Data Warehousing 

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Data Warehousing 

Introduction:

Our comprehensive four-day interactive program on Data Warehousing is specially designed for mid-management staff in the utilities industry. In today’s data-driven environment, a solid understanding of data warehousing principles is essential for effective management and strategic decision-making. This course aims to equip participants with the fundamental knowledge and analytical skills necessary to navigate and manage data warehousing projects confidently.

Course Objectives and Outcomes:    

  • Fundamental Understanding: Learn the basics of data warehousing, including architecture, design, and implementation.
  • Analytical Skills: Develop the ability to analyze and interpret data warehousing metrics and performance indicators.
  • Data Integration and Management: Gain insights into data integration processes, ETL (Extract, Transform, Load) techniques, and data quality management.
  • Strategic Data Utilization: Understand how to leverage data warehousing for business intelligence, decision support, and strategic planning.

Course Content:

Day 1: Introduction to Data Warehousing

Welcome and Introduction

  • Overview of the Training Program

Overview of Data Warehousing

  • Definition and Importance
  • Key Concepts and Terminology

Data Warehousing Architecture

  • Components of a Data Warehouse
  • Data Warehouse vs. Data Mart

Designing a Data Warehouse

  • Data Modeling (Star Schema, Snowflake Schema)
  • Case Study: Designing a Basic Data Warehouse

Q&A and Recap

Day 2: Data Integration and ETL Processes

Introduction to Data Integration

  • Importance and Challenges

ETL (Extract, Transform, Load) Processes

  • Overview of ETL
  • Extracting Data from Various Sources
  • Transforming Data: Cleaning, Aggregating, and More
  • Loading Data into the Warehouse

Data Quality Management

  • Ensuring Data Accuracy and Consistency
  • Data Profiling and Cleansing Techniques

Case Study: Implementing an ETL Process

Q&A and Recap

Day 3: Data Warehousing Technologies and Tools

Data Warehousing Tools

  • Overview of Popular Data Warehousing Tools (e.g., Oracle, Microsoft SQL Server, Amazon Redshift)

Data Storage and Management

  • Storage Solutions and Optimization

Data Warehouse Performance

  • Indexing, Partitioning, and Query Optimization

Business Intelligence and Data Warehousing

  • Using Data Warehousing for BI and Reporting
  • Case Study: BI Tools and Data Warehousing

Q&A and Recap

Day 4: Strategic Utilization and Advanced Topics

Leveraging Data Warehousing for Strategic Decision-Making

  • Linking Data Warehousing to Business Strategy

Advanced Data Warehousing Topics

  • Real-Time Data Warehousing
  • Big Data Integration

Data Security and Governance

  • Ensuring Data Privacy and Security
  • Data Governance Frameworks

Integrative Exercises and Wrap-Up

  • Group Activity: Developing a Data Warehousing Strategy
  • Ethical Considerations in Data Management

Final Q&A and Feedback