Designing and Implementing Data Warehouses


A crucial part of every Business Intelligence system is a data warehouse — its design and implementation determine if stored data can be used to answer business questions quickly and efficiently. Because data warehouses serve a different purpose than operational databases (OLTP), their structure is also different, which means that to create a successful data warehouse a distinct set of skills is needed. The goal of the training is to equip BI specialists and database programmers with knowledge and skills necessary to manage and conduct data warehouse projects. The participants gain knowledge and necessary abilities on multidimensional modelling, in particular they get familiar with the two most popular multidimensional modelling methodologies — Ralph Kimball’s and William Inman’s ones. The training emphasizes practical ramifications of multidimensional modelling and implementations of those techniques using Microsoft technologies, mainly SQL Server.


  • Course level: 300
  • Start date: as required
  • Duration time: 3 days

Price: 3500 zł

  • Open training
  • On-site (costumer's premises)
  • Customer’s computer


The course is addressed to BI specialists and database programmers. Its participants will be given a complete methodology of multidimensional modelling, starting with identifying business processes, through data warehouse design, dimension tables design and optimization, fact tables design and optimization, and finishing with making the DW highly efficient and scalable.


The basic training is comprised of 8 modules. Just like all the other courses on our offer, it has been designed by our experts, therefore we can freely customize it to suit the individual needs of the participants. We would like to encourage you not only to choose the modules which you find relevant for your needs, but also to feel free to contact us with your suggestions and questions you would like to hear answered during the course. Our trainings are exceptional also because we limit the time set aside for laboratory type classes customarily conducted after the completion of each module, to the benefit of exercises done with the assistance of the trainer and demonstrations. We believe in this manner we can equip you with substantially more practical information and tips, and focus on dealing with the issues directly within your scope of interest. However, each day of the training is finished with a laboratory class of approximately 1hr, so that you can do self-practice and do exercises of your choice.


Duration: Level:
Module 1

Introduction to Multidimensional Modelling
  • Characteristic of Data Warehouse
  • Kimball’s Methodology and Data Warehouse Development Lifecycle
  • Inman’s Methodology
  • Hub and Spoke hybrid approach
  • Presentation of Microsoft DW/BI Technologies

60 minutes 300
Module 2

Data Warehouse Project Lifecycle
  • Project Planning and Management Best Practices
  • Milestones of DW Project
  • Technology Track Lifecycle
  • Data Track Lifecycle
  • BI Track Lifecycle

60 minutes 300
Module 3

Multidimensional Modelling Basics Techniques
  • Introduction to Multidimensional Modelling
  • Introduction to Bus Matrix
  • Identification and Analysis of Business Processes
  • Declaring the Grain
  • Identify the Dimensions
  • Identify the Facts and Measures
  • Determining Requirements and Limitations of a Project Scope
  • Star Schema and Snowflake Schema Overview
  • Introduction to Dimension Tables
  • Introduction to Fact Tables
  • Model Evaluation

180 minutes 300
Module 4

Basic Fact Tables Modelling Techniques
  • Fact Table Logical Design
  • Additive, Semi-additive and Non-additive Measures
  • Three Fact Table Types: Transactional, Periodic Snapshot and Cumulative Snapshot
  • Factless Fact Tables
  • Fact Table Physical Design

120 minutes 300
Module 5

Basic Dimension Tables Modelling Techniques
  • Dimension Table Logical Design
  • Surrogate versus Natural Keys
  • Degenerate Dimensions
  • NULL Handling Techniques
  • Time Dimension Considerations
  • Hierarchies
  • Uniform Dimensions
  • Role-Playing Dimensions
  • Junk Dimensions
  • Slowly Changing Dimension Types 1,2 and 3
  • Dimension Table Physical Design

180 minutes 300
Module 6

Advanced Fact Tables Modelling Techniques
  • Surrogate Keys
  • Numeric Values as Measures or Attributes
  • Working with Fact tables of Different Grain
  • Bridge Tables
  • Dealing with Different Currencies
  • Pros and Cons of Snapshot Fact Tables
  • Timespan Tracking Techniques
  • Drilling Down Techniques
  • Dealing with Incomplete Data

180 minutes 400
Module 7

Advanced Dimension Tables Modelling Techniques
  • Joining Dimension Tables
  • Multivalued Dimensions and Bridge Tables
  • Slowly Changing Dimension Types 4,5,6 and 7
  • Dynamic Values Bands Techniques
  • Dealing with Different Time Zones
  • Hierarchies Optimization Techniques
  • Account Dimensions
  • Dealing with Incomplete Data

180 minutes 400
Module 8

SQL Server DW Functions
  • Bitmap Indices
  • Data Compression
  • Sparse Attribute
  • Columnstore Indices

120 minutes 300


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