Understanding Data Warehouses, Data Stores and Data Marts

Available only for on-site training

Why This Course?

Data warehouses are the most challenging and the least understood aspect of data management in business organizations. Many organizations are still struggling to understand the implications of different design alternatives of a data warehouse. Lack of understanding caused organizations to spend millions of dollars building wrong architectures. This course offers an unbiased, technical analysis of design alternatives. It is a must for every one who is involved in planning, building, or managing a data warehouse project.

What will you learn?

  • Why and when a data warehouse is needed
  • The real differences between data warehouses, data stores, and data marts
  • How to prepare/migrate data to the data warehouse
  • OLAP vs. ROLAP for accessing the data warehouse
  • How to select tools for the data warehouse access
  • The role of metadata in data warehouses
  • How to effectively maintain the data warehouse
  • How to meet the needs of business users more effectively

Course Outline

1. Introduction

  • Operational vs. informational data
  • A data warehouse architecture
  • Levels of data in the data warehouse
  • Structuring data in the data warehouse
  • Constructing the data warehouse
  • Cost justification

2. Operational Data Stores

  • What is an ODS
  • Data warehouse vs. ODS
  • Mixing ODS and data warehouses
  • Building the ODS
  • ODS as a first step to data warehousing
  • Capturing the delta in the ODS

3. Data Marts

  • Problems with the data warehouse
  • What is a data mart
  • Advantages of data marts
  • Problems with data marts
  • Mixing data marts and data warehouses

4. Metadata

  • Why metadata
  • Metadata versioning
  • Components and views of metadata
  • Characteristics of tools for metadata

5. Data Acquisition

  • What is data acquisition for the data warehouse
  • A typical data acquisition process
  • Steps of data acquisition
  • Characteristics and examples of data acquisition tools

6. Accessing Data in the Data Warehouse

  • OLAP, ROLAP (relational), MOLAP(multidimensional)
  • Drilling down, drilling across, and drilling through
  • Data mining
  • Classification of data access tools
  • Selecting OLAP tools

7. Data Warehouse Administration

  • The data architecture group and its responsibilities
  • Monitoring the data warehouse
  • Data warehouse routine maintenance
  • Assuring the integrity of the data warehouse