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Special offer: Training Vouchers - Free Courses with purchase.

 

Designing an Effective Data Warehouse

Course 2191 • 4 Days

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Quick Enrol

You Will Learn How To

  • Architect a robust data warehouse solution
  • Ensure a targeted solution by identifying appropriate stakeholders and requirements
  • Apply dimentional modeling to improve business decisions
  • Extract, transform and load operational data based on organizational needs
  • Employ Business Intelligence (BI) tools to slice and dice data
  • Deploy, maintain and monitor an end-to-end data warehousing project

Course Benefits

Inadequate planning and management of data warehouse projects can lead to failed implementations and dissatisfied stakeholders. A successful data warehousing project involves precise planning and analysis to implement a data store as a basis for the business decision-making process. In this course, you gain the skills needed to develop an effective data warehouse solution.

Who Should Attend

Anyone interested in implementing a data warehouse solution in their organization, and those who need to reengineer an existing data warehouse. Prior experience with a data warehousing implementation and/or databases is helpful but not required.

Course 2191 Content

Introduction to Data Warehousing

  • Identifying data warehouse components
  • Analyzing failed installations
  • Determining stakeholders
  • Developing a roadmap for project implementation

Preparing an Implementation Plan

Establishing a foundation

  • Program vs. project requirements
  • Scoping the project and evaluating business justification
  • Comparing Agile vs. waterfall methodologies

Monitoring progress of the roadmap

  • Tracking stages and communicating milestones
  • Managing project expectations
  • Assessing risk and mitigation plans

Analyzing Organizational Data Requirements

Determining business requirements

  • Assessing the business problem
  • Validating organizational goals
  • Identifying expected outcomes

Soliciting user requirements

  • Choosing diverse participants
  • Ranking feedback based on value to the enterprise

Establishing Dimentional Modeling

Modeling the business process

  • Star and Snowflake schema
  • OLTP vs. OLAP
  • Multidimensional cubes
  • Hierarchies

Comparing modeling techniques

  • Inmon and the relational approach
  • Kimball and the dimensional approach
  • Selecting the appropriate technique for your environment

Evaluating the model

  • Creating fact tables and dimensions
  • Pivoting data in Excel to answer business questions

Building the Data Warehouse

Architecting the Physical Database

  • Mapping the logical data model to the physical data model
  • Evaluating hardware considerations

Ensuring data quality

  • Profiling source data
  • Configuring the database for change data capture
  • Refreshing the data warehouse

Extracting data from multiple sources

  • Connecting to different data sources
  • Databases
  • Spreadsheets
  • Text files

Transforming data during migration

  • Cleansing and scrubbing data
  • Mapping data elements and data types
  • Conforming dimensions and facts

Loading data into a data warehouse

  • Employing a staging database
  • Automating incremental data loading
  • Verifying success for data integrity

Leveraging Business Intelligence for Data Analysis

Identifying levels in the BI stack

  • Demonstrating SharePoint as a deployment platform
  • Utilizing Excel as a client tool for data analysis
  • Querying data from the OLAP server
  • Enumerating the components of the data tier

Exploring business intelligence tools

  • Drill down through multidimensional hierarchies
  • Surfacing Key Performance Indicators (KPIs) to evaluate the health of your organization

Deploying a CompleteData Warehouse Solution

Managing system deployment and support

  • Assembling the testing group
  • Organizing a pilot project

Taking advantage of industry standard tools and techniques

  • Identifying available data warehousing tools
  • Choosing the right tool based on organizational needs
  • Adopting best practices

Planning for growth

  • Controlling change management
  • Choosing a method of data storage
  • HOLAP
  • MOLAP
  • ROLAP

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Learning Tree AnyWareTM is a trademark of Learning Tree International, Inc. in the United States and other countries, and is covered by a patent application pending in the United States.
  
Designing an Effective Data Warehouse

Training Dates

Live online classroom training.Most events below can be taken in-class or live, online from your home or office with AnyWare.
Jul 10 - 13Toronto enrol
Oct 2 - 5Ottawa enrol
Nov 6 - 9Toronto enrol
Jan 29 - Feb 1Ottawa enrol

US Dates

Jul 17 - 20Rockville, MD enrol
Aug 14 - 17New York enrol
Sep 4 - 7Reston, VA enrol
Oct 9 - 12Rockville, MD enrol
Nov 6 - 9New York enrol
Jan 8 - 11Reston, VA enrol

For AnyWare enrolments, please register at least 7 days prior to the start of the course.

More Dates and Locations.

 

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