manage standards, policies and best practices and associate them with physical assets.
• Socializing data – Empower stakeholders to see data in one place and in the context of their roles.
Addressing the Complexities of Metadata Management
The complexities of metadata management can be addressed with a strong data management strategy coupled with metadata management software to enable the data quality the business requires.
This encompasses data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossary maintenance, and metadata management (associations and lineage).
erwin has developed the only data intelligence platform that provides organizations with a complete and contextual depiction of the entire metadata landscape.
It is the only solution that can automatically harvest, transform and feed metadata from operational processes, business applications and data models into a central data catalog and then made accessible and understandable within the context of role-based views.
erwin’s ability to integrate and continuously refresh metadata from an organization’s entire data ecosystem, including business processes, enterprise architecture and data architecture, forms the foundation for enterprise-wide data discovery, literacy, governance and strategic usage.
Organizations then can take a data-driven approach to business transformation, speed to insights, and risk management.
With erwin, organizations can:
1. Deliver a trusted metadata foundation through automated metadata harvesting and cataloging
2. Standardize data management processes through a metadata-driven approach
3. Centralize data-driven projects around centralized metadata for planning and visibility
4. Accelerate data preparation and delivery through metadata-driven automation
5. Master data management platforms through metadata abstraction
6. Accelerate data literacy through contextual metadata enrichment and integration
7. Leverage a metadata repository to derive lineage, impact analysis and enable audit/oversight ability
With erwin Data Intelligence as part of the erwin EDGE platform, you know what data you have, where it is, where it’s been and how it transformed along the way, plus you can understand sensitivities and risks.
With an automated, real-time, high-quality data pipeline, enterprise stakeholders can base strategic decisions on a full inventory of reliable information.
Many of our customers are hard at work addressing metadata management challenges, and that’s why erwin was Named a Leader in Gartner’s “2019 Magic Quadrant for Metadata Management Solutions.”
