Metadata Management Tools for Data-Driven Enterprises

Key Elements for Metadata Management Tools in Data-Driven Enterprises

Driving Metadata Management

Almost every enterprise today is seeking to gain a competitive advantage by harnessing their data to make more data-driven decisions. But where do they even begin? How do you jump-start a data and self-service analytics strategy? In the most pragmatic sense, you can’t begin without knowing what data you have in your possession. So how do you know what data you have and how do you ensure you have the momentum to stay ahead of your data? Core to a data strategy is a metadata management practice that includes metadata management tools with some very key elements. Those key metadata management tool elements include a data inventory, data lineage, the user experience, data enrichment, business rules, metadata exchange, support for security and privacy and a general means around managing complex deployments. All of these things and more are necessary to gain a competitive advantage for a data-driven enterprise.

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Key criteria to look for in a metadata management tool

  • Streamlined data inventory
  • Data lineage insight
  • Simple user experience
  • Data enrichment automation
  • Defined business rules
  • Metadata exchange
  • Support for security and privacy
  • Expertise on complex deployments

Data Lineage

Data lineage helps determine the validity of your data. Waterline Data derives lineage information that compares the data to determine its source of data and the downstream uses of data.

Using artificial intelligence to analyze data within hive tables, SQL tables, or files in HDFS and cloud storage, the more advanced metadata management tools such as Waterline Data, identify similar signatures to select potential lineage candidates. Data stewards can review inferred lineage and accept or reject the lineage derived by the automated algorithms thereby increasing an enterprise’s confidence in their data.

User Experience

A variety of users and functional groups own data within any enterprise. Therefore, metadata management tools must be able to support the skill-set of any user, in addition to the data architects or data stewards helping to manage the data.  Waterline Smart Data Catalog provides a unique user-friendly, collaborative approach to managing and curating metadata. Users collaborate and share “tribal data knowledge” through curation, comments, and ratings, ensuring valuable metadata remains accessible across organizations and available to make informed business decisions through self-service analytics.

Data Enrichment

Data tagging and ratings enrich the data for better management. Smart data catalogs curate data and provides capabilities for rating data, such that data analysts, data scientists, and stewards are able to rate the data to provide further information for data consumers. Waterline Smart Data Catalog enables users to easily define automatic rules for identifying data such as account information which may contain personally identifiable information (PII).

Further, the automatic tagging capabilities enable unique technologies to even identify such things as duplicate data.

Business Rules

Business semantics identify the relationships between data elements. Waterline Smart Data Catalog provides custom properties to connect the right data to the right people as part of a metadata management process. Automatic tagging based on business logic can be augmented through a rules engine to adapt to an enterprises business culture.

Support for Security and Privacy

Data privacy policies differentiate smart metadata management applications from other metadata management tools. Waterline Smart Data Catalog fulfills the metadata management criteria around security and privacy by leveraging the native data source security and permissions to ensure only those permitted can access and use data.

Metadata Exchange and Workflow Management

Ultimately, any metadata management application must be able import and export metadata efficiently. Waterline Smart Data Catalog lets you easily exchange metadata with BI tools, data prep tools, security tools, data governance tools, and single purpose, embedded catalogs. Importing business glossary terms and definitions from existing data glossaries or CSV files helps you leverage previous work. To complement inferred data lineage, it imports existing lineage information directly from Apache Atlas, Cloudera Navigator, and ETL tools. It can also export all tags and any tag associations assigned to individual sources and fields, to close the loop with data governance tools. REST APIs enable you to interoperate across your software ecosystem.

 

 
 

Keep Up-to-Date – Support for the Most Complex Systems

Maintaining a comprehensive, accurate machine learning data catalog of enterprise data assets helps transform your business into a powerful data-driven enterprise. Scaling metadata management for big data requires automation to power continuous updates and prevent data swamps. Waterline Smart Data Catalog continuously updates metadata as data is created, collected, or changed, using automated discovery and machine learning to keep up with the flow and scalability of data across the enterprise. It enables you to respond quickly to evolving regulations, reducing your risk of fines and protecting your brand.

Resources

Are You and Your Metadata No Longer Friends?

Read Blog

Do You Need a Metadata Repository or Do You Really Need a Data Catalog?

Read Blog

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