Introduction to Data Management

Learn how data quality anchors data management, enabling compliant reporting, GDPR readiness, and reliable decision making across legacy systems and startups.

Define data governance policies and procedures to ensure data quality and archiving, privacy, and security. Link governance roles like data owners and stewards to master data management and data registers.

Explore data ownership and data steward roles in governance, with owners setting strategic policies and stewards handling technical procedures. Learn why a single business owner ensures accountability and data quality.

Explore the dimensions of data ownership across organizations, where attributes within a data entity have different owners, and regional, domain, and lifecycle factors shape governance through specialization.

The data governance officer coordinates ownership and stewardship across departments, standardizing practices, exchanging information, and elevating data quality while the data owners retain responsibility.

Apply data ownership and data steward roles within your organization's domain structure. Ensure cooperation, escalation channels, and training to address data privacy and data quality in governance.

Define prescriptive and descriptive architecture roles, guide change with rules and procedures, and map baseline to target architectures through stakeholder analysis and data modeling.

Learn prescriptive data architecture by applying constraints—principles and patterns—driven by data ownership, a leading source system, and data integration to guide projects.

Explore descriptive data architecture by examining data models, patterns, and artifacts; learn how canonical data models and integration patterns enable decoupled, reusable architectures.

Explore how data modeling supports data management, governance, and architecture, detailing stakeholders, data owners, and the three-layer framework of conceptual, logical, and physical models.

Learn conceptual data modeling with Archimedes notation to define data entities, primary and secondary models, and their relationships across business and application layers, with stakeholder collaboration and iterative validation.

Explore how the logical data model sits between conceptual and physical models, focusing on semantic and syntactic details, entities, attributes, relationships, cardinality, and stakeholder alignment.

Learn physical data modeling as the technical implementation of conceptual and logical models, using primary keys, foreign keys, and constraints to generate relational or XML structures.

Explore data operations within data management, linking incidents, problem management, and change and release processes to ensure data availability, performance, backup and restore, and security and privacy.

Explore why data quality sits at the center of data management and how stakeholders apply Dharma's data quality framework to improve data across the lifecycle.

Explore the 11 data quality attributes from the data management body of knowledge. Understand how accuracy, completeness, consistency, timeliness, and other qualities affect data use and governance.

Explore registers and master data as high-quality data sets, emphasizing accuracy, validation, completeness, and timeliness. Understand keys, authentic registers, metadata, and data ownership in data management.

understand master data management as the coordinated process of building high quality, reusable data entities across registers, with ownership, governance, data quality (accuracy, completeness, and uniqueness), and integration across systems.

Explore four master data management models and practical architectures for data registers, data integration, and data virtualization, with validation, governance, and interface transformations guiding consumer and producer interactions.

Explore how data warehouses integrate internal and external sources, enable time-based drill-down reporting, and support ETL processes, governance, and BI with star or snowflake data models.

Explore practical data warehouse models, from star to snowflake, with fact tables and hierarchies for product, time, shop, and employees, and learn ETEL extraction, transformation, and load.

Master data security and data privacy, including authentication, authorization, access rights, and auditing. Discover why protecting personal data and organizational information matters for compliance, transparency, and preventing corporate image damage.