Cover -- Title Page -- Copyright -- About the Author -- Contents -- Forewords -- By Aditya Kongara -- By John R. Talburt -- By Aaron Zornes -- Preface -- Part I-Introduction -- 1: An Introduction to Data Governance -- Definition -- Case Study -- The Pillars of Data Governance -- Summary -- 2: Enterprise Data Management Reference Architecture -- Edm Categories -- Big Data -- Data Governance Tools -- Summary -- Part II-Categories of Data Governance Tools -- 3: The Business Glossary -- Bulk-load Business Terms in Excel, CSV, or XML Format -- Create Categories of Business Terms -- Facilitate Social Collaboration -- Automatically Hyperlink Embedded Business Terms -- Add Custom Attributes to Business Terms and Other Data Artifacts -- Add Custom Relationships to Business Terms and Other Data Artifacts -- Add Custom Roles to Business Terms and Other Data Artifacts -- Link Business Terms and Column Names to the Associated Reference Data -- Link Business Terms to Technical Metadata -- Support the Creation of Custom Asset Types -- Flag Critical Data Elements -- Provide OOTB and Custom Workflows to Manage Business Terms and Other Data Artifacts -- Review the History of Changes to Business Terms and Other Data Artifacts -- Allow Business Users to Link to the Glossary Directly From Reporting Tools -- Search for Business Terms -- Integrate Business Terms with Associated Unstructured Data -- Summary -- 4: Metadata Management -- Pull Logical Models From Data Modeling Tools -- Pull Physical Models From Data Modeling Tools -- Ingest Metadata From Relational Databases -- Pull in Metadata From Data Warehouse Appliances -- Integrate Metadata From Legacy Data Sources -- Pull Metadata From ETL Tools -- Pull Metadata From Reporting Tools -- Reflect Custom Code in the Metadata Tool -- Pull Metadata From Analytics Tools -- Link Business Terms with Column Names.

Pull Metadata From Data Quality Tools -- Pull Metadata From Big Data Sources -- Provide Detailed Views on Data Lineage -- Customize Data Lineage Reporting -- Manage Permissions in the Metadata Repository -- Support the Search for Assets in the Metadata Repository -- Summary -- 5: Data Profiling -- Conduct Column Analysis -- Discover the Values Distribution of a Column -- Discover the Patterns Distribution of a Column -- Discover the Length Frequencies of a Column -- Discover Hidden Sensitive Data -- Discover Values with Similar Sounds in a Column -- Agree on the Data Quality Dimensions for the Data Governance Program -- Develop Business Rules Relating to the Data Quality Dimensions -- Profile Data Relating to the Completeness Dimension of Data Quality -- Profile Data Relating to the Conformity Dimension of Data Quality -- Profile Data Relating to the Consistency Dimension of Data Quality -- Profile Data Relating to the Synchronization Dimension of Data Quality -- Profile Data Relating to the Uniqueness Dimension of Data Quality -- Profile Data Relating to the Timeliness Dimension of Data Quality -- Profile Data Relating to the Accuracy Dimension of Data Quality -- Discover Data Overlaps across Columns -- Discover Hidden Relationships Between Columns -- Discover Dependencies -- Discover Data Transformations -- Create Virtual Joins or Logical Data Objects That Can Be Profiled -- Summary -- 6: Data Quality Management -- Transform Data into a Standardized Format -- Improve the Quality of Address Data -- Match and Merge Duplicate Records -- Create a Data Quality Scorecard -- Select the Data Domain or Entity -- Define the Acceptable Thresholds of Data Quality -- Select the Data Quality Dimensions to Be Measured for the Specific Data Domain or Entity -- Select the Weights for Each Data Quality Dimension.

Select the Business Rules for Each Data Quality Dimension -- Assign Weights to Each Business Rule in a Given Data Quality Dimension -- Bind the Business Rules to the Relevant Columns -- View the Data Quality Scorecard -- Highlight the Financial Impact Associated with Poor Data Quality -- Conduct Time Series Analysis -- Manage Data Quality Exceptions -- Summary -- 7: Master Data Management -- Define Business Terms Consumed by the MDM Hub -- Manage Entity Relationships -- Manage Master Data Enrichment Rules -- Manage Master Data Validation Rules -- Manage Record Matching Rules -- Manage Record Consolidation Rules -- View a List of Outstanding Data Stewardship Tasks -- Manage Duplicates -- View the Data Stewardship Dashboard -- Manage Hierarchies -- Improve the Quality of Master Data -- Integrate Social Media with MDM -- Manage Master Data Workflows -- Compare Snapshots of Master Data -- Provide a History of Changes to Master Data -- Offload MDM Tasks to Hadoop for Faster Processing -- Summary -- 8: Reference Data Management -- Build an Inventory of Code Tables -- Agree on the Master List of Values for Each Code Table -- Build Simple Mappings Between Master Values and Related Code Tables -- Build Complex Mappings Between Code Values -- Manage Hierarchies of Code Values -- Build and Compare Snapshots of Reference Data -- Visualize Inter-temporal Crosswalks Between Reference Data Snapshots -- Summary -- 9: Information Policy Management -- Manage Information Policies, Standards, and Processes Within the Business Glossary -- Manage Business Rules -- Leverage Data Governance Tools to Monitor and Report on Compliance -- Manage Data Issues -- Summary -- Part III-The Integration Between Enterprise Data Management and Data Governance Tools -- 10: Data Modeling -- Integrate the Logical and Physical Data Models with the Metadata Repository.

Expose Ontologies in the Metadata Repository -- Prototype a Unified Schema across Data Domains Using Data Discovery Tools -- Establish a Data Model to Support Master Data Management -- Summary -- 11: Data Integration -- Deploy Data Quality Jobs in an Integrated Manner with Data Integration -- Move Data Between the MDM or Reference Data Hub and the Source Systems -- Leverage Reference Data for Use by the Data Integration Tool -- Integrate Data Integration Tools into the Metadata Repository -- Automate the Production of Data Integration Jobs by Leveraging the Metadata Repository -- Summary -- 12: Analytics and Reporting -- Export Data Profiling Results to a Reporting Tool for Further Visual Analysis -- Export Data Artifacts to a Reporting Tool for the Visualization of Data Governance Metrics -- Integrate Analytics and Reporting Tools with the Business Glossary for Semantic Context -- Summary -- 13: Business Process Management -- Data Governance Workflows Should Leverage BPM Capabilities -- Master Data Workflows Should Leverage BPM Capabilities -- Data Governance Tools Should Map to BPM Tools -- Summary -- 14: Data Security and Privacy -- Determine Privacy Obligations -- Discover Sensitive Data Using Data Discovery Tools -- Flag Sensitive Data in the Metadata Repository -- Mask Sensitive Data in Production Environments -- Mask Sensitive Data in Non-Production Environments -- Monitor Database Access by Privileged Users -- Document Information Policies Implemented by Data Masking and Database Monitoring Tools -- Create a Complete Business Object Using Data Discovery Tools That Can Be Acted upon by Data Masking Tools -- Summary -- 15: Information Lifecycle Management -- Document Information Policies in the Business Glossary That Are Implemented by ILM Tools -- Discover Complete Business Objects That Can Be Acted on Efficiently by ILM Tools -- Summary.

Part IV-Big Data Governance Tools -- 16: Hadoop and NoSQL -- Conduct an Inventory of Data in Hadoop -- Assign Ownership for Data in Hadoop -- Provision a Semantic Layer for Analytics in Hadoop -- View the Lineage of Data in and out of Hadoop -- Manage Reference Data for Hadoop -- Profile Data Natively in Hadoop -- Discover Data Natively in Hadoop -- Execute Data Quality Rules Natively in Hadoop -- Integrate Hadoop with Master Data Management -- Port Data Governance Tools to Hadoop for Improved Performance -- Govern Data in NoSQL Databases -- Mask Sensitive Data in Hadoop -- Summary -- 17: Stream Computing -- Use Data Profiling Tools to Understand a Sample Set of Input Data -- Govern Reference Data to Be Used by the Stream Computing Application -- Govern Business Terms to Be Used by the Stream Computing Application -- Summary -- 18: Text Analytics -- Big Data Governance to Reduce the Readmission Rate for Patients with Congestive Heart Failure -- Leverage Unstructured Data to Improve the Quality of Sparsely Populated Structured Data -- Extract Additional Relevant Predictive Variables Not Available in Structured Data -- Define Consistent Definitions for Key Business Terms -- Ensure Consistency in Patient Master Data Across Facilities -- Adhere to Privacy Requirements -- Manage Reference Data -- Summary -- Part V-Evaluation Criteria and the Vendor Landscape -- 19: The Evaluation Criteria for Data Governance Platforms -- The Total Cost of Ownership -- Data Stewardship -- Approval Workflows -- The Hierarchy of Data Artifacts -- Data Governance Metrics -- The Cloud -- Summary -- 20: ASG -- ASG-metaglossary -- ASG-Rochade -- ASG-becubic -- 21: Collibra -- Business Glossary -- Reference Data Management -- Data Stewardship -- Workflows -- Metadata -- Data Profiling -- 22: Global IDs -- Data Profiling -- Data Quality -- Metadata -- 23: IBM -- Metadata.

Information Integration.