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

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ETL lead developer

Facilitator (not on the BI project team)

Meta data administrator

Project manager

Scribe (not on the BI project team)

Stakeholders (including data owners)

Subject matter expert

Web master

[a]

Steps that can be performed in parallel are boxed together to indicate potential overallocation

of resources, depending on how the roles are assigned (if different overlapping roles are

assigned to the same person).

[b]

Only the roles that perform vital development work are listed. Supporting roles, such as data

owner, IT auditor, network services, technical support, and so on are not listed in this matrix.

[c]

Although all design activities can be started and performed in parallel, the design of the BI

target databases must be finalized before the design of the ETL process can be completed. This

mainly affects the time allocation for the database administrator, who must actively participate

in both steps.

[ Team LiB ]

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[ Team LiB ]

Chapter Eighteen. Entry & Exit Criteria and

Deliverables Matrix

Development Step

Entry Criteria

Exit Criteria

Deliverables

1. Business Case

Assessment

Strategic business

goals of the

organization

Strategic plan for

the overall BI

decision-support

initiative

Objectives of the

BI application

Business problem

or business

opportunity

Unfulfilled

application

requirements from

a prior release

Request for

infrastructure

changes (technical

as well as

nontechnical)

Project endorsement

(from IT and

business executive

management)

Identified business

sponsor (and an

alternate sponsor, if

possible)

Identified business

representative for the

core team

Requirements for the

next release (new

requirements or

those deferred from a

prior release)

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

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2. Enterprise

Infrastructure

Evaluation

Section A. Technical

Infrastructure

Evaluation

Objectives of the

BI application

Statement of the

business problem

or business

opportunity

Project

endorsement

(from IT and

business executive

management)

Identified business

sponsor (and an

alternate sponsor,

if possible)

Request for

technical

infrastructure

changes

Proposed BI

solution

Compatibility issues

and solutions for

them

Product and vendor

evaluations

Licensed (purchased)

products or upgrades

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)

Installation of selected

products

Section B. Nontechnical

Infrastructure

Objectives of the1.

Improved1.

Nontechnical1.

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Infrastructure

Evaluation

BI application

Statement of the

business problem

or business

opportunity

Project

endorsement

(from IT and

business executive

management)

Identified business

sponsor (and an

alternate sponsor,

if possible)

Request for

nontechnical

infrastructure

changes

Proposed BI

solution

nontechnical

infrastructure

Development

guidelines for project

core team

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

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procedure

- Communication

process

3. Project Planning

Objectives of the

BI application

Statement of the

business problem

or business

opportunity

Identified business

sponsor (and an

alternate sponsor,

if possible)

Cost-benefit

analysis

Risk assessment5.

Technical

infrastructure gap

analysis

assessment

Nontechnical

infrastructure gap

analysis

assessment

Requirements for

the next release

(new requirements

or those deferred

from a prior

release)

Identified project

team members and

their levels of

participation

Critical success

factors

Measures of success3.

Approved BI project4.

Approved budget5.

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

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- Roles and

responsibilities

- Team structure

- Communication

plan

- Assumptions

- Constraints

- Risk assessment

- Critical success

factors

Project plan2.

4. Project

Requirements

Definition

Approved BI

project

Project charter2.

Project plan3.

Identified business

sponsor (and an

alternate sponsor,

if possible)

Business (process)

ownership defined

Unfulfilled

requirements from

previous BI

project

New requirements7.

Request for

infrastructure

changes (technical

as well as

nontechnical)

Critical success

factors

Measures of

success

10.

Detailed project

requirements (data

and process)

Detailed

infrastructure

requirements

(technical as well as

nontechnical)

Selected internal and

external data sources

(operational files and

databases)

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

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5. Data Analysis

Approved project1.

Project charter2.

Project plan3.

Business (process)

ownership defined

Data ownership

defined

Full-time

availability of

business

representative,

part-time

availability of

other business

people, especially

data owners

Trained data

modeler

Application

requirements

document with

detailed project

requirements

High-level logical

data model (if

available)

List of data

elements as well

as source files and

source databases

10.

Logically integrated

data view from a

business perspective

Source data quality

assessment

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

Normalized and fully

attributed logical data

model (project-specific)

with:

- Kernel entities

- Associative

entities

- Characteristic

entities

- Cardinality and

optionality

- Unique

identifiers

- Attributes

Business meta data:

- Data names and

definitions

- Data

relationships

- Unique

identifiers

- Data types and

lengths

- Domains

- Business rules

and policies

- Data ownership

Data-cleansing

specifications

Expanded enterprise

logical data model

[*]

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6. Application

Prototyping

Project charter1.

Project plan2.

Application

requirements

document with

detailed project

requirements

Approval for

prototyping

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

tools)

Full-time

availability of

business

representative,

part-time

availability of

other business

people

Gap analysis of

reporting needs and

current reporting

capabilities

Justification, benefits,

and feasibility for BI

application

Tool demo and

verified tool

functionality

Decision whether to

license (buy) a new

access and analysis

tool (OLAP, report

writer)

OLAP (or report

writer) product and

vendor evaluation

Installation of OLAP

tool (or report writer)

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)

Completed prototype2.

Revised application

requirements document

with detailed project

requirements (data and

functions)

Skills survey matrix4.

Issues log5.

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7. Meta Data

Repository Analysis

Approved meta

data repository

project

Requirements for

a new meta data

repository or for

new functionality

of the existing

meta data

repository

Requirements for

new meta data

components

Gap analysis of

meta data already

available versus

meta data needed

and not available

Identified new meta

data repository

functionality

Mapping between

business meta data

and technical meta

data

Updates to the

revised application

requirements

document with

detailed meta data

repository

requirements

Logical meta model

(new or enhanced)

showing:

- Kernel entities

- Associative

entities

- Characteristic

entities

- Relationships

- Cardinality and

optionality

- Unique

identifiers

- Attributes

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

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8. Database Design

Revised

application

requirements

document with

detailed project

requirements

(data and

functions)

List of data

elements as well

as source files and

source databases

Normalized and

fully attributed

logical data model

(project-specific)

Expanded

enterprise logical

data model

Standardized

business meta

data

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

Physical data model:

- Tables and

columns

- Primary and

foreign keys

- Cardinality

- Referential

integrity rules

- Indices

Physical design of BI

target databases:

- Dataset

placement

- Index placement

- Partitioning

- Clustering

- Indexing

Data definition

language (DDL)

Data control language

(DCL)

Physical BI target

databases

Database maintenance

procedures

Extract/Transform/Load

Design

Revised

application

requirements

document with

detailed project

requirements

(data and

functions)

List of data

elements as well

as source files and

source databases

Expected

performance of ETL

process

Identified meta data

to be produced by

the ETL process:

- Load statistics

- Data quality

metrics

Source-to-target

mapping document with

transformation

specifications for:

- Data

transformations

- Data cleansing

- Referential

integrity checking

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