Data%20Warehouse%20Project%20Planning%20

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Data Warehouse Fundamentals
Chapter 4

• Data Warehouse Project Planning Management

Paul K Chen
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Chapter 4 - Objectives

• Review types of development models
• Review the essentials of system development life
  cycle and project management functions
• Discuss project team organization, roles, and
  responsibilities
• Review data warehouse project scope document
• Consider the warning signs and success factors
• Distinguish between data warehouse projects and
  OLTP system projects
• Discuss Data Warehouse deployment

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Types of Development Models

• The Waterfall Development Model
• The Spiral Model
• The Iterative Development Model

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The Waterfall Development Model

• Characteristics
• Encouraging to gather and define system
  requirements.
• Breaking the complex mission of development into
  several logical steps (, analysis, design, code,
  test, and so forth) Divide and conquer
  approach.
• Ensuring each step is executed properly with good
  quality deliverable, validation, entry, and exit
  criteria for each step.

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The Waterfall Development Model

• Advantages
• Enabling tracking of project progress more
  accurately and uncovering possible slippages
  early.
• Focusing the organization that develops the
  software system to be more structured and
  manageable.
• Disadvantages
• The process could become too rigid to be
  efficient and effective.

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The Spiral Model

• Developed by Boehm in 1988
• Characteristics
• Relying heavily on prototyping and risk
  management vs. the document-driven approach of
  the waterfall approach.
• Foe each portion of the project and for each of
  its levels of elaboration, the same sequence of
  steps (cycle) is involved. For instance, the
  concept of software requirements, to design, and
  implementation, each involves a spiral cycle.

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The Spiral Model

• Approach
• The first step of each cycle is to identify the
  objective of the portion of the product being
  elaborated, the alternative means of
  implementation of the portion of the product, and
  the constraints imposed on the application of the
  alternatives.
• The next step is to evaluate the alternatives
  relative to the objectives and constraints and to
  identify the associated risks and resolve them.
• In addition to prototyping for risk analysis, the
  spiral model also simulations, models, and
  benchmarks in order to reach the beat
  alternatives.

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Waterfall Approach vs. Spiral Approach
Structured Development Analysis, design and
coding take place in The traditional waterfall
way. Each step is isolated from the other.
(Waterfall Approach)
A
D
P
Object-oriented development One multifaceted
model is used from Concept to code. Because one
underlying model is used, teams apply Analysis,
design And programming Concurrently.
A
D
P
(Spiral Approach)
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The Iterative Development Model

• Characteristics
• Begin with a subset of the requirements and
  develop a subset of the product that satisfies
  the essential needs of the users.
• Based on the analysis of each immediate product,
  the requirements and design are modified over a
  series of iterations to provide a system to the
  user that meets evolving customer needs with
  improved design based on feedback and testing.
• Combine with prototyping with the strength of the
  classical waterfall model.
• Supporting the iterative development was the
  small team approach in which each team assumed
  the full responsibility of the system.

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System Development Life Cycle A brief overview

• It is a systematic approach to solving business
• problem. Its divided into seven phases
• Identifying problems, opportunities, and
  objectives
• Determining system requirements
• Analyzing system needs
• Designing the recommended systems
• Developing and documenting software
• Testing and maintaining the system
• Implementing and evaluating the systems

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System Development Life Cycle A Brief Overview

• Why should a system development project be
• segmented in phases?
• Project Management easier to understand and
  manage its deliverables and track its progress
• Resources Better utilize the resources related
  to
• technology, skills, and time
• Risk Minimize commitment and cost in case the
  project restarts.

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Project Management Functions

• Initiate project
• Project planning
• Establishing project
• Organization

• Start the project by assessing the
• opportunity
• Determining tasks, schedule, and
• allocating resources
• Defining project charter and issuing
• The statement of work
• Organizing staff by function, tools
• and environment

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Project Management Functions (contd)

• Administration
• Evaluation and control
• Termination

• On-going project reporting
• And administrative work
• Monitor project progress
• by cost, product, and
• schedule
• Wrapping up the task by
• doing project summary and
• archives

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Five Major Project Fundamentals For System
Analysts

• The five project fundamentals the system analysts
  must
• handle are
• Project initiation
• Determining project feasibility
• Project scheduling
• Activity planning and control
• Managing system analysis team members

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Project Initiation

• Projects are initiated for two broad reasons
• Problems that lend themselves to systems
  solutions
• Opportunities for improvement through
• Upgrading systems
• Altering systems
• Installing new systems

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Project Feasibility

• A feasibility study assesses the operational,
  technical, and economic merits of the proposed
  project
• There are three types of feasibility
• Technical feasibility
• Economic feasibility
• Operational feasibility

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Technical Feasibility

• Technical feasibility assesses whether the
  current technical resources are sufficient for
  the new system
• If they are not available, can they be upgraded
  to provide the level of technology necessary for
  the new system

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Economic Feasibility

• Economic feasibility determines whether the time
  and money are available to develop the system
• Includes the purchase of
• New equipment
• Hardware
• Software

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Operational Feasibility

• Operational feasibility determines if the human
  resources are available to operate the system
  once it has been installed
• Users that do not want a new system may prevent
  it from becoming operationally feasible

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Determining Project Feasibility (Key Issues)

• Value and Expectations
• Risk Assessment
• Top-down or Bottom-up
• Build or Buy
• Single Vendor or Best-of-Breed

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Tools for Planning Scheduling Activities

• Gantt Chart PERT (Program Evaluation and Review
  Techniques) diagram Spreadsheet
• Computer-based project scheduling
• Such as Microsoft Project Computer
  Associates CA-Super Project

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Gantt Chart
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Gantt vs. PERT Diagram
A
B
C
D
E
4
2
5
9
Time
15
20
C, 5
A 4
40
50
E, 6
10
B, 2
D,3
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The longest path is called critical path.
Circles called events
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Activity Planning and Control

• Beginning to plan a project by breaking it these
  three
• major activities
• Analysis
• Design
• Implementation

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Activity Planning and Control

• Refining the planning and scheduling of analysis
  activities
• by adding detailed tasks and establishing the
  following
• milestones
• Data Gathering
• Data Flow Decision analysis
• Proposal Preparation

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Data Warehouse Project Team Roles and
Responsibilities

• Executive Sponsor Direction, support,
  arbitration
• Project Manager Assignment, monitoring, control
• User Liaison Manager Coordination with user
  group
•  Lead Architect Architecture Design
• Business Analyst Requirement definition
• Data Modeler Relational and Dimensional
  Modeling
• Data Warehouse Administrator DBA
• Quality Assurance Analyst Quality control for
  warehouse data
• Testing Coordinator Program, system and tool
  testing
• End-user Application Specialist Confirmation of
  data meanings/relationships
• Development Programmer in-house programming and
  scripts
•   
•   

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Steps in Ascertaining Hardware and Software Needs

• Inventory computer hardware already in the
  organization
• Estimate both current and projected workload for
  the system
• Evaluate the performance of hardware and software
  using some predetermined criteria
• Choose the vendor according to the evaluation
• Acquire the hardware and software from the
  selected vendor
• Acquire the hardware and software in conformance
  with your enterprise architecture
• The acquisition of the hardware and software must
  be justified by a business process required of
  either short-term (tactical) or
  long-term(strategic) goals.

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Data Warehouse Project Scope Document

• I Executive Summary
• -- Business needs
• II Project Background
• -- How did the project start?
• -- Who is the sponsor?
• III Project Definition
• -- Project Objectives
• -- Project Organization
• -- Project Critical Success Factor
• -- Measurements of Success

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Data Warehouse Project Scope Document

• IV Project Scope
• Whats in the Data Warehouse?
• Whats not in the Data Warehouse?
• Samples of Queries Reports
• V Methodology and Approach
• Methodology Employed
• Techniques Employed

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Data Warehouse Project Scope Document

• VI Project Cost/Benefits
• VII Project Schedule, Budget and Resources
• -- The plan should include the following
  milestones
• Logical Data Modeling
• Data Warehouse Data Modeling
• Data Warehouse Physical Model
• Source System of Record
• Extraction/Transformation Program
• Populated Data Warehouse
• Populated Metadata
• End User Access Application
• End User Training
• Ongoing Support Plan

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Data Warehouse Project Scope Document

• VIII Project Planning Assumptions and Issues
• -- Project Assumptions
• -- Project Risks
• -- Project Contingencies
• IX Expected Follow-on Projects

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Summary

• Project management consists of these four
  essential
• elements
• Planning (an iterative process)
• Determining the deliverables
• Estimating efforts and cost
• Projecting the resources
• Organizing
• Assembling the team
• Defining and establishing the structure of
  the team
• Creating a productive environment

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Summary

• Controlling the project
• Monitoring the progress
• Reporting performance and variables
• Adjusting resources
• Leading the project
• Emphasizing human factorsmotivation
• Team spirit Delegation

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Consider the warning signs and success factors
Warning Sign Indication Action
The Data Requirements definition phase is well the target date. Need to write too many in-house programs. Users not cooperating to provide details of data. Suffering from analysis paralysis. Selected third party tools running out of steam. Possible turf concerns over data ownership. Stop the capturing of unwanted inf. Remove any problems by meeting with users. Set firm final target date. If there is time and budget, get different tools. Otherwise increase programming staff. Work with executive sponsor to resolve the issue.
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Consider the warning signs and success factors
(contd)
Warning Sign Indication Action
Users not comfortable with the query tools. Continuing problems with data brought over to the staging area. Users not trained adequately. Data transformation and mapping not complete. First ensure that the selected query tool is appropriate. Then provide additional training. Revise all data transformation and integration routines. Ensure that no data is missing. Include the user representative in the verification process.
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Data Warehouse Project Different From OLTP System
Project
Data Acquisition Data Storage Inf. Delivery
Large Number of sources Many disparate sources Different computing platforms Outside sources High initial load Ongoing data feeds Storage of large data volumes Rapid growth Need for parallel processing Data storage in staging area Multiple index types Several index files Several user types Queries stretched to limits Multiple query types Web-enabled Multidimensional analysis OLAP functionality Metadata management
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Data Warehouse Project Different From OLTP System
Project
Data Acquisition Data Storage Inf. Delivery
Data replication considerations Difficult data integration Complex data transformations Data cleaning Storage of newer data types Archival of old data Compatibility with tools RDBMS MDDBMS Interfaces to DSS applications Feed into data mining Multi-vendor tools
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Major Deployment Activities

• Complete User Acceptance
• Finish final testing of all aspects of user
  interface including system performance.
• Perform Initial Loads
• Load dimension tables followed by the fact
  tables. Create aggregate tables.

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Major Deployment Activities (contd)

• Get User Desktops Ready
• Install all the needed desktop tools. Test
  each client machine.
• Complete Initial User Training
• Train the users on data warehouse concepts,
  relevant contents, and data access tools.

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Major Deployment Activities (contd)

• Institute Initial user Support
• Set up support to assist the users in basic
  usage, answer questions, and hold hands.
• Deploy in stages
• Divide the deployment into manageable stages
  in agreement with users.

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Deploy in Stages

• Top-down approach
• Deploy the overall enterprise data warehouse
  (E-R model) followed by the dependent data marts,
  one by one.
• Bottom-up approach
• Gather departmental requirements, plan and
  deploy the independent data marts, one by one.
• Practical approach
• Deploy the subject data marts (dimensional
  model), one by one, with fully confirmed
  dimensions and facts, according to preplanned
  sequence.

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Considerations for A Pilot
Types of pilot deployment

• Proof-of Technology Intended only to prove new
  technology for IT.
• Comprehensive Test Only intended for IT to test
  all
• infrastructure/architecture.
• Proof-of-concept Small-scale, works with limited
  data, not suitable for integration

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Considerations for A Pilot (contd)

• User tool appreciation Only intended for users
  to test and become familiar with tools.
• Broad Business Early deliverable with broader
  scope, may be integrated.
• Expandable Seed Manageable and simple, but
  designed for integration.