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The Data Warehousing and Business Intelligence (DWBI) Exam, also known as DAMA DWBI-1220, is a certification exam that assesses an individual's knowledge and skills in data warehousing and business intelligence. DWBI-1220 exam is designed to evaluate a candidate's ability to design, implement, and manage data warehousing and business intelligence solutions. It covers a wide range of topics, including data modeling, data integration, data quality, data governance, business analytics, and reporting.
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DAMA DWBI-1220 certification exam is suitable for data warehousing and business intelligence professionals who already have some exposure to the field and wish to validate their skills and knowledge formally. Data Warehousing and Business Intelligence certification program is also an excellent choice for individuals who aspire to make a career in data warehousing and business intelligence. Additionally, it is designed for practitioners working with commercial or open-source relational database management systems.
DAMA DWBI-1220 Exam is a comprehensive certification program that tests the knowledge and skills of professionals in the field of data warehousing and business intelligence. Passing the exam demonstrates that the candidate has a thorough understanding of the principles and practices of data warehousing and business intelligence and is capable of applying them in real-world situations. DWBI-1220 exam is based on industry standards and best practices, and it is updated regularly to reflect the latest developments in the field.
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DAMA DWBI-1220 Exam is administered by the Data Management Association (DAMA), which is a non-profit, vendor-independent organization that is dedicated to advancing the field of data management. DWBI-1220 exam is designed to assess the candidate's understanding and ability to apply the best practices and principles of data warehousing and business intelligence in real-world scenarios. Data Warehousing and Business Intelligence certification is recognized globally, making it a valuable credential for professionals who are seeking to build a career in the field of data warehousing and business intelligence.
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| Section | Objectives |
|---|---|
| Topic 1: Dimensional Modelling and Design | - Normalization vs dimensional approaches - Fact and dimension tables, slowly changing dimensions - Star and snowflake schema design |
| Topic 2: Data Warehousing Fundamentals | - Purpose and role of data warehousing within enterprise data management - Data storage concepts and scalability considerations - Architectural models (Inmon, Kimball, hybrid approaches) |
| Topic 3: ETL and Data Integration | - Handling metadata and lineage in warehousing - Data quality and integration techniques - Extract, Transform, Load processes and tools |
| Topic 4: Business Intelligence Concepts | - BI frameworks and analytical reporting principles - Self-service BI and decision support systems - BI tools, dashboards, and data visualisation techniques |
| Topic 5: Performance Optimisation and Modern Architectures | - Cloud-based data warehousing and modern platform considerations - Real-time analytics and big data integration - Query performance, indexing and partitioning strategies |
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