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

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3. Improve the

nontechnical infrastructure

Create time estimates for

creating or modifying

new standards,

guidelines, and

procedures

Change the guidelines for

using the development

methodology before the

BI project begins, if

necessary

Modify the roles and

responsibilities before

the BI project begins, if

necessary

Create new processes as

needed, or modify any

process that appears to

be inadequate or not

working

3. Project Planning

1. Determine the project

requirements

Define data requirements

Define functional

requirements (reports,

queries, online help

function)

Define infrastructure

requirements (technical

and nontechnical)

Expand or create the

high-level logical data

model

Validate the

requirements with other

business people

Obtain sponsor approval

for the requirements

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2. Determine the condition

of the source files and

databases

Review the content of

each potential source file

and source database

(internal and external)

Assess source data

violations to the:

- Technical data

conversion rules

- Business data

domain rules

- Business data

integrity rules

Determine which data

elements are critical to

the business, which are

important (but not

critical), and which are

insignificant

Estimate how long it

would take to cleanse the

critical source data

elements and extrapolate

an estimate (make an

educated guess) for

cleansing the important

source data elements

Review data-cleansing

estimates with the

business sponsor and

have the business

sponsor prioritize the

cleansing effort

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3. Determine or revise the

cost estimates

Review the technical

infrastructure

assessment report

Review the nontechnical

infrastructure

assessment report

Review the project

requirements

Review the project

constraints (time, scope,

budget, resources,

quality)

Review the need for

consulting, contracting,

and training

Revise the original cost

estimates, if necessary

4. Revise the risk

assessment

Review and revise the

original risk assessment

matrix

For every risk, determine

the likelihood of it

materializing: low,

medium, high

Determine the impact of

every risk: low, medium,

high

Define triggers

(indications that a risk is

about to materialize)

Define a risk mitigation

plan, listing actions to

prevent or circumvent

each risk

Define a contingency

plan, listing alternative

actions to take when a

risk materializes

Identify your

assumptions because

they may become risks

Include assumptions in

the contingency plan (list

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alternatives)

Review the project

constraints (time, scope,

budget, resources,

quality) as they relate to

risk

5. Identify critical success

factors

Define the success

criteria for the BI project

(what would be

considered a "success")

Determine critical

success factors (what

must be in place in order

for the project to meet

the success criteria)

Review critical success

factors with the business

sponsor

Obtain agreement and

cooperation on the

critical success factors

from the business

sponsor (for example,

provide one full-time

business representative

for the project)

6. Prepare the project

charter

Write the project charter

with information about

the BI project collected

up to this point:

- Purpose and

reason for the BI

project

- Costs and

benefits

- Infrastructure

and business

process

improvements

- High-level scope

(data and

functions)

- Items not in the

scope (originally

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requested but

subsequently

excluded from the

scope)

- Expectations from

the business

people in terms of

availability,

security, response

time

(performance),

data cleanliness,

ongoing support

- Team structure,

roles, and

responsibilities

- Risks,

assumptions, and

constraints

- Critical success

factors

7. Create a high-level

project plan

Create a work breakdown

structure (list of

appropriate tasks)

Determine base

estimates for all tasks

(using estimates

provided by the team

members who will do the

work)

Identify task

dependencies

Revise the base

estimates for assigned

resources, based on:

- Skill level

- Subject matter

expertise

- Additional

administrative

activities

- Non-work-related

activities

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Identify resource

dependencies (resource

leveling)

Create a critical path

method (CPM) or Pert

chart

Create a Gantt chart

8. Kick off the project

Prepare an agenda for

the kickoff meeting

Call a kickoff meeting

(include the business

sponsor and the business

representative)

Assign roles and

responsibilities to core

team members

Identify extended team

members and review

their responsibilities

Discuss the project

charter

Walk through the project

plan

Discuss the concept of

self-organizing teams

(core team members

monitoring and

redistributing [sharing]

their workload)

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4. Project Requirements

Definition

1. Define the requirements

for technical infrastructure

enhancements

Define the requirements

for additional hardware

Define the requirements

for additional middleware

Define the requirements

for a new DBMS or

upgrades to the existing

DBMS

Define the requirements

for the network or

upgrades to it

Define the security

requirements and decide

whether to buy a security

package

Define the requirements

for development tools

(CASE, ETL)

Define the requirements

for data access and

reporting tools (OLAP,

report writers)

Define the requirements

for a new data mining

tool

Determine whether to

license (buy) or custom

build a meta data

repository

If a meta data repository

already exists, determine

how to enhance it

2. Define the requirements

for nontechnical

infrastructure

enhancements

Define the requirements

for creating or changing

standards, guidelines,

and procedures for:

- Governance

standards and

procedures for

prioritizing

requirements and

deliverables

(functions, data,

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meta data)

- Use of the

development

methodology

- Estimating

guidelines

- Scope

management

(change control)

process

- Issues

management

process

- Roles and

responsibilities

- Security process

- Meta data

capture and

delivery process

- Logical data

modeling

- Data quality

measures and

triage process

- Testing process

- SLA process

- Support functions

- Dispute

resolution process

- Communication

process

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3. Define the reporting

requirements

Collect or create sample

report layouts

Collect or create sample

queries

Define business rules for

the reports

Define aggregation and

summarization rules

Define reporting

dimensions

Define query libraries

Identify stewards of the

libraries

Get samples of the types

of ad hoc queries the

business analysts may

want to write

Define access interfaces

(GUI front end, Web

display, portal)

4. Define the requirements

for source data

Define all source data

elements (for reporting

dimensions, for report

fields, for queries, for

data mining)

Classify data elements as

critical, important,

insignificant

Define the data domains

(allowable values)

Define the significant and

obvious business rules

for the data

Analyze the source files

and source databases in

more detail to determine

data-cleansing

requirements

Define the historical data

requirements (how much

history to load and from

how many years back, or

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accumulate history from

this point forward)

5. Review the project

scope

Compare the detailed

project requirements to

the high-level scope in

the project charter

Review the project

constraints (time, scope,

budget, resources,

quality)

Determine whether the

scope is still realistic

under those constraints

Renegotiate the scope, if

necessary

Create a change-control

document for managing

changes to the

requirements

Create an issues log for

tracking and resolving

issues

6. Expand the logical data

model

Add newly discovered

entities and their

relationships to the high-

level (conceptual) logical

data model

Refine the logical data

model by resolving the

many-to-many

relationships

Add unique identifiers to

each entity

Attribute the logical data

model with critical data

elements

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