Certified Data Management Professional - CDMP

Apply data governance as the authority to monitor and enforce data management, ensuring policies, standards, and compliance while fostering data stewardship, governance programs, and change management to protect data value.

Drive data governance to reduce risks and improve processes, anchored in regulatory compliance with HIPAA, GDPR, and CcpA, and by enabling advanced analytics and data science.

Explore centralized, replicated, and federated data governance operating frameworks, understanding how centralized policy standardizes across regions, replicated increases local autonomy, and federated coordinates with business units while preserving autonomy.

Establish an enterprise data governance framework with a formal strategy, readiness assessment, operating model, and defined policies, standards, and governance bodies.

Explore the enterprise data model and enterprise conceptual model, its physical and logical levels, normalization, subject areas, and horizontal and vertical mappings to improve governance, consistency, and interoperability.

Track data flows from tendering to invoicing, including RFPs, proposals, evaluations, and purchase orders, by designing a data flow matrix that captures CRUD operations on core entities.

Explore data modeling components: entities, relationships, attributes, and domains, and learn how entities as nouns capture business objects, define value domains, and enforce clarity, accuracy, and completeness.

Explore how attributes define, identify, and measure an entity with the employee example, and how completeness interacts with primary and candidate keys to uniquely identify instances and support alternate keys.

Explore data modeling components by examining attributes and identifiers, including simple key, compound key, composite key, and surrogate key, with natural keys or business keys such as social security number.

Learn how first normal form removes repeating groups, enforces atomic values, and uses a primary key to uniquely identify records, illustrated by procurement data.

Explore the second normal form, where non-key attributes depend on the primary key and a surrogate procurement id replaces composite keys, enabling product and supplier splits with foreign keys.

Define the CDM as a high-level, entity-focused conceptual data model that clarifies relationships and business requirements to guide logical and physical modeling.

Explore how the logical data model bridges conceptual and physical designs by detailing attributes, normalization, keys, and constraints to align business requirements with a db-agnostic blueprint.

Centralized architectures are simple but risk outages; distributed architectures offer high availability with multi-node processing, using MapReduce with Hadoop, and databases like MongoDB and Cassandra for scalable performance.

Examine how databases balance data integrity and scalability with acid and base processing, detailing atomicity, consistency, isolation, durability, and eventual consistency.

Data security uses policies and procedures to control access, authorization, authentication, and auditing of data, addressing regulatory, government, proprietary, and contractual privacy needs while classifying risks and applying security techniques.

Explore cyber threats, insider and physical threats, and malware categories like adware, spyware, Trojan horse, viruses, and worms, including phishing, social engineering, platform intrusion, SQL injection, and ransomware.

Explore phishing and social engineering as forms of deception, and examine platform intrusion and SQL injection attacks, with defenses like updates, firewalls, and parameterized queries and least privilege access.

Explore common data and network security terms such as backdoors, bots, cookies, firewalls, the network perimeter, DMZs, and VPNs, and understand how these elements defend or expose systems to threats.

Capture deltas from inserts, updates, and deletes with change data capture (CDC) to drive data integration, and compare data-based, log-based, and external object approaches for real-time capability and overhead.

Learn how document and content management controls the life cycle management of unstructured and semi-structured data, enabling fast retrieval, secure access, and regulatory compliance.

Discover how inconsistent department data, including names, region codes, emails, and cost centers, drives misreporting, and learn how reference and master data management align and govern data across the enterprise.

Explore how reference and master data management reconcile and integrate data for enterprise-wide sharing through stewardship, semantic consistency, and guiding principles: shared data ownership, quality, stewardship, control, change, and authority.

Master data management coordinates people, process, and technology to maintain the most up-to-date, unambiguous master data across the enterprise, governing data quality, integration, and access.

Plan and execute data acquisition within a single domain, selecting sources, applying data cleansing, validation, standardization, and enrichment to enable accurate entity resolution in MDM.

Understand the entity resolution process in master data management, including reference extraction, preparation, resolution, identity management, and relationship analysis and affiliation management, and how matching links records across systems.