Moss L.T., Atre S. Business intelligence roadmap: The complete project lifecycle for decision-support applications

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(both internal and

external)

Business meta

data

Data-cleansing

specifications

Physical BI target

databases

- Reconciliation

totals

Decision whether to

license (buy) an ETL

tool

ETL product and

vendor evaluation

Installation of ETL

tool

- Reconciliation

and error

handling

- Algorithms for

aggregations and

summarizations

ETL process flow

diagram showing

process dependencies

among:

- Program

modules

- Temporary and

permanent work

files and tables

- Sort, merge,

and load utilities

ETL program design

document for three sets

of ETL programs:

- Initial load

- Historical load

- Incremental

load

Staging area with:

- Program

libraries

- Allocated disk

space for

temporary and

permanent work

files and tables

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10. Meta Data

Repository Design

Revised

application

requirements

document with

detailed meta data

repository

requirements

New or enhanced

logical meta

model for the

meta data

repository

Identified new

meta data

repository

functionality

Mapping (link)

between business

meta data and

technical meta

data

New or enhanced

meta data repository

design

Decision whether to

license (buy) or build

a meta data

repository

Meta data repository

product and vendor

evaluation

Installation of meta

data repository

product

Physical meta model:

- Tables and

columns

- Primary and

foreign keys

- Cardinality

- Referential

integrity rules

DDL for the meta data

repository

DCL for the meta data

repository

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

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11.

Extract/Transform/Load

Development

Source-to-target

mapping

document

ETL process flow

diagram showing

process

dependencies

ETL program

design document

Staging area4.

Fully functioning ETL

process

Fully tested ETL

programs or ETL tool

modules:

- Integration

tested or

regression

tested

- Performance

tested

- Quality

assurance

tested

- Acceptance

tested

ETL test plan with test

cases

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)

ETL program library

with fully functioning

ETL programs and

scripts (or ETL tool

library with fully

functioning ETL tool

modules)

12. Application

Development

Completed

prototype with

partial application

functionality

(optional)

Revised

application

requirements

document with

detailed project

requirements

(data and

functions)

Sample reports

that currently

exist and are

actively used

Sample mock-up

report layouts for

new reports

New or existing

tools (report

writers and query

Fully functioning

access and analysis

components of the BI

application

(application

programs)

Fully tested

application programs

or OLAP functions:

- Integration or

regression

tested

- Performance

tested

- Quality

assurance

tested

- Acceptance

tested

Application design

document containing:

- Report layouts

- Screen designs

- Interface

designs

- Programming

specs

- Calculations for

reports and

queries

- Online help

function

Application test plan

with test cases

Application programs or

OLAP functions for the

access and analysis

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writers and query

tools)

Physical BI target

databases

components of the BI

application

Application program

library with fully

functioning application

programs and scripts

(or OLAP tool library

with fully functioning

OLAP tool modules)

Training materials:

- Presentation

slides

- Instructor notes

- Student

workbooks

- Exercises and

their solutions

- Other pertinent

handouts

13. Data Mining

Approved data

mining initiative

Objectives of the

BI application

Statement of the

business problem

or business

opportunity

Identified business

sponsor (and an

alternate sponsor,

if possible)

Data mining

activities of the

competition

Dedicated data

mining expert

(statistician) to

interpret the data

mining results

Data mining tool7.

Requirements for

pattern discovery in

the data

Data mining

algorithms and

operations

Plan for measuring

the results of data

mining activities

Knowledge discovery

from data mining

New marketing

strategies to:

- Increase

revenue

- Increase

profit

- Decrease

costs

- Increase

Data mining database1.

Analytical data model2.

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market share

- Increase

customer

satisfaction

New business

strategies based on

knowledge discovery

14. Meta Data

Repository

Development

Physical meta

model (database

design) for the

meta data

repository

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

Fully functioning

meta data repository

Fully tested meta

data repository

programs or meta

data repository

product modules:

- Integration or

regression

tested

- Acceptance

tested (and

quality

assurance

tested)

Physical meta data

repository database

Meta data repository

test plan with test cases

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

Meta data repository

program library with

fully functioning meta

data repository

programs and scripts

(or fully functioning

meta data repository

product modules)

Meta data repository

production

documentation:

- Operating

procedure

- Reference guide

Meta data repository

training materials

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- Presentation

slides

- Instructor notes

- Student

workbooks

- Exercises and

their solutions

- Other pertinent

handouts

15. Implementation

ETL programs or

instructions for the

ETL tool

Application

programs (access

and analysis) or

OLAP functions

Meta data

repository

programs or meta

data repository

product functions

Physical BI target

databases

Physical meta data

repository

database

Fully functioning

production ETL

process

Fully functioning

production BI

application

Fully functioning

production meta data

repository process

Metrics for measuring

success

Production ETL program

library with fully

functioning ETL

programs and scripts

Production application

program library with

fully functioning

application programs

(access and analysis)

Production meta data

repository program

library with fully

functioning meta data

repository programs

Production BI target

databases fully

populated with initial

and historical source

data

Production meta data

repository database

populated with business

meta data, technical

meta data, and ETL

meta data (load

statistics, reconciliation

totals, data quality

metrics)

Production

documentation:

- Operating

procedures

- Reference

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guides

16. Release Evaluation

Project charter1.

Project plan2.

Issues log3.

Availability of all

project team

members

Measurements for:

- Data

quality

- Ease of use

- Training

effectiveness

- Business

satisfaction

Performance

- Return on

investment

Honest

observations and

assessments of

project

development

approach

Suggestions for

improvement

Evaluation of

business satisfaction

Lessons learned2.

Process improvement

items

Repeatable success4.

Post-implementation

review agenda listing:

- Date and time of

the meeting

- Place of the

meeting

- Invited

attendees

- Topics for

review

- Questions to be

discussed

Post-implementation

review meeting minutes

recording:

- Highlights of

discussions

- Suggestions and

resolutions of

agenda topics

Action item list3.

[*]

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

[ Team LiB ]

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[ Team LiB ]

Chapter Nineteen. Activity Dependency

Matrix

Development Step

Activities

1. Business Case

Assessment

2. Enterprise

Infrastructure

Evaluation

Section A.

Technical

Infrastructure

Evaluation

Section B.

Nontechnical

Infrastructure

Evaluation

3. Project Planning

4. Project

Requirements

Definition

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5. Data Analysis

6. Application

Prototyping

7. Meta Data

Repository Analysis

8. Database Design

Extract/Transform/Load

Design

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10. Meta Data

Repository Design

11.

Extract/Transform/Load

Development

12. Application

Development

13. Data Mining

14. Meta Data

Repository

Development

15. Implementation

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