Chapter Eighteen. Entry Exit Criteria and Deliverables Matrix


Chapter Eighteen. Entry & Exit Criteria and Deliverables Matrix

Development Step

Entry Criteria

Exit Criteria

Deliverables

1. Business Case Assessment

  1. Strategic business goals of the organization

  2. Strategic plan for the overall BI decision-support initiative

  3. Objectives of the BI application

  4. Business problem or business opportunity

  5. Unfulfilled application requirements from a prior release

  6. Request for infrastructure changes (technical as well as nontechnical)

  1. Project endorsement (from IT and business executive management)

  2. Identified business sponsor (and an alternate sponsor, if possible)

  3. Identified business representative for the core team

  4. Requirements for the next release (new requirements or those deferred from a prior release)

  1. Business case assessment report documenting:

    - Executive summary

    - Strategic business goals of the organization

    - Objectives of the proposed BI application

    - Statement of the business need (business problem or business opportunity)

    - Explanation of how the BI application will satisfy that need

    - Ramifications for not addressing the business need and not committing to the proposed BI solution

    - Cost-benefit analysis results

    - Risk assessment

    - Recommendations

2. Enterprise Infrastructure Evaluation

     

Section A. Technical Infrastructure Evaluation

  1. Objectives of the BI application

  2. Statement of the business problem or business opportunity

  3. Project endorsement (from IT and business executive management)

  4. Identified business sponsor (and an alternate sponsor, if possible)

  5. Request for technical infrastructure changes

  6. Proposed BI solution

  1. Compatibility issues and solutions for them

  2. Product and vendor evaluations

  3. Licensed (purchased) products or upgrades

  1. Technical infrastructure assessment report, covering:

    - Servers and operating systems

    - Client workstations

    - Middleware ( especially DBMS gateways)

    - Custom interfaces

    - Network components

    - Bandwidth

    - DBMS functionality and utilities (backup and recovery, performance monitoring)

    - Development tools (ETL, OLAP)

    - Meta data repository

    - Product evaluation scores

    - Vendor evaluation scores

    - Recommendations for product licensing (purchase)

  2. Installation of selected products

Section B. Nontechnical Infrastructure Evaluation

  1. Objectives of the BI application

  2. Statement of the business problem or business opportunity

  3. Project endorsement (from IT and business executive management)

  4. Identified business sponsor (and an alternate sponsor, if possible)

  5. Request for nontechnical infrastructure changes

  6. Proposed BI solution

  1. Improved nontechnical infrastructure

  2. Development guidelines for project core team

  1. Nontechnical infrastructure assessment report with proposed improvements to:

    - Standards

    - Use of a development methodology

    - Estimating guidelines

    - Scope management (change control) procedure

    - Issues management procedure

    - Roles and responsibilities

    - Security process

    - Meta data capture and delivery process (business and technical meta data)

    - Process for merging logical data models into a single enterprise view

    - Data quality measures and triage process

    - Testing standards and procedures

    - Service-level agreements

    - Support function

    - Dispute resolution procedure

    - Communication process

3. Project Planning

  1. Objectives of the BI application

  2. Statement of the business problem or business opportunity

  3. Identified business sponsor (and an alternate sponsor, if possible)

  4. Cost-benefit analysis

  5. Risk assessment

  6. Technical infrastructure gap analysis assessment

  7. Nontechnical infrastructure gap analysis assessment

  8. Requirements for the next release (new requirements or those deferred from a prior release)

  1. Identified project team members and their levels of participation

  2. Critical success factors

  3. Measures of success

  4. Approved BI project

  5. Approved budget

  1. Project charter with the sections:

    - Goals and objectives

    - Statement of the business problem

    - Proposed BI solution

    - Results from the cost-benefit analysis

    - Results from the infrastructure gap analysis (technical and nontechnical)

    - Functional project deliverables

    - Historical requirements

    - Subject area to be delivered

    - High-level logical data model

    - Items not in scope (originally requested but subsequently excluded)

    - Condition of source files and databases

    - Availability and security requirements

    - Access tool requirements

    - Roles and responsibilities

    - Team structure

    - Communication plan

    - Assumptions

    - Constraints

    - Risk assessment

    - Critical success factors

  2. Project plan

4. Project Requirements Definition

  1. Approved BI project

  2. Project charter

  3. Project plan

  4. Identified business sponsor (and an alternate sponsor, if possible)

  5. Business (process) ownership defined

  6. Unfulfilled requirements from previous BI project

  7. New requirements

  8. Request for infrastructure changes (technical as well as nontechnical)

  9. Critical success factors

  10. Measures of success

  1. Detailed project requirements (data and process)

  2. Detailed infrastructure requirements (technical as well as nontechnical)

  3. Selected internal and external data sources (operational files and databases)

  1. Application requirements document, with the following sections:

    - Technical infrastructure requirements

    - Nontechnical infrastructure requirements

    - Reporting requirements

    - Ad hoc and canned query requirements

    - Requirements for source data, including history

    - High-level logical data model

    - Data-cleansing requirements

    - Security requirements

    - Preliminary service-level agreements

5. Data Analysis

  1. Approved project

  2. Project charter

  3. Project plan

  4. Business (process) ownership defined

  5. Data ownership defined

  6. Full-time availability of business representative, part-time availability of other business people, especially data owners

  7. Trained data modeler

  8. Application requirements document with detailed project requirements

  9. High-level logical data model (if available)

  10. List of data elements as well as source files and source databases

  1. Logically integrated data view from a business perspective

  2. Source data quality assessment

  3. Standardized business meta data for:

    - Data names

    - Data definitions

    - Data relationships

    - Data identifiers

    - Data types

    - Data lengths

    - Data content (domain)

    - Data rules

    - Data policies

    - Data ownership

  1. Normalized and fully attributed logical data model ( project-specific ) with:

    - Kernel entities

    - Associative entities

    - Characteristic entities

    - Cardinality and optionality

    - Unique identifiers

    - Attributes

  2. Business meta data:

    - Data names and definitions

    - Data relationships

    - Unique identifiers

    - Data types and lengths

    - Domains

    - Business rules and policies

    - Data ownership

  3. Data-cleansing specifications

  4. Expanded enterprise logical data model [*]

6. Application Prototyping

  1. Project charter

  2. Project plan

  3. Application requirements document with detailed project requirements

  4. Approval for prototyping

  5. Sample reports that currently exist and are actively used

  6. Sample mock-up report layouts for new reports

  7. New or existing tools (report writers and query tools)

  8. Full-time availability of business representative, part-time availability of other business people

  1. Gap analysis of reporting needs and current reporting capabilities

  2. Justification, benefits, and feasibility for BI application

  3. Tool demo and verified tool functionality

  4. Decision whether to license (buy) a new access and analysis tool (OLAP, report writer)

  5. OLAP (or report writer) product and vendor evaluation

  6. Installation of OLAP tool (or report writer)

  1. Prototype charter with the following sections:

    - Primary purpose for the prototype (what requirement is being prototyped and why)

    - Prototype objectives (what type of prototype will be used, what will be proven or tested )

    - Prototype participants (IT and business people)

    - Data to be used for the prototype

    - Hardware and software platforms for the prototype

    - Measures of success (how you will know it was worth it)

    - Application interface agreement (standards, skills, ease of use)

  2. Completed prototype

  3. Revised application requirements document with detailed project requirements (data and functions)

  4. Skills survey matrix

  5. Issues log

7. Meta Data Repository Analysis

  1. Approved meta data repository project

  2. Requirements for a new meta data repository or for new functionality of the existing meta data repository

  3. Requirements for new meta data components

  4. Gap analysis of meta data already available versus meta data needed and not available

  1. Identified new meta data repository functionality

  2. Mapping between business meta data and technical meta data

  3. Updates to the revised application requirements document with detailed meta data repository requirements

  1. Logical meta model (new or enhanced) showing:

    - Kernel entities

    - Associative entities

    - Characteristic entities

    - Relationships

    - Cardinality and optionality

    - Unique identifiers

    - Attributes

  2. Meta-meta data:

    - Meta data names

    - Meta data definitions

    - Meta data relationships

    - Unique identifiers

    - Types and lengths

    - Domains

    - Business rules and policies

    - Meta data ownership

8. Database Design

  1. Revised application requirements document with detailed project requirements (data and functions)

  2. List of data elements as well as source files and source databases

  3. Normalized and fully attributed logical data model (project-specific)

  4. Expanded enterprise logical data model

  5. Standardized business meta data

  1. Database design schema:

    Entity-relationship design for:

    - Operational data store (ODS)

    - Enterprise data warehouse (EDW)

    - Data marts with detailed data for ad hoc reporting

    Multidimensional design for:

    - Data marts with aggregations and summarizations

    - Oper marts (operational data marts for patterned reporting)

    - Web warehouse with summarized click-stream data

  1. Physical data model:

    - Tables and columns

    - Primary and foreign keys

    - Cardinality

    - Referential integrity rules

    - Indices

  2. Physical design of BI target databases:

    - Dataset placement

    - Index placement

    - Partitioning

    - Clustering

    - Indexing

  3. Data definition language (DDL)

  4. Data control language (DCL)

  5. Physical BI target databases

  6. Database maintenance procedures

9. Extract/Transform/Load Design

  1. Revised application requirements document with detailed project requirements (data and functions)

  2. List of data elements as well as source files and source databases (both internal and external)

  3. Business meta data

  4. Data-cleansing specifications

  5. Physical BI target databases

  1. Expected performance of ETL process

  2. Identified meta data to be produced by the ETL process:

    - Load statistics

    - Data quality metrics

    - Reconciliation totals

  3. Decision whether to license (buy) an ETL tool

  4. ETL product and vendor evaluation

  5. Installation of ETL tool

  1. Source-to-target mapping document with transformation specifications for:

    - Data transformations

    - Data cleansing

    - Referential integrity checking

    - Reconciliation and error handling

    - Algorithms for aggregations and summarizations

  2. ETL process flow diagram showing process dependencies among:

    - Program modules

    - Temporary and permanent work files and tables

    - Sort, merge, and load utilities

  3. ETL program design document for three sets of ETL programs:

    - Initial load

    - Historical load

    - Incremental load

  4. Staging area with:

    - Program libraries

    - Allocated disk space for temporary and permanent work files and tables

10. Meta Data Repository Design

  1. Revised application requirements document with detailed meta data repository requirements

  2. New or enhanced logical meta model for the meta data repository

  3. Identified new meta data repository functionality

  4. Mapping (link) between business meta data and technical meta data

  1. New or enhanced meta data repository design

  2. Decision whether to license (buy) or build a meta data repository

  3. Meta data repository product and vendor evaluation

  4. Installation of meta data repository product

  1. Physical meta model:

    - Tables and columns

    - Primary and foreign keys

    - Cardinality

    - Referential integrity rules

  2. DDL for the meta data repository

  3. DCL for the meta data repository

  4. Meta data repository programming specifications for:

    - Meta data extract and transformation programs

    - Meta data load programs

    - Tool interfaces

    - Meta data reports and queries

    - Access interfaces

    - Online help function

11. Extract/Transform/Load Development

  1. Source-to-target mapping document

  2. ETL process flow diagram showing process dependencies

  3. ETL program design document

  4. Staging area

  1. Fully functioning ETL process

  2. Fully tested ETL programs or ETL tool modules:

    - Integration tested or regression tested

    - Performance tested

    - Quality assurance tested

    - Acceptance tested

  1. ETL test plan with test cases

  2. ETL programs or instructions for the ETL tool to:

    - Extract source data

    - Transform source data

    - Load data into BI target databases (unless a DBMS utility is used)

  3. ETL program library with fully functioning ETL programs and scripts (or ETL tool library with fully functioning ETL tool modules)

12. Application Development

  1. Completed prototype with partial application functionality (optional)

  2. Revised application requirements document with detailed project requirements (data and functions)

  3. Sample reports that currently exist and are actively used

  4. Sample mock-up report layouts for new reports

  5. New or existing tools (report writers and query tools)

  6. Physical BI target databases

  1. Fully functioning access and analysis components of the BI application (application programs)

  2. Fully tested application programs or OLAP functions:

    - Integration or regression tested

    - Performance tested

    - Quality assurance tested

    - Acceptance tested

  1. Application design document containing:

    - Report layouts

    - Screen designs

    - Interface designs

    - Programming specs

    - Calculations for reports and queries

    - Online help function

  2. Application test plan with test cases

  3. Application programs or OLAP functions for the access and analysis components of the BI application

  4. Application program library with fully functioning application programs and scripts (or OLAP tool library with fully functioning OLAP tool modules)

  5. Training materials:

    - Presentation slides

    - Instructor notes

    - Student workbooks

    - Exercises and their solutions

    - Other pertinent handouts

13. Data Mining

  1. Approved data mining initiative

  2. Objectives of the BI application

  3. Statement of the business problem or business opportunity

  4. Identified business sponsor (and an alternate sponsor, if possible)

  5. Data mining activities of the competition

  6. Dedicated data mining expert (statistician) to interpret the data mining results

  7. Data mining tool

  1. Requirements for pattern discovery in the data

  2. Data mining algorithms and operations

  3. Plan for measuring the results of data mining activities

  4. Knowledge discovery from data mining

  5. New marketing strategies to:

    - Increase revenue

    - Increase profit

    - Decrease costs

    - Increase market share

    - Increase customer satisfaction

  6. New business strategies based on knowledge discovery

  1. Data mining database

  2. Analytical data model

14. Meta Data Repository Development

  1. Physical meta model (database design) for the meta data repository

  2. Meta data repository program specifications for:

    - Populating the meta data repository

    - Access and tool interfaces to the meta data repository

    - Reporting from the meta data repository

    - Online help function for the meta data repository

  1. Fully functioning meta data repository

  2. Fully tested meta data repository programs or meta data repository product modules:

    - Integration or regression tested

    - Acceptance tested (and quality assurance tested)

  1. Physical meta data repository database

  2. Meta data repository test plan with test cases

  3. Meta data repository programs or meta data repository product functions for:

    - Meta data migration process (including tool interfaces)

    - Meta data application (including access interfaces)

    - Meta data repository online help function

  4. Meta data repository program library with fully functioning meta data repository programs and scripts (or fully functioning meta data repository product modules)

  5. Meta data repository production documentation:

    - Operating procedure

    - Reference guide

  6. Meta data repository training materials

    - Presentation slides

    - Instructor notes

    - Student workbooks

    - Exercises and their solutions

    - Other pertinent handouts

15. Implementation

  1. ETL programs or instructions for the ETL tool

  2. Application programs (access and analysis) or OLAP functions

  3. Meta data repository programs or meta data repository product functions

  4. Physical BI target databases

  5. Physical meta data repository database

  1. Fully functioning production ETL process

  2. Fully functioning production BI application

  3. Fully functioning production meta data repository process

  4. Metrics for measuring success

  1. Production ETL program library with fully functioning ETL programs and scripts

  2. Production application program library with fully functioning application programs (access and analysis)

  3. Production meta data repository program library with fully functioning meta data repository programs

  4. Production BI target databases fully populated with initial and historical source data

  5. Production meta data repository database populated with business meta data, technical meta data, and ETL meta data (load statistics, reconciliation totals, data quality metrics)

  6. Production documentation:

    - Operating procedures

    - Reference guides

16. Release Evaluation

  1. Project charter

  2. Project plan

  3. Issues log

  4. Availability of all project team members

  5. Measurements for:

    - Data quality

    - Ease of use

    - Training effectiveness

    - Business satisfaction

    - Performance

    - Return on investment

  6. Honest observations and assessments of project development approach

  7. Suggestions for improvement

  1. Evaluation of business satisfaction

  2. Lessons learned

  3. Process improvement items

  4. Repeatable success

  1. Post-implementation review agenda listing:

    - Date and time of the meeting

    - Place of the meeting

    - Invited attendees

    - Topics for review

    - Questions to be discussed

  2. Post-implementation review meeting minutes recording:

    - Highlights of discussions

    - Suggestions and resolutions of agenda topics

  3. Action item list

[*] Note: This deliverable is typically created by data administration behind the scenes of the BI project.



Business Intelligence Roadmap
Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications
ISBN: 0201784203
EAN: 2147483647
Year: 2003
Pages: 202

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