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Data and Analytics Tutorial

Data and Analytics Overview
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Data and Analytics Success

Data and Analytics Strategy
Project Management
Data Analytics Methodology
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BI Requirements Workshop

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Enterprise Information Management

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Metadata
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Data Stores and Structures

Data Sources
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Data Pipeline
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BI - Business Intelligence
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Data Science

Statistics
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Prescriptive Analytics

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Testing
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Sustaining DW/BI

Data and Analytics Project Management

Business Intelligence and Data Warehousing Require Project Management Know How

How should a data warehousing / business intelligence project be managed?  Planning and organizing the data warehouse project includes:

  • Defining Scope and Objectives
  • Avoiding Major Data Warehouse Mistakes
  • Choosing Enterprise Data Warehouse vs. Data Mart
  • Getting the Right Sponsor
  • Forming the Team
  • Producing the Project Roadmap and Plans
  • Determining the Budget
  • Training the Team

Defining Scope and Objectives

Defining the correct scope and setting realistic objectives are key to data warehouse project success. Scope defines project boundaries including:

  • Business requirements addressed
  • Users
  • Subject Areas

Objectives define project success criteria including quantified planned benefits.

Defining an overly large project scope and letting scope grow in an uncontrolled fashion (scope creep) are sure fire ways to hurt the chance of project success.

Remember you can't please everyone:

"I cannot give you a formula
for success, but I can give you a formula
for failure: try to please everybody."

- Herbert Swope



We recommending the SMART objectives approach when setting goals and objectives.

SMART Objectives Support Data Warehousing

Avoiding Major Data Warehouse Mistakes

Be alert against making these common data warehousing missteps:

  • Focus on technology instead of people and process
  • Lack of sponsorship and management support
  • Overly ambitious or undefined scope
  • Undefined requirements
  • Unrealistic expectations
  • Failure to architect a long term solution
  • Failure to obtain high quality data
  • Failure to consider future requirements
  • Trying to turn the prototype into the final solution
  • Designed around one tool/vendor
  • Failure to scale up
  • Failure to store at the right level of detail / grain

The Methodology article provides a step by step approach that should help you to avoid these problems.  For further understanding of best and worst practices see the article titled Sustaining Data Warehousing and Business Intelligence.

Enterprise Data Warehouse vs Data Mart

The choice of Enterprise Data Warehouse vs Data Mart is key to the success of data warehousing projects.

The Enterprise Data Warehouse is:

  • Enterprise Wide
  • All purpose 
  • Takes 2 to 5 Years to Build
  • Requires Executive Sponsor
  • Costs $2 to $5 Million

While the Data Mart is:

  • Business Unit or Business Process Focused
  • Focused Purpose
  • Takes 2 to 9 Months to Build
  • Requires Management Sponsor
  • Costs $200,000 to $2 Million

The project may require both an Enterprise Data Warehouse and one or more Data Marts.  The Technical Architecture explains more about this choice.

Forming the Data Warehousing Team

The right team is key to any successful project and data warehousing projects are no different.  The following roles are needed for an effective data warehousing project team:

  • Sponsor and Data Warehousing Champions
  • Project Leader / Manager
  • Business Subject Matter Experts (SMEs)
  • Coaches
  • Business Analyst
  • Enterprise Architect
  • Data Warehouse Trainer
  • Data Modeler
  • Database Administrator
  • Technical Architect
  • Extract/Transform/Load Designer/Developers

Getting The Right Sponsor

 The executive sponsor is a senior management person who takes overall responsibility for a project.  A good project sponsor typically is a:

  • Person with large stake in the project outcome
  • Person with authority over resources appropriate to project (Data Warehouse requires more authority and resources than Data Mart)

The project sponsor fills a number of roles including:

  • Developer of the business case
  • Harvester of benefits
  • Overseer of the project
  • Link to upper management
  • Project champion - promoting the project across the organization

For more information see Terence J. Cooke-Davies' excellent article, The Executive Sponsor – The Hinge upon which Organisational Project Management Maturity Turns? that describes the role of the project sponsor.

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Producing the Project Roadmap and Project Plans

 The Project Roadmap is larger in scope than a single project plan.  It encompasses a series of projects that carry the organization forward to longer range objectives.

An individual project will include:

  • Develop Scope Definition
  • Develop Work Package Plan
  • Develop Project Schedule
  • Assemble Project Budgets
  • Approve Plan

Key Project Questions

  Answering critical questions is another key to project success:

" I keep six honest serving men, They taught me all I knew;
Their names are what and why and when and how and where and who. "

- Rudyard Kipling



Seek to answer these key questions: 

  • What are the expected outcomes of this project?
  • What are the inputs and outputs?
  • Why are we doing this project?
  • When will the project begin and end?
  • How will the outcomes be accomplished?
  • Where will the project take place?
  • Who is involved with this project?
  • Who is the customer?
  • Who is the sponsor?
  • Who will contribute to the project?

The Proposed Project Plan

The purpose of the proposed project plan is:

  • Communication tool (decision makers and team members)
  • Decision making tool (should this project be approved?)
  • Guides the project phases and activities

The proposed project plan contains:

  • Overview of project (Mission, Scope, Goals, Objectives, Benefits)
  • Project activity description (Activity List and Work Breakdown Structure)
  • Project timeline and critical path
  • Resource requirements
  • Cost estimate / budget

Approving the plan includes committing to the proposed resource level as well as approving the stated objectives.

Developing Scope

 Scope specifies the boundaries of the project.  It tells what’s in and what’s out.  This effort includes: 

  • Scope plan
  • Scope definition
  • Alternative development

Develop Work Package Plan

 The Work Package Plan is a detailed plan that breaks a project down to the activity level.  The first part of this work includes building an activities list using techniques such as brainstorming, templates and checklists.  This is followed up with these further efforts.

  • Activity reconciliation - Prioritize, combine
  • Activity definition
  • Activity selection - Apply litmus test
  • Work Breakdown Structure (WBS)

Determining the Budget

 The budget is an itemized projection of the resources need for the project including the amount of money needed for item.  Here are some of the major items that should be included in the budget:

  • People (Employees, Consultants)
  • Hardware
  • Software (Development, Infrastructure)
  • External Data

The people budget can be determined by multiplying the hours estimated in the Work Package Plan by the rates.  The projections for hardware, software and external data depend upon the Technical Architecture selected.  Be sure to add some contingency time in case the project does not go as planned.

Training the Team

 Make sure that the data warehousing team is trained in the skills needed for success.  Review each role and team member for needed skills and train as needed.  Team members may require skills in areas such as:

  • Project Management
  • Data Warehouse Architecture
  • Data Warehouse Modelling
  • Requirements Analysis
  • Specific Tools

 


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