Certified Data Management Professional (CDMP) Essentials

Data governance defines a set of processes, policies and procedures to ensure availability, integrity and security of data assets throughout their lifecycle, enabling quality, compliance with regulations and informed decisions.

Discover data governance frameworks such as Dama POC Data Management Body of Knowledge framework and Cobit, and learn practices like executive sponsorship, data policies, data stewardship, and data quality management.

Data stewards own data assets, enforce quality standards, and uphold governance, privacy, and security across domains through collaboration with users and IT teams.

Explore data governance implementation strategies such as top down, bottom up, pilot project, federated, and center of excellence. Organizations tailor these approaches to goals and culture to implement governance practices.

Explore data quality and its dimensions, including accuracy, completeness, consistency, timeliness, validity, uniqueness, and precision, to improve decision making and data driven initiatives.

Explore data quality assessment techniques to evaluate and improve data assets. Learn how data profiling, sampling, dimension assessment, rules validation, metrics analysis, and cleansing reveal and correct quality issues.

Explore data cleansing and data validation methods to identify and correct errors, de-duplicate records, standardize formats, validate against business rules, and ensure referential integrity for high data quality.

Define clear data quality objectives aligned with organizational goals, identify stakeholders, set standards for profiling, sampling, and checks, and implement monitoring and improvement strategies for continuous data quality.

Explore data modeling to define entities, attributes, and relationships, identify primary and foreign keys, and create a blueprint that guides database development, ensures data consistency, and enables integration.

Explore er modeling concepts that visualize entities, attributes, and relationships, and explain primary keys, foreign keys, cardinality, degree, weak entities, and inheritance in database design.

Explore database design principles and normalization to create efficient, scalable databases. Learn how entity relationships, primary keys, and foreign keys enforce data integrity and remove redundancy across normal forms BCNF.

Advance data modeling with subtyping and supertyping to classify entities into subtypes, apply aggregation and recursive relationships, and employ dimensional modeling with denormalization for efficient querying and analysis.

Integrate data from diverse sources using ETL to provide a unified view and improve data quality, enabling informed decisions and advanced analytics.

Master the extract, transform, and load process for data integration, extracting, transforming, enriching, aggregating, and loading data from diverse sources into target systems with data quality.

Explore data integration strategies, including batch processing, real time integration, ESB routing, data replication, and data virtualization, and ETL tools, EAI tools, and integration platforms that implement them.

Explore data warehouse and data mart design, including data sources, a three-tier architecture, etl processes, data modeling with star and snowflake schemas, governance, and bi tools for integrated, historical analytics.

Master data management ensures a single source of truth by enforcing data governance, quality, and integration across systems, enabling consistent, compliant, and efficient decision making and operations.

Master data governance and data quality in MDM establish a framework of rules, ownership, and processes that ensure consistent, secure, and high quality master data across systems.

Define business objectives and assess current state to lay the foundation for master data management, then establish governance, data quality, and integration practices for secure, interoperable MDM.

Gain an overview of global data privacy regulations, including GDPR, CCPA, DPA, and LGPD. Learn key principles like consent, purpose limitation, data minimization, and individual rights.

Learn to implement data privacy compliance by understanding regulations like GDPR and CCPA, conducting a DPIA, applying privacy by design, managing data subject rights, and planning incident response.

Implement access controls, encryption, masking, and anonymization, and network security to protect data from unauthorized access, then establish backups, disaster recovery, security awareness, incident response, and audits for resilience.

Learn how data analytics moves from data collection and pre-processing to exploration, modeling, evaluation, and insights using descriptive, diagnostic, predictive, and prescriptive analytics.

Explore data visualization techniques and tools to transform raw data into charts, graphs, maps, and infographics that reveal patterns, trends, and insights for data-driven decision making.

Leverage data sources, integrate and warehouse data, then analyze and report insights to support data-driven decisions. Identify trends, optimize performance, and gain competitive edge through dashboards, reports, and actionable information.

Develop a data management strategy that ensures accuracy, accessibility, and security. Define goals, assess current data landscapes, establish data governance, and implement data quality controls to enable trusted data-driven insights.

Data management maturity models, including CMMi and data management maturity frameworks, offer a path to assess current capabilities, identify gaps, and chart a roadmap for governance, quality, integration, and architecture.

Design and implement a data management roadmap that aligns with business objectives, prioritizes initiatives, engages stakeholders, and measures progress through milestones across governance, quality, integration, and security.

Explore the CDMP exam overview and structure, including computer-based format, domains such as data governance, data modeling, data quality, data integration, data security, and levels from associate to master.