Data Warehousing Fundamentals

Course Description


Introduction:

 

Welcome to the "Data Warehousing Fundamentals" training course offered by Cambridge for Global Training. This course is designed to provide participants with a comprehensive understanding of data warehousing concepts, principles, and practices. 

 

In today's data-driven world, organizations need to effectively manage and analyze large volumes of data to gain insights and make informed decisions. Data warehousing plays a crucial role in this process by providing a centralized repository for storing and organizing data from various sources. Through this course, participants will learn the fundamentals of data warehousing, including its architecture, design principles, implementation strategies, and best practices.

 

Course Objectives:

By the end of the course, participants will be able to:

 

  • Understand Data Warehousing Concepts: Gain a solid understanding of the basic concepts and principles of data warehousing, including its purpose, benefits, and components.
  • Learn Data Warehouse Architecture: Explore the architecture of data warehouses, including data sources, data staging, data storage, and data presentation layers.
  • Master Data Modelling Techniques: Learn various data modelling techniques such as dimensional modelling and star schema design for organizing data effectively in a data warehouse.
  • Explore ETL Processes: Understand Extract, Transform, and Load (ETL) processes and tools used to extract data from source systems, transform it into a usable format, and load it into the data warehouse.
  • Implement Data Quality and Governance: Learn how to ensure data quality and governance in a data warehouse environment to maintain accuracy, consistency, and reliability of data.
  • Develop Business Intelligence Solutions: Discover how to leverage data warehousing for business intelligence (BI) solutions, including reporting, dashboards, and data analysis.
  • Apply Best Practices in Data Warehousing: Acquire knowledge of industry best practices for designing, implementing, and managing data warehouses to ensure optimal performance and efficiency.

 

Who Should Attend:

 

  • IT professionals interested in data warehousing concepts and practices
  • Data analysts seeking to expand their knowledge of data warehousing
  • Business intelligence developers
  • Database administrators
  • Data engineers
  • Project managers involved in data-related projects
Course Outline


Unit 1: Introduction to Data Warehousing

 

  • Understanding data warehousing fundamentals
  • Purpose and benefits of data warehousing
  • Data warehouse architecture overview
  • Role of data warehousing in business intelligence

 

Unit 2: Data Modelling Techniques

 

  • Dimensional modelling concepts
  • Star schema design
  • Fact and dimension tables
  • Normalization and denormalization

 

Unit 3: ETL Processes and Tools

 

  • Extracting data from source systems
  • Transforming data for analysis
  • Loading data into the data warehouse
  • ETL tools and their functionalities

 

Unit 4: Data Quality and Governance

 

  • Importance of data quality in data warehousing
  • Data governance principles and practices
  • Data cleansing and validation techniques
  • Implementing data quality controls

 

Unit 5: Business Intelligence Solutions

 

  • Reporting and querying in data warehousing
  • Dashboard design and visualization techniques
  • Data analysis and decision-making support
  • Integrating BI solutions with data warehouses
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Data Warehousing Fundamentals
REF code: Q-916
Date: 15 - 19 Dec 2024
City: Manama
Language: English
Price: 4150 £

Course Description


Introduction:

 

Welcome to the "Data Warehousing Fundamentals" training course offered by Cambridge for Global Training. This course is designed to provide participants with a comprehensive understanding of data warehousing concepts, principles, and practices. 

 

In today's data-driven world, organizations need to effectively manage and analyze large volumes of data to gain insights and make informed decisions. Data warehousing plays a crucial role in this process by providing a centralized repository for storing and organizing data from various sources. Through this course, participants will learn the fundamentals of data warehousing, including its architecture, design principles, implementation strategies, and best practices.

 

Course Objectives:

By the end of the course, participants will be able to:

 

  • Understand Data Warehousing Concepts: Gain a solid understanding of the basic concepts and principles of data warehousing, including its purpose, benefits, and components.
  • Learn Data Warehouse Architecture: Explore the architecture of data warehouses, including data sources, data staging, data storage, and data presentation layers.
  • Master Data Modelling Techniques: Learn various data modelling techniques such as dimensional modelling and star schema design for organizing data effectively in a data warehouse.
  • Explore ETL Processes: Understand Extract, Transform, and Load (ETL) processes and tools used to extract data from source systems, transform it into a usable format, and load it into the data warehouse.
  • Implement Data Quality and Governance: Learn how to ensure data quality and governance in a data warehouse environment to maintain accuracy, consistency, and reliability of data.
  • Develop Business Intelligence Solutions: Discover how to leverage data warehousing for business intelligence (BI) solutions, including reporting, dashboards, and data analysis.
  • Apply Best Practices in Data Warehousing: Acquire knowledge of industry best practices for designing, implementing, and managing data warehouses to ensure optimal performance and efficiency.

 

Who Should Attend:

 

  • IT professionals interested in data warehousing concepts and practices
  • Data analysts seeking to expand their knowledge of data warehousing
  • Business intelligence developers
  • Database administrators
  • Data engineers
  • Project managers involved in data-related projects

Course Outline


Unit 1: Introduction to Data Warehousing

  • Understanding data warehousing fundamentals
  • Purpose and benefits of data warehousing
  • Data warehouse architecture overview
  • Role of data warehousing in business intelligence

Unit 2: Data Modelling Techniques

  • Dimensional modelling concepts
  • Star schema design
  • Fact and dimension tables
  • Normalization and denormalization

Unit 3: ETL Processes and Tools

  • Extracting data from source systems
  • Transforming data for analysis
  • Loading data into the data warehouse
  • ETL tools and their functionalities

Unit 4: Data Quality and Governance

  • Importance of data quality in data warehousing
  • Data governance principles and practices
  • Data cleansing and validation techniques
  • Implementing data quality controls

Unit 5: Business Intelligence Solutions

  • Reporting and querying in data warehousing
  • Dashboard design and visualization techniques
  • Data analysis and decision-making support
  • Integrating BI solutions with data warehouses
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