Metadata Management: How to Bring Business and IT Users Together
The Importance of Enterprise Metadata Management Tools
How well do you know your data? Can you tell where it came from, where it’s referenced and if it’s relevant for your analytics or reporting initiatives?
With the right metadata management tools, you can understand your data with full context. They help you increase your data’s quality and relevance. This allows you to unleash its full business value. As data continues to grow and become more distributed, it’s essential to use metadata to:
- Discover data
- Understand data relationships
- Track how data is used
- Assess the value and risks associated with data usage
These are mission-critical processes. As such, metadata management plays a central, strategic role in driving digital transformation.
A metadata management solution becomes even more valuable if it is active. This means your metadata management is accelerated with AI and machine learning, augmented with human knowledge and integrated with data analytics programs and other applications that generate new data insights. It makes broader data management processes, applications and systems more intelligent and dynamic.
Active metadata management is the foundation of a well-architected data management system. This yields benefits across the entire lifecycle of data projects. For example, creating a metadata repository can highlight missing, incorrect or anomalous data. By tapping into the metadata, your systems can automatically correct and enrich the data feeding into a report. This helps avoid costly errors. It also enhances the quality of data analytics to sharpen data-driven decision-making.
Informatica Enterprise Metadata Management Tools
Informatica’s enterprise metadata management tools help you fully harness the value of all your data with active metadata.
Four categories of metadata management
Informatica helps enterprises to start this journey by tapping into four major categories of metadata:
- Technical metadata: Database schemas, mappings and code, transformations and quality checks
- Business metadata: Glossary terms, governance processes as well as application and business context
- Operational and infrastructure metadata: Run-time stats, time stamps, volume metrics, log information, system information and location information
- Usage metadata: User ratings, comments and access patterns
Metadata in these four categories becomes the basis for a common metadata foundation. Informatica metadata management uses a rich set of capabilities to create this shared foundation:
- Collect:
- Curate:
- Infer:
Scan metadata from all enterprise data systems across the cloud and on-premises, such as data lakes and data warehouses. This includes databases and filesystems, data integration tools and processes that help fuel your data analytics and data science tools with a high level of trustworthiness toward data fitness.
Document the business view of data with glossary terms, concepts, relationships and processes. Augment the collected metadata with this business context. Gather user input in the form of ratings, reviews, and certifications. This helps to assess the usefulness of data assets to other users.
Apply intelligence to derive relationships not obvious in the collected metadata. This includes data provenance and data lineage, data similarity, and ranking the most useful data sets for different types of users and purposes.
The Power of Metadata Management
Informatica gathers technical, business, operational and usage metadata. This is used to create a knowledge graph of an enterprise’s data assets and their relationships. This metadata graph is made active by applying AI & machine learning, and integrating it with all of our data management solutions.
Active metadata serves as the unifying foundation for the Informatica Intelligent Data Management Cloud, a cloud-native and AI-powered data management platform. Active metadata also fuels data intelligence in the CLAIRE AI engine. This accelerates and automates core data management and governance processes.
CLAIRE uses metadata to:
- Automatically discover data domains
- Classify data
- Identify similar data and other data relationships
- Recommend next-best actions
- Associate business terms with physical datasets
Making an intelligent data catalog a core part of your data infrastructure brings additional benefits. You can ensure that active metadata is integrated into all your data management processes. Informatica Enterprise Data Catalog helps you capture enterprise-wide metadata and turn it into active metadata. This is done using extensive metadata connectors. These scan and index metadata augmented with intelligence from CLAIRE.
Active metadata adds automation to make data easier and more efficient to use. Users can better build, deploy and operate data management applications. These apply to data analytics, data science, data governance and nearly any other data-driven business priority.
Benefits of Active Metadata Management
Here are a few ways Informatica’s active metadata management tools deliver value across the data management lifecycle:
- Next-Generation Analytics
- Enables self-service through simple search, discovery and recommendations for relevant data
- Provides a complete view of data including lineage, relationships and quality. This improves trust and confidence for data analytics
- Helps accelerate AI/ML projects with improved data transparency for agile data preparation, data analysis and development of ML models for AI applications
- Data Quality and Governance
- Discovers, classifies and documents key data elements. This helps you prioritize data governance activities
- Provides detailed metadata and data lineage. This bridges technical and business context for data governance
- Documents data quality in the context of business systems and processes. This increases visibility into sources of data quality problems
- Data Democratization and Sharing
- Enables data consumers of all skill levels to find, understand, trust and access the data they need through a self-service data marketplace
- Empowers data consumers for data-driven decision-making and drives business outcomes
- Data Privacy
- Correlates relationships between individual data subjects and their personal data across structured and unstructured sources. This helps automate data subject access requests (DSARs)
- Tracks protection status, access, proliferation, and risk exposure of sensitive data. This increases compliance transparency and enables remediation
- Master Data Management
- Discovers and accelerates onboarding of new data sources that should be part of your master data
- Infers and recommends additional attributes and hierarchical structures. This simplifies enrichment of master data models
- Cloud Modernization
- Enables comprehensive understanding of your data landscape. This helps prioritize datasets and workloads for cloud migration and data modernization
- Provides detailed data lineage and impact analysis. This supports cloud migration with minimal disruption and optimal efficiencies
- Data Integration
- Speeds up development of data integration pipelines with recommendations on mappings for ETL and ELT
- Automatically derives structure from incomplete device and log files. This makes them easier to understand and work with as complete
- DevOps for Data Management
- Provides predictive analytics and recommendations for future capacity planning
- Helps effectively manage changes with detailed lineage views and business logic that enable what-if impact analyses
Related Metadata Management Resources
Unleash the Power of Cloud Analytics with Metadata Management
Seven Metadata Management Best Practices Every Successful Data Leader Must Know
