Data Warehousing

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What is Data Warehousing?

  • Data Warehousing course is a fundamental course that is designed to establish the basic knowledge about data warehousing , including planning, designing, building, populating and maintaining a data warehouse.
  • This course is a pre-requisite to the Oracle Business Intelligence course for the students that do not have work experiences in the related fields.
  • Dimensional Modeling is a proven technique for designing and creating a data warehouse. This course will describe the dimensional modeling techniques
  • The data warehouse ETL is considered as the major factor for the success of a data warehouse and considered the major efforts and costs spent on implementing a data warehouse.  This course will describe designing and building the process of extracting, cleaning, conforming and delivering data for the data warehouse

 

Course Benefits:

  • Describe the data warehouse concept and terminology
  • Describe the role of data warehouse and business intelligence in today’s market place
  • Design a data warehouse model using the dimensional modeling techniques
  • Apply the various optimization techniques to improve the data warehouse performance
  • Design and develop a data warehouse ETL process
  • Evaluate the various ETL tools

 

Who Should Attend:

  • This course is designed for anyone who is interested in the career of working as a data warehouse designer, a BI application developer, an ETL designer and developer, a project manager who may be in charge of implementing and deploying a data warehouse, or a data warehouse database administrator. 

 

About the Instructor:

  • 15 year experience in enterprise business application  development
  • 5 year in developing prepackaged BI Apps
  • Various roles in the application development, including application engineer, application architect, solution architect, product manager, and development manager.

 

Course Dates: 6-week course (pls call for details)

 

Course Content

  • Week One – Data Warehouse Overview
      • What is a data warehouse?
      • OLTP vs. OLAP
      • Data Warehouse Lifecycle
      • Dimensional Modeling
      • Dimension
      • Fact
      • Granularity
      • Surrogate key vs. Nature Key
      • Star Schema
      • Snow Flake Schema
      • Data Mart
      • Operational Data Store (ODS)
      • Data Modeling
      • ER and ERD
      • Normalization
      • Denormalization
      • 3NF
      • Primary Key and Foreign Key
      • ETL
      • Extract
      • Transform
      • Load
  • Week Two – Dimensional Modeling basic
      • Dimension
      • Conformed Dimension
      • Slowly Changing Dimension (SCD)
      • Snow Flake Model
      • Dimension Hierarchy
      • Rollup Dimension
      • Degenerate Dimension
      • Rapidly Changing Dimension
      • Junk Dimension
      • Minidimension
      • Outrigger Dimension
      • Role Playing Dimension
      • Fact
      • Transaction Fact
      • Periodic Snapshot
      • Accumulating Snapshot
      • Factless Fact
      • Multiple Currency Support
      • Aggregate
      • Rollup Dimension
  • Week Three – Dimensional Modeling Advance
      • Determining Fact or Dimension
      • Star or Snow Flake
      • Dimension  to Dimension Relationship
      • Partition the Large Dimension
      • Bitmap Index
      • Star Transformation
      • Materialized View
  • Week Four – ETL Process Design
      • Source Study and Data Profiling
      • Logical Mapping and Design
      • Explore the change data capture process
      • Capture and apply deletes to the data warehouse
      • Support Multiple Source systems
      • Conform and Standardize the data
      • Generate the Time dimension
      • Build the slowing change dimensions
      • Resolve the Dimension Foreign Key from Fact
      • Dimension Hierarchy Data Flattening
      • Loading and Updating Aggregates
  • Week Five – ETL Development
      • ETL Tool Evaluation Criteria
      • Informatica Power Center Overview
      • Designer
      • Workflow Manager
      • Repository Manager
      • Informatica Overall Architecture
      • Oracle Data Integrator Overview
      • ODI studio
      • ETL and ELT
  • Week Six – Analyzing and Presenting Data
      • BI Tool Overview
      • Ad Hoc Query Tool
      • Report Creation
      • Dashboard Creation
      • Various Delivery Mechanisms