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ASPE SDLC now offers specialty agile assessments













COURSE 9160 | 2-DAY SESSION
Introduction to Business Intelligence
Build the right mix of project management and requirements gathering skills to make your data warehouse project stick.

Learn how to:
  • Implement best practices, Identify business and technical drivers for the project
  • Gather and prioritize business and technical requirements
  • Identify critical success factors and mitigate risk
  • Scope out current and future project phases
  • Identify organizational and cultural issues, including staffing, roles, and responsibilities
  • Manage user expectations for function, schedules, performance, and availability
  • Determine data warehouse methodology, project planning, and project control
  • Discern effective change control
  • Prepare for success in deployment, rollout and ongoing support
  • Implement effective management monitoring and communication
  • Harness the most proven data warehouse/BI best practices

Making the decision: will BI initiatives pay off for you?
Business Intelligence and Data Warehousing are expensive initiatives that shouldn’t be taken lightly. Both involve high risk and high reward for the most experienced project manager or business analyst. Project management is especially critical for a data warehouse project. Without good management, projects are prone to run late, go over budget, deliver low quality, and most importantly, simply miss expectations.

Your understanding determines your success
It is imperative that project managers and business analysts allocate sufficient time to gain a complete understanding of the corporate vision including:

  1. Short and long term objectives and requirements
  2. Strategic plan to meet those objectives and requirements
  3. Challenges and obstacles
  4. All the key performance indicators (KPIs)

The data warehouse project manager or business analyst must embrace new tasks and deliverables, develop a different working relationship with the users, both business and IT, and work in an environment that is far less defined than with traditional operational systems.

Live, In-Class Breakout Sessions
The workshop will mix classroom instruction and breakout sessions. The breakout sessions enable group discussions in a consultative environment with the instructor examining how the concepts, best practices and industry experiences discussed during the workshop apply to your company and project situation. The breakout sessions are interactive and encourage a two-way dialogue to provide the instructor with a better understanding of your particular situation. Using a consultative approach enables the instructor to better target your needs and focus your training on how it applies to you.

Specifically you will:

    1. Plan by exercise selected portions of your project
    2. Discuss best practices that are applicable to your project
    3. Identify critical success factors and risks impacting your project
    4. Understand how to organize and mobilize both IT and business to achieve success
    5. Gain a detailed understanding of data warehousing and business intelligence projects

This course helps develop the skills needed to usher projects through all phases of planning and implementation. It provides a solid basis on: test data, metadata planning, data stewardship, governance, backup planning, ROI measurement, documentation, support preparation, user training, communications planning, and other elements of a successful data warehouse.


Immediate Benefits of This Workshop:

  1. Understand how to develop a comprehensive project plan for your data warehousing or business intelligence project that will lead to successful business solutions
  2. Grasp how to gather and prioritize business and technical requirements
  3. How to scope out current and future project phases
  4. Understand the organizational and cultural issues, including staffing, roles, and responsibilities
  5. How to manage user expectations for function, schedules, performance, and availability
  6. How to identify critical success factors and mitigate risk
  7. Understand what data warehouse methodology, project planning, and project controls you need
  8. Determine effective change controls for an iterative DW/BI approach
  9. How to prepare for successful deployment, rollout and ongoing support
  10. Identify and select appropriate best or pragmatic DW/BI practices for your project
  11. Recognize the differences between a data warehouse or BI project and a standard IT project
  12. Understand data quality and integrity metrics
  13. Grasp the ETL process
  14. Determine how your current BI tools will fit into your project
  15. Comprehend a standard test plan for a data warehouse or BI project
  16. Identify potential rollout strategies for your data warehouse or BI project
  17. Understand how to fill the communication gaps between IT and business teams