Implementing a Modern Data Catalog to Power Data Intelligence: Make Trustworthy Data Central to Your Organization

Description

Are you looking to use data as a strategic asset in your organization, so that more people can make better, data-driven decisions and accelerate time to value? This report explains how. Whether you're working on self-service analytics, data governance, or cloud data migration, authors Fadi Maali, an experienced data engineer and the lead editor of the DCAT Specification, and Jason Lim, director of product and cloud marketing at Alation, show you why a data catalog is the starting point and center of all of it. Modern data catalogs are collections of metadata describing data assets and their usage. They provide relevant functionality to support metadata management, enrichment, and search. Not only do these catalogs help you find relevant data, they also guide you through the data's proper use. This report shows you how a data catalog can help you easily find and then use the data you need. A data catalog is a collection of metadata describing data assets and their usage. Modern data catalogs provide relevant functionality to support metadata management, enrichment, and search. They not only help users find relevant data but guide them on proper use of that data. Data catalogs help answer the questions: • How can I find relevant data? • Once I find data, can I use it? • Should I use it? • How should I use it? Cataloging and managing metadata in enterprises is not a new practice. Metadata repositories have existed since the 1970s and relational databases have had metadata catalogs since their early days. However, in the years since, the technology surrounding data and the role of data in the enterprise have both changed substantially. Enterprise data landscapes have grown more sophisticated—the “3 Vs” of big data (volume, velocity, and variety) are widely known. And the legislative environment mandating compliant data usage continues to grow in complexity as more people (and AI-powered programs) access and use data in new ways.1 Moreover, the growing adoption of cloud computing and SaaS results in more data residing outside the enterprise infrastructure and control. As a result, collecting, managing, and using comprehensive and accurate metadata has become paramount; and modern data catalogs are the tools that enable best practices. Modern data catalogs have grown in maturity and sophistication to address new and increasingly complex challenges. They now provide a comprehensive set of functionalities to integrate with other enterprise data tools and to support automatic collection and enrichment of metadata, using advanced techniques such as machine learning, natural language processing, and crowdsourcing. 1. Data Catalogs What Is in a Data Catalog? Data Catalog Features and Example Applications A Framework to Characterize Data Catalogs Summary 2. Types of Data Catalogs Tool-Adjunct Data Catalogs Broad Connectivity Intelligence Active Governance Domain-Specific Catalogs Broad Connectivity Intelligence Active Governance Data Catalog Platforms Broad Connectivity Intelligence Active Governance Summary 3. Implementing a Data Catalog Data Catalog in an Enterprise Data Stack Enterprise Data Lakes The Modern Data Stack Data Mesh Data Fabric Successful Implementation of Data Catalogs Accommodate Existing Workflows for Data Users Focus on People Focus on Business and Technical Metadata Have an Adoption Plan Measure Adoption and Impact of the Data Catalog Summary 4. Enterprise Data Catalog Business Impact Catalog Business Impact Catalog Use Cases Self-Service Business Intelligence Data Governance and Guided Data Usage Data Operations Cloud and Multicloud Migration Summary 5. Conclusion About the Authors