Effective Data Warehouse Construction

4 Day Course

Book Now - 1 Delivery Method Available:

Scheduled Online Onsite


A Data Warehouse has the potential to revolutionise your business. Increased profitability, customer retention, and market penetration are all possible applications of an effective Data Warehouse implementation … but first of all you have to build it.

The approach, method and design techniques required to build a Data Warehouse differ significantly from those required to build a database to support on-line transaction processing.

This practical course introduces the delegate to all the necessary terminology, architectures, approaches, skills, tools, techniques, and infrastructure required to design and implement a successful Data Warehouse solution.

 This is largely achieved by guiding the delegate through an easy to understand, incremental, and iterative process, and also through a series of practical exercises.

Being vendor-neutral, the extensive practical element of this course reflects the natural heterogeneity developers usually face in the real world. The numerous exercises and demonstrations - using technology from some of the world's leading business intelligence software vendors - make this course far more useful than one which solely focuses on the product set of just a single vendor.

This course is made up of a mix of theory and practicals that allow delegates to apply the principles they have learnt using a variety of industry leading tools. In this rapidly changing area the specific tools may change from time to time. Please contact QA-IQ for the latest details.

On completion, delegates will be able to:

  • Make a business case, assemble a project team, and lay the infrastructure necessary for the Data Warehouse construction to begin
  • Design, implement, utilise, maintain, and administer the Data Warehouse
  • Build models using the dimensional (star schema) modelling technique
  • Extract data from one or more operational systems
  • Transform, condition, and cleanse the data
  • Populate the Data Warehouse using a variety of mechanisms
  • Query, drill-down, and report the data
  • Understand the role of extract tools such as OLAP and data mining
  • Understand the importance of metadata and issues surrounding its integration
  • Assess your organisation's readiness to embark on a Data Warehousing project

Training Partners

We work with the following best of breed training partners using our bulk buying power to bring you a wider range of dates, locations and prices.


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Introduction (1 topic)

  • Historical background; What is a Data Warehouse and why do we need it? OLTP versus DSS; Benefits to the business; Benefits to IT; Reasons for failure

The Project (1 topic)

  • Skills required; Top down vs. bottom up development; Ownership & funding; Methodology; Scoping and requirements gathering; Questions to ask in determining requirements

Modelling (1 topic)

  • Review of modelling terminology and techniques; How a Warehouse is different; Logical and physical modelling; 3NF vs. denormalisation

Dimensional Modelling Basics (1 topic)

  • The dimensional model; The fact table; The dimension tables; Using the dimensional model; Modelling Attributes in the Dimensions; Steps in design

Dimensional Modelling Further Considerations (1 topic)

  • Conformed Dimensions; Synonym Dimensions; Mini Dimensions; Snowflaking; Changing Dimension Values; Handling Hierarchies; The importance of Surrogate Keys; Aggregates

Hardware Architectures and Database Architectures (1 topic)

  • SMP; Clusters; MPP; RDBMS, Things to look out for; Database Parallelism; TPC benchmarks

Software Architectures (1 topic)

  • Centralised Data Warehouse; Independent or Federated Data Marts; Hybrid approach; Standards

Data Extraction (1 topic)

  • Extraction method; Tool selection guidelines; Metadata; dependencies; The Data Quality Assessment Process

Data Transformation (1 topic)

  • The Case for data quality; Transformation; Cleansing; Conditioning; Specific data type issues; Transformation methods

Data Loading (1 topic)

  • How to identify what has changed; Snapshot vs. detail data; Full Refresh vs. Delta Capture; Load methodology; Load techniques

Querying the Data (1 topic)

  • Canned queries; Report writers; ROLAP and OLAP tools; Data visualisation; Drilldown analysis; End user training; Performance

Data Warehousing and the Internet (1 topic)

  • Technology overview; Web reporting; Web marts; The Internet as a data source; Extranets; Intelligent agents

Data Mining and Exploration (1 topic)

  • Data mining methodology; Data minining algorithms; Interpreting the output; Formulating a strategy

Operating and Maintaining the System (1 topic)

  • Processes and procedures; Change control; User and privilege administration; Service level agreements; Archive and recovery

Assessment (1 topic)

  • Being ready for a Data Warehouse; Establishing a plan; Getting the mandate; Training; Feasibility study; Choosing a pilot project


Delegates require a basic understanding of IT and how business systems use IT; this would be gained by at least a year's experience in IT or business systems development. It is assumed that delegates attending this course will already have had some exposure to Relational Databases and Database Modelling. Systems/Application programming experience would be an advantage. Database modelling skills can be acquired on QA-IQ's Database Analysis and Design course. Developers, software engineers, database administrators, data analysts, system analysts or application designers who will be involved in designing, building or maintaining a Data Warehouse.

Additional Learning

The courses below may help you meet the knowledge level required to take this course. If you are unsure please ask a training advisor .

  • Database Analysis and Design

    3 Day Database Analysis Course - Learn the various techniques available to analyse the business processes and produce an Entity-Relationship.

    3 Day Course Course Code CSDRM2
    Scheduled Online Onsite

or call:408-759-5074

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