TDWI Data Warehouse Automation: Better, Faster, Cheaper Training

  • Learn via: Classroom / Virtual Classroom / Online
  • Duration: 1 Day
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  • We can host this training at your preferred location. Contact us!

Building a data warehouse is among the most labor-intensive and time-consuming activities of BI development. There are many moving parts—requirements, source data analysis, source-target mapping, data acquisition, data transformation logic, ETL design, database loading, scheduling, error handling—and getting it right the first time isn’t easy. When you finally do get it right, something changes. One of the most pervasive problems in BI today is the fact that data warehouses take too long to build and they are hard to change!

Data warehouse automation (DWA) is a relatively new class of technology that accelerates warehouse development and change cycles while simultaneously assuring quality and consistency. More than simply generating ETL scripts, DWA automates the entire life cycle from source system analysis to testing and documentation. Productivity gains, cost savings, and quality improvement are all possible with DWA.

There is no prerequisite.

BI and data warehousing program and project managers; data integration architects, designers, and developers; data warehouse operations, maintenance, and support personnel; data and technology architects.

  • Concepts, principles, and practices of data warehouse automation (DWA)
  • The current state of DWA technology
  • Automation opportunities and benefits when building or managing a data warehouse
  • How to get started with DWA
  • Best practices and mistakes to avoid with DWA

Module 1 – Data Warehouse Automation Concepts and Principles

  • Data Warehouse Automation Basics
    • Data Warehouse Automation Defined
    • Automated vs. Hand-Crafted
    • Automation vs. Customization
    • Data Warehouse Automation vs. CASE
  • Why Data Warehouse Automation
    • Business Benefits
    • Technical Benefits
    • Barriers and Resistance
  • The Foundation
    • Components of Data Warehousing
    • Data Warehousing Projects
    • Design Patterns
  • Activities and Deliverables
    • Data Warehousing Processes
    • What Can You Automate?
  • The Technology Landscape
    • Automation Tools and Vendors

Modue 2 – Building and Managing the Data Warehouse

  • The Data Warehousing Lifecycle
    • A Closed Loop
    • Architecture and Planning
    • Implementation
    • Deployment and Operations
  • Building the Data Warehouse
    • Requirements Driven Development
    • Modeling and Metadata Driven Development
    • Discovery Driven Development
    • Data Driven Development
  • Managing the Data Warehouse
    • Operations
    • Monitoring and Tuning
    • Maintenance and Change
    • Evolution
    • Support

Module 3 – Using Data Warehouse Automation

  • Automation Use Cases
    • Building an New Data Warehouse
    • Building Dependent Data Marts
    • Building Dimensional Data Marts
    • Conforming Independent Data Marts
    • Data Warehouse Prototyping
    • Agile Data Warehousing
    • Data Warehouse Migration
    • Re-Architecting the Data Warehouse
    • Warehouse Management
  • Case Studies
    • Arch Insurance Group
    • British American Tobacco
    • F5 Networks
    • Lamar
    • ProShop
    • Shell Oil
    • Union Bank

Module 4 – Data Warehouse Automation in Action

  • BIReady in Action
    • Product Overview
    • Demonstration
  • Kalido in Action
    • Product Overview
    • Demonstration
  • TimeXtender in Action
    • Product Overview
    • Demonstration
  • WhereScape in Action
    • Products Overview
    • WhereScape RED
    • Demonstration

Module 5 – Getting Started with Data Warehouse Automation

  • Step by Step
    • A Process for Automation
  • Human Factors
    • People and Automation
  • New Horizons
    • Automation and Data Warehousing Trends
  • Next Steps
    • Making Your Plans


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