Data Governance Basics
This training is designed for professionals who seek to:
understand the basics of data management according to DAMA-DMBOK2®,
gain a holistic view of the role of Data Governance, Data Quality, Metadata, Architecture and other domains,
take the first step towards the CDMP® (Certified Data Management Professional) Fundamentals exam,
learn to apply DAMA principles in practice - in your organization or client projects.
Format
Live online
12 hours of sessions
6 modules: lecture, Q&A, interactive, practical tasks
For whom
Heads of departments, departments and project managers
Data engineers, analysts, data architects, BI engineers
Business analysts, product managers, data stewards
IT auditors
Result
After the training you will be able to
Systematically understand the DAMA-DMBOK Framework
Prepare for the CDMP® exam
Develop basic Data Governance artifacts.
Apply the principles of Data Quality, Metadata and MDM in practice
Understand the architecture of modern data platforms
Advantages
Learning that is based on the experience of successfully passing the exam
The specifics of the state of data management in Ukraine are taken into account
Training with representatives of DAMA Ukraine Kyiv and DAMA International®
Training program
Module 1
Introduction to DAMA-DMBOK® and the basics of Data Governance
Percentage of questions on the exam
Data Governance (11%), Data Ethics (2%), Data Management Process (2%)
Main topics
DAMA-DMBOK as a data management standard: structure, principles, DAMA Wheel
Role of CDMP Certification and Exam Structure
Data Governance Framework: roles, policies, standards, processes, organizational model
Data Ethics: ethical principles in the collection, storage and use of data
Data Management Process: planning, control, evaluation
Module 2
Data architecture, modeling, metadata management
Percentage of questions on the exam
Data Architecture (6%) , Metadata Management (11%), Data Modeling & Design (11%)
Main topics
Enterprise Data Architecture:
conceptual, logical and physical levels
data streams
Enterprise Architecture Frameworks
Data Modeling: ERD, 3NF concepts, normalization, Dimensional Modeling
Metadata Management:
technical, business and operational metadata
business directory
types of metadata management architectures
Relationships between architecture, models, and metadata
Module 3
Master data and data quality
Percentage of total questions on the exam
Master and Reference Data Management (10%), Data Quality (11%)
Main topics
Master Data Management (MDM): core domains, golden record, matching & merging
Reference Data Management: codes, classifiers, standards
Data quality management cycle
Data profiling
Data quality metrics: accuracy, completeness, consistency, timeliness, validity
Identifying the root causes of problematic data (Pareto, 5 Why's)
Data quality standards (ISO 8000, DAMA, Stanford)
Module 4
Data integration, storage and protection
Percentage of total questions on the exam
Data Storage and Operations (6%), Data Integration and Interoperability (6%), Data Security (6%)
Main topics
Data Lifecycle
Data Integration: ETL/ELT, API, Data Virtualization, CDC
Interoperability and exchange standards (JSON, XML, RDF)
Data protection:
sources of data protection requirements
access, encryption, classification, GDPR/ISO 27001
Module 5
Data Warehouses, Business Analytics and Big Data
Percentage of total questions on the exam
Data Warehousing & Business Intelligence (10%), Big Data (2%)
Main topics
DWH concepts: Kimball vs Inmon, star schema, ETL processes
BI & Analytics: OLAP, reporting, KPI, dashboards
Big Data: characteristics (3V+), Hadoop, Spark, Data Lakehouse
Data Lakehouse architectures (Delta Lake, BigQuery, Databricks)
Module 6
Synthesis and preparation for the exam
Main topics
DAMA Wheel Knowledge Zones Repetition
Typical exam questions: formats and tips
Building a personal training plan
How to prepare for the Specialist level