Task_Data


ID

Task_Name

Predecessors

1

Your Project Name

 

2

Step 1: Business Case Assessment

 

3

Determine the business need

 

4

Identify the business need

 

5

Determine current financial consequences of the business need

 

6

Assess the current decision-support system (DSS) solutions

3

7

Assess current usage of the existing DSS

 

8

Determine the shortcomings of the existing DSS

 

9

Perform gap analysis

 

10

Assess the operational sources and procedures

3

11

Assess the data quality of operational systems

 

12

Review file structures and databases

 

13

Review content (domain) of source data elements

 

14

Assess the current data movement

 

15

Review data entry practices

 

16

Review data extraction practices

 

17

Review data manipulation practices

 

18

Review data duplication practices

 

19

Assess current operational procedures

 

20

Identify poor data entry practices

 

21

Identify lack of edit checks

 

22

Identify defective program code

 

23

Identify lack of training

 

24

Assess the competitors ' BI decision-support initiatives

3

25

Determine the competitors' successes and failures

 

26

Determine whether competitors gained market advantages

 

27

Determine the BI application objectives

6, 10, 24

28

Identify the strategic business goals of the organization

 

29

Define the overall BI decision-support objectives

 

30

Define the project-specific BI application objectives

 

31

Match the overall BI decision-support objectives to the strategic business goals

 

32

Match the project-specific BI application objectives to the strategic business goals

 

33

Propose a BI solution

27

34

Review current DSS solutions

 

35

Review DSS gap analysis

 

36

Determine how the BI application will lessen the business pain

 

37

Create a high-level architecture for the proposed BI solution

 

38

Consolidate and prioritize unfulfilled requirements from previous BI projects

 

39

Create a high-level (conceptual) logical data model

 

40

Perform a cost-benefit analysis

27

41

Determine costs

 

42

Determine benefits ( tangible and intangible)

 

43

Identify short- term benefits to the organization

 

44

Identify long-term benefits to the organization

 

45

Calculate the projected return on investment (ROI)

41, 42

46

Perform a risk assessment

27

47

Create a risk assessment matrix

 

48

List the technology risks

 

49

List the complexity risks

 

50

List the integration risks

 

51

List the organization risks

 

52

List the project team risks

 

53

List the financial investment risks

 

54

Assign weights to the risks

47

55

Rank the risks: low, medium, or high

54

56

Determine the risks ( ramifications ) of not implementing a BI solution

54

57

Write the assessment report

33, 40, 46

58

Describe the business need

 

59

Describe lost opportunities

 

60

Describe the proposed BI solution

 

61

State the cost justification and expected ROI

 

62

Include risk assessment results

 

63

Write recommendations (include operational business process improvements)

 

64

Obtain project approval from business sponsor

57

65

Step 2: Enterprise Infrastructure Evaluation

 

66

Section A: Technical Infrastructure Evaluation

 

67

Assess the existing platform

64

68

Review hardware

 

69

Review operating systems

 

70

Review middleware, especially DBMS gateways

 

71

Review custom interfaces

 

72

Review network components and bandwidth

 

73

Review the DBMS

 

74

Review tools (CASE, ETL, OLAP, etc.)

 

75

Review the meta data repository

 

76

Perform gap analysis

 

77

Evaluate and select new products

64

78

Identify the product categories you need to evaluate (hardware, DBMS, tools)

 

79

List all products being considered for each category

 

80

Itemize your requirements for the products

 

81

Weigh each product requirement (scale of 1 to 10)

 

82

Rank each product against the weighted requirements (scale of 0 to 10)

81

83

Determine the total score for each product

82

84

List all vendors of all products

 

85

Itemize your requirements for the vendors

 

86

Weigh each vendor requirement (scale of 1 to 10)

 

87

Rank each vendor against the weighted requirements (scale of 0 to 10)

86

88

Determine the total score for each vendor

87

89

Evaluate the product scores and vendor scores

83, 88

90

Create a short list of products and vendors in each category

89

91

Have the products demonstrated by the vendors

90

92

Choose the final product in each product category

91

93

Obtain business sponsor approval to license the products

92

94

Write the technical infrastructure assessment report

67, 77

95

Itemize findings about servers, operating systems, middleware, etc.

 

96

List the weighted requirements

 

97

List the product scores

 

98

List the vendor scores

 

99

List the product costs

 

100

List the products on the short list

 

101

Explain the rationale for selecting or rejecting products

 

102

Explain the final selection criteria

 

103

Write the executive summary

 

104

Expand the current platform

94

105

Order new products

 

106

Install new products

105

107

Test new products

106

108

Train technical staff on new products

106

109

Section B: Nontechnical Infrastructure Evaluation

 

110

Assess the effectiveness of existing nontechnical infrastructure components

57

111

Review standards for data naming, abbreviations, modeling, etc.

 

112

Review the use of the development methodology

 

113

Review estimating guidelines

 

114

Review change-control procedures

 

115

Review issues management procedures

 

116

Review roles and responsibilities

 

117

Review security processes and guidelines

 

118

Review meta data capture and delivery processes

 

119

Review meta data repository functionality

 

120

Review the process for merging logical data models into the enterprise data model

 

121

Review data quality measures and the cleansing triage process

 

122

Review the service-level agreement (SLA) process

 

123

Review the BI support function

 

124

Review the dispute resolution process

 

125

Review the communication process

 

126

Perform gap analysis

 

127

Write the nontechnical infrastructure assessment report

110

128

Itemize findings about inadequate standards, guidelines, procedures, etc.

 

129

Write recommendations for nontechnical infrastructure changes

 

130

Prioritize nontechnical infrastructure requirements for the BI project

 

131

Prioritize nontechnical infrastructure requirements for outside the BI project

 

132

Write the executive summary

 

133

Improve the nontechnical infrastructure

127

134

Create time estimates for creating or modifying new standards, guidelines, procedures

 

135

Change the guidelines for using the development methodology

 

136

Modify the roles and responsibilities

 

137

Create new processes as needed

 

138

Step 3: Project Planning

 

139

Determine the project requirements

94, 127

140

Define data requirements

 

141

Define functional requirements ( reports , queries, online help function)

 

142

Define infrastructure requirements (technical and nontechnical)

 

143

Expand or create the high-level logical data model

140

144

Validate the requirements with other business people

140, 141, 142

145

Obtain sponsor approval for the requirements

144

146

Determine the condition of the source files and databases

139

147

Review the content of each potential source file and source database (internal and external)

 

148

Assess source data violations

 

149

Review technical data conversion rules

 

150

Review business data domain rules

 

151

Review business data integrity rules

 

152

Determine which data elements are critical, important, insignificant

 

153

Estimate the time needed for cleansing of critical source data

152

154

Estimate the time needed for cleansing of important source data

152

155

Review data-cleansing estimates with the business sponsor and prioritize the cleansing effort

153, 154

156

Determine or revise the cost estimates

146

157

Review the technical infrastructure assessment report

 

158

Review the nontechnical infrastructure assessment report

 

159

Review the project requirements

 

160

Review the project constraints (time, scope, budget, resources, quality)

 

161

Review the need for consulting, contracting, training

 

162

Revise the original cost estimates

161

163

Revise the risk assessment

146

164

Review and revise the original risk assessment matrix

 

165

Determine the likelihood of the risks materializing: low, medium, high

 

166

Determine the impact of every risk: low, medium, high

 

167

Define triggers

 

168

Define a risk mitigation plan

 

169

Define a contingency plan

 

170

Identify your assumptions

 

171

Include assumptions as risks on the contingency plan

 

172

Review the project constraints as they relate to risk

 

173

Identify critical success factors

156, 163

174

Define the success criteria for the BI project

 

175

Determine critical success factors

174

176

Review critical success factors with the business sponsor

175

177

Obtain agreement and cooperation on the critical success factors from the business sponsor

176

178

Prepare the project charter

173

179

State the purpose and reason for the BI project

 

180

State costs and benefits

 

181

Describe infrastructure and business process improvements

 

182

Describe the high-level scope (data and functions)

 

183

List items not in the scope

 

184

List expectations from the business people (preliminary SLA)

 

185

Define team structure, roles, and responsibilities

 

186

List risks, assumptions, and constraints

 

187

List critical success factors

 

188

Create a high-level project plan

173

189

Create a work breakdown structure

 

190

Determine base estimates for all tasks

 

191

Identify task dependencies

 

192

Revise the base estimates for assigned resources

191

193

Address skill level

 

194

Address subject matter expertise

 

195

Address additional administrative activities

 

196

Address non-work- related activities

 

197

Identify resource dependencies (resource leveling)

192

198

Create a critical path method (CPM) or Pert chart

197

199

Create a Gantt chart

197

200

Kick off the project

178, 188

201

Prepare an agenda for the kickoff meeting

 

202

Call a kickoff meeting

201

203

Assign roles and responsibilities to core team members

202

204

Identify extended team members and review their responsibilities

202

205

Discuss the project charter

202

206

Walk through the project plan

202

207

Discuss the concept of self-organizing teams

202

208

Step 4: Project Requirements Definition

 

209

Define the requirements for technical infrastructure enhancements

200

210

Define the requirements for additional hardware

 

211

Define the requirements for additional middleware

 

212

Define the requirements for a new DBMS or upgrades to the existing DBMS

 

213

Define the requirements for the network or upgrades to it

 

214

Determine the security requirements

 

215

Define the requirements for development tools (CASE, ETL)

 

216

Define the requirements for data access and reporting tools (OLAP, report writers)

 

217

Define the requirements for a new data mining tool

 

218

Determine whether to license or build a meta data repository

 

219

Determine how to enhance an existing meta data repository

 

220

Define the requirements for nontechnical infrastructure enhancements

200

221

Define the requirements for governance (prioritizing) standards and procedures

 

222

Define the requirements for the development methodology

 

223

Define the requirements for estimating guidelines

 

224

Define the requirements for the scope management process

 

225

Define the requirements for the issues management process

 

226

Define the requirements for roles and responsibilities

 

227

Define the requirements for the security process

 

228

Define the requirements for the meta data capture and delivery process

 

229

Define the requirements for logical data modeling

 

230

Define the requirements for the data cleansing process

 

231

Define the requirements for the testing procedures

 

232

Define the requirements for the SLA process

 

233

Define the requirements for the BI support function

 

234

Define the requirements for the dispute resolution process

 

235

Define the requirements for the communication process

 

236

Define the reporting requirements

200

237

Collect or create sample report layouts

 

238

Collect or create sample queries

 

239

Define business rules for the reports

 

240

Define aggregation and summarization rules

 

241

Define reporting dimensions

 

242

Define query libraries

 

243

Identify stewards of the libraries

 

244

Get samples of ad hoc queries (if possible)

 

245

Define access interfaces

 

246

Define the requirements for source data

200

247

Define all source data elements

 

248

Classify data elements as critical, important, insignificant

 

249

Define the data domains ( allowable values)

 

250

Define the significant and obvious business rules for the data

 

251

Determine the data-cleansing requirements

 

252

Define the historical data requirements

 

253

Review the project scope

209, 220, 236, 246

254

Compare the detailed project requirements to the high-level scope in the project charter

 

255

Review the project constraints (time, scope, budget, resources, quality)

 

256

Determine whether the scope is realistic under those constraints

 

257

Renegotiate the scope, if necessary

256

258

Create a change-control document

 

259

Create an issues log

 

260

Expand the logical data model

253

261

Add newly discovered entities and relationships

 

262

Refine the logical data model by resolving the many-to-many relationships

261

263

Add unique identifiers to each entity

262

264

Attribute the logical data model with critical data elements

262

265

Define preliminary service-level agreements

253

266

Identify or revise the expectations for availability

 

267

Identify or revise the expectations for security

 

268

Identify or revise the expectations for response time

 

269

Identify or revise the expectations for data cleanliness

 

270

Identify or revise the expectations for ongoing support

 

271

Write the application requirements document

260, 265

272

Describe the technical infrastructure requirements

 

273

Describe the nontechnical infrastructure requirements

 

274

Describe the reporting requirements

 

275

Describe the ad hoc and canned query requirements

 

276

Describe the requirements for source data, including history

 

277

Describe the data-cleansing requirements

 

278

Describe the security requirements

 

279

List the preliminary SLAs

 

280

Step 5: Data Analysis

 

281

Analyze the external data sources

271

282

Identify entities and relationships from each external data source

 

283

Merge the new entities and relationships from the external data sources into the logical data model

 

284

Refine the logical data model

271, 281

285

Fully attribute the logical data model to include all required source data elements

 

286

Create new entities and relationships where needed to store the new attributes

 

287

Analyze the layout of all identified source files and source databases

 

288

Analyze the content of all identified source data elements

 

289

Create the data-specific business meta data components

 

290

Analyze the source data quality

271, 281

291

Apply business data domain rules and business data integrity rules

 

292

Look for default values

 

293

Look for missing values

 

294

Look for cryptic values

 

295

Look for contradicting values

 

296

Look for values that violate the business rules

 

297

Look for missing primary keys

 

298

Look for duplicate primary keys

 

299

Determine the severity of the problem

 

300

Determine the criticality of the problem

 

301

Expand the enterprise logical data model

284, 290

302

Merge the project-specific logical data model into the enterprise logical data model

 

303

Identify data discrepancies and inconsistencies between the logical data models

 

304

Resolve data discrepancies

290

305

Discuss the discrepancies with data owners and other business executives

 

306

Adjust either the project-specific logical data model or the enterprise logical data model

 

307

Notify other affected project teams

 

308

Document the discrepancies as meta data and schedule time for resolutions

 

309

Write the data-cleansing specifications

304

310

Review the classification of data elements: critical, important, insignificant

 

311

Write data-cleansing specifications for all critical data elements

 

312

Write data-cleansing specifications for selected important data elements

 

313

Step 6: Application Prototyping

 

314

Analyze the access requirements

271

315

Review the application requirements document with the subject matter expert and the business representative

 

316

Analyze the report requirements

 

317

Analyze the query requirements

 

318

Analyze the ad hoc requirements

 

319

Analyze the interface requirements

 

320

Communicate all your findings to the database administrator

 

321

Create a skill set matrix for each business person participating in the prototyping activities

 

322

Indicate computer skill level: beginning, advanced, expert

 

323

Indicate application knowledge: beginning, advanced, expert

 

324

Determine the scope of the prototype

271

325

Determine the objective and the primary use of the prototype

 

326

Decide which type of prototype to build (show-and-tell, demo, etc.)

 

327

Select a subset of functions (reports, queries, ETL, interface)

 

328

Select a subset of sample data from source files and source databases

 

329

Create a change-control document for the prototype

 

330

Create an issues log for the prototype

 

331

Determine the number of prototype iterations

 

332

Determine the number of prototype participants

 

333

Determine the time limits for each prototype iteration

331

334

Estimate the cost and benefit for each prototype iteration

331

335

Determine the point of diminishing returns for prototyping

331

336

Select tools for the prototype

271

337

Review existing in-house tools and find out who uses them

 

338

Review the availability of new reporting and querying tools

 

339

Review existing or new graphical tools

 

340

Review existing or new report distribution tools

 

341

Review existing DBMS options for the prototype

 

342

Select the platform on which the prototype will be developed

 

343

Select one of the installed and tested DBMSs

 

344

Select one or more existing or new tools

 

345

Determine training needs for the new tools

 

346

Schedule training sessions

345

347

Prepare the prototype charter

314, 324, 336

348

State the purpose of the prototype

 

349

State what type of prototype you selected

 

350

List who will participate (IT and business people)

 

351

Define what the rules are (scope, time, iterations)

 

352

Define how you will measure the success of the prototype

 

353

Design the reports and queries

347

354

Design the reports

 

355

Design the queries

 

356

Design the interfaces

 

357

Create a physical data model (database design) for the prototype database

 

358

Identify the data to be used for the prototype

 

359

Map sample source data or new test data into the prototype database

358

360

Build the prototype

347

361

Create the physical prototype database

 

362

Create sample test data

 

363

Load the prototype database with sample data

 

364

Write a selected subset of reports

 

365

Write a selected subset of queries

 

366

Write a selected subset of interfaces or other functions

 

367

Test reports, queries, interfaces, or other functions

364, 365, 366

368

Document any problems with the tool

367

369

Document any issues with the reports or queries

367

370

Document any issues with the interfaces or other functions

367

371

Document any issues with dirty source data

367

372

Validate the time and cost estimates for the BI application

367

373

Demonstrate the prototype

353, 360

374

Review reports and queries with the business people

 

375

Review problems and issues with the business sponsor and the business representative

 

376

Review the project requirements with the subject matter expert and the business representative

 

377

Document requested changes in the change-control document

 

378

Analyze the impact of requested changes on other constraints (time, quality, cost, resources)

377

379

Review impact of requested changes with the business sponsor and the business representative

378

380

Revise the application requirements document to include approved changes

379

381

Review lessons learned with the entire project core team and in particular with the ETL step core team

380

382

Use prototype demonstrations to promote the BI application

380

383

Perform the next prototype iteration, if applicable

373

384

Step 7: Meta Data Repository Analysis

 

385

Analyze the meta data repository requirements

271

386

Review the technical infrastructure assessment report

 

387

Perform a cost-benefit analysis for licensing versus building a meta data repository

 

388

Make the decision to license or build a meta data repository

387

389

Review the nontechnical infrastructure assessment report

 

390

Determine the scope of the meta data repository deliverables

 

391

Prioritize the meta data repository deliverables

390

392

Update the application requirements document to reflect any changes

391

393

Analyze the interface requirements for the meta data repository

271

394

Analyze the meta data sources

 

395

Analyze word processing files and spreadsheets

 

396

Analyze DBMS dictionaries

 

397

Analyze CASE, ETL, OLAP tools

 

398

Analyze report writers and query tools

 

399

Analyze the data mining tool

 

400

Determine what import and export features are available in these tools

 

401

Determine what import and export features are available in the meta data repository product

 

402

Analyze the meta data repository access and reporting requirements

271

403

Review the original meta data repository access and reporting requirements

 

404

Review the meta data security requirements

 

405

Identify the access interface media (PDF, HTML)

 

406

Analyze the feasibility of a context-sensitive help function

 

407

Determine what reports should be produced from the meta data repository

 

408

Create the logical meta model

385, 393, 402

409

Create business meta data entities

 

410

Create technical meta data entities

 

411

Determine the relationships between the meta data entities

 

412

Create attributes for business and technical meta data entities

 

413

Draw an entity-relationship diagram

 

414

Create the meta-meta data

 

415

Describe all meta data entities

408

416

Name the meta data entities

 

417

Define all meta data entities

 

418

Define the relationships between all meta data entities

 

419

Define the security for meta data entities

 

420

Define the physical location for meta data entities

 

421

Define timeliness for meta data

 

422

Define volume for meta data entities

 

423

Describe all meta data attributes

415

424

Name the meta data attributes

 

425

Define all meta data attributes

 

426

Define type and length for meta data attributes

 

427

Define the domain for meta data attributes

 

428

Define the security for meta data attributes

 

429

Define ownership for meta data attributes

 

430

Define the business rules for meta data entities, attributes, and relationships

423

431

Step 8: Database Design

 

432

Review the data access requirements

309, 373

433

Review the data-cleansing specifications

 

434

Review the prototyping results

 

435

Review detailed access and analysis requirements

 

436

Review detailed reporting requirements

 

437

Review detailed querying requirements

 

438

Review known ad hoc querying requirements

 

439

Review data security requirements

 

440

Determine projected data volumes and growth factors

 

441

Determine the projected number of concurrent database usages

 

442

Determine the location of business people

 

443

Determine the frequency of report and query executions

 

444

Determine the peak and seasonal reporting periods

 

445

Determine platform limitations

 

446

Determine tool limitations (ETL, OLAP, report writers)

 

447

Determine the aggregation and summarization requirements

309, 373

448

Review measures (facts) used by the prototype

 

449

Review the dimensions used by the prototype

 

450

Review the drill-down and roll-up functions of the prototype

 

451

Review common reporting patterns among existing reports

 

452

Determine the most frequently used reporting dimensions

 

453

Review the logical data model with the data administrator

 

454

Determine the level of detail (granularity) needed

 

455

Determine how the detailed data will be accessed (drill-down or ad hoc)

 

456

Determine how many business relationships (entity relationships) will be needed

 

457

Design the BI target databases

435, 447

458

Determine the appropriate database design schemas (multidimensional or entity-relationship)

 

459

Create the physical data models (database design diagrams)

 

460

Create the technical meta data for the physical data models

459

461

Map the physical data models to the logical data model

459

462

Design the physical database structures

457

463

Determine how to cluster the tables

 

464

Determine the placement of datasets

 

465

Determine how to stripe disks

 

466

Determine how to partition the tables across multiple disks

 

467

Determine how much free space to choose

 

468

Determine how much buffer space to declare

 

469

Determine how large to set the blocksize

 

470

Determine the most appropriate indexing strategy

 

471

Determine whether referential integrity will be enforced by the DBMS

 

472

Build the BI target databases

462

473

Create the data definition language (DDL)

 

474

Define storage groups

 

475

Define databases

 

476

Define partitions

 

477

Define tablespaces

 

478

Define tables

 

479

Define columns

 

480

Define primary keys

 

481

Define foreign keys

480

482

Define indices

480

483

Create the data control language (DCL)

473

484

Define parameters for the security SYSTABLE

 

485

Set up group IDs

 

486

Grant CRUD (create, read, update, delete) authority to group IDs

 

487

Assign developers, business analysts, and programs to the appropriate group IDs

 

488

Run the DDL to create the physical database structures

473

489

Run the DCL to grant authority to the physical database structures

483

490

Build the indices

488

491

Develop database maintenance procedures

483

492

Define database maintenance activities

 

493

Define database backups (full and incremental backups )

 

494

Define disaster recovery procedures

 

495

Define reorganization procedures for fragmented tables

 

496

Define the frequency of and procedure for performance monitoring activities

 

497

Prepare to monitor and tune the database designs

491

498

Plan to monitor the performance of ETL loads, reports, and queries at runtime

 

499

Plan to use a performance-monitoring utility to diagnose performance degradation

 

500

Plan to refine the database design schemas

 

501

Plan to add additional indices, if necessary

 

502

Prepare to monitor and tune the query designs

491

503

Plan to review and streamline all SQL calls in programs

 

504

Plan to write pass-through queries for OLAP tools, if necessary

 

505

Plan to utilize parallel query execution

 

506

Step 9: Extract/Transform/Load Design

 

507

Create the source-to-target mapping document

491

508

Review the record layouts for the source files

 

509

Review the data description blocks for the source databases

 

510

Review the data-cleansing specifications for source data elements

 

511

Create a matrix for all target tables and target columns

 

512

List all applicable source files and source databases for every target table

 

513

List all relevant source data elements for every target column

 

514

List data type and length for every target column

 

515

List data type and length for every source data element

 

516

Write transformation specifications for populating the columns

514, 515

517

Combine data content from multiple sources (if needed)

 

518

Split data content from one data element across multiple columns (if needed)

 

519

Include aggregation and summarization algorithms

 

520

Include data-cleansing specifications for each column

 

521

Include logic for checking referential integrity (if not performed by the DBMS)

 

522

Include logic for error messages and record rejection counts

 

523

Include logic for reconciliation totals (record counts, domain counts, amount counts)

 

524

Test the ETL tool functions

491

525

Review the transformation specifications in the source-to-target mapping document

516

526

Determine whether the ETL tool functions can perform the required transformation logic

525

527

Determine what supplementary custom code must be written

526

528

Design the ETL process flow

507, 524

529

Determine the most efficient sequence to extract source data

 

530

Determine the most efficient sequence to transform, cleanse , and load the data

 

531

Determine the sort and merge steps in the ETL process

 

532

Identify all temporary and permanent work files and tables

 

533

Determine what components of the ETL process can run in parallel

 

534

Determine what tables can be loaded in parallel

 

535

Draw the process flow diagram

533, 534

536

Show the extracts from source files and source databases

 

537

Indicate temporary and permanent work files and tables

 

538

Show the sort and merge processes

 

539

Show the transformation programs

 

540

Show the error rejection files and error reports

 

541

Show the load files and load utilities

 

542

Design the ETL programs

528

543

Design three sets of ETL programs

 

544

Design the initial load programs

 

545

Design the historical load programs

 

546

Design the incremental load programs

 

547

Modularize the ETL programs

 

548

Translate the transformation specifications into programming specifications

547

549

Set up the ETL staging area

528

550

Determine whether and how to distribute the ETL process

 

551

Set up the ETL server

 

552

Allocate space for temporary and permanent work files and tables

551

553

Create program libraries

551

554

Establish program-versioning procedures

551

555

Step 10: Meta Data Repository Design

 

556

Design the meta data repository database

414

557

Review the logical meta model for the meta data repository

 

558

Design the meta data repository database (entity-relationship or object-oriented)

 

559

Draw the physical meta model diagram (entity-relationship or object-oriented)

 

560

Map the physical meta model to the logical meta model

 

561

Create the DDL for the meta data repository database

 

562

Create the DCL for the meta data repository database

 

563

Design backup and recovery procedures

 

564

Design versioning and archival procedures

 

565

Install and test the meta data repository product

414

566

Compile a list of meta data repository products and vendors

 

567

Compare the meta data repository products to the meta data repository requirements

 

568

Create a scorecard for each evaluated meta data repository product

 

569

Create a scorecard for each evaluated meta data repository vendor

 

570

Narrow the list of meta data repository products and vendors to a short list

568, 569

571

Arrange for meta data repository product demos

 

572

Check the vendors' client references

 

573

License the meta data repository product

572

574

Install and test the meta data repository product

573

575

Design the meta data migration process

556, 565

576

Analyze all sources for extracting business meta data

 

577

Analyze all sources for extracting technical meta data

 

578

Design the tool interface process

 

579

Design the transformations for the extracted meta data

 

580

Design the load programs for the meta data repository

 

581

Write the programming specifications for the meta data migration process

 

582

Write tool interface programming specifications

578

583

Write transformation programming specifications

579

584

Write meta data repository load programming specifications

580

585

Design the meta data application

556

586

Design the meta data repository report programs

 

587

Design the media for displaying meta data ad hoc query results

 

588

Design the access interface process

 

589

Design the context-sensitive online help function

 

590

Write the programming specifications for the meta data application

 

591

Write report programming specifications

586

592

Write query script specifications

587

593

Write access interface programming specifications

588

594

Write online help function programming specifications

589

595

Step 11: Extract/Transform/Load Development

 

596

Build and unit test the ETL process

542, 549

597

Code the ETL programs

 

598

If using an ETL tool, write instructions for the ETL tool modules

 

599

Capture the ETL technical meta data for the meta data repository

 

600

Write code to produce reconciliation totals, quality metrics, and load statistics

 

601

Unit test each individual program module

597, 600

602

If using an ETL tool, unit test each ETL tool module

598, 600

603

Write the scripts to execute the ETL programs and the sort, merge, and load utilities

601, 602

604

Integration or regression test the ETL process

596

605

Create a test plan with test cases for the ETL process

 

606

Create test data for the ETL programs

 

607

Integration or regression test the entire ETL process

605, 606

608

Log the actual test results and document any test issues

605, 606

609

Compare actual test results with expected test results

605, 606

610

Revise the ETL programs (or the instructions for the ETL tool)

609

611

Retest the entire ETL process from beginning to end

610

612

Performance test the ETL process

604

613

Test individual ETL programs and tool modules that read or write to high-volume tables

 

614

Test the parallel execution of ETL programs and tool modules against high-volume tables

 

615

Test the ETL programs and ETL tool modules that perform complicated operations

 

616

Use full-volume data for performance testing

 

617

If using a stress test simulation tool, define test components and run a simulation test

 

618

Quality assurance (QA) test the ETL process

612

619

Move all ETL programs into the QA environment

 

620

QA test the entire ETL process from beginning to end

619

621

Obtain approval from the operations staff to move the ETL process into production

620

622

Acceptance test the ETL process

612

623

Acceptance test the entire ETL process from beginning to end

 

624

Validate all cleansing transformations

 

625

Validate error-handling routines

 

626

Validate reconciliation totals

 

627

Obtain certification for the ETL process from the business representative

623

628

Step 12: Application Development

 

629

Determine the final project requirements

491

630

Review the results of the prototype

 

631

Review the prototyping programs and scripts

 

632

Review the change-control document

 

633

Review the issues log

 

634

Review existing and mock-up report layouts

 

635

Review existing spreadsheets

 

636

Review the latest version of the application requirements document

 

637

Agree on the final project requirements

 

638

Update the application requirements document to reflect any changes

637

639

Design the application programs

491

640

Design the final reports

 

641

Design the final queries

 

642

Design the front-end interface (GUI, Web portal)

 

643

Design the online help function

 

644

Write programming specifications

 

645

Write report programming specifications

640

646

Write query script specifications

641

647

Write front-end interface programming specifications

642

648

Write online help function programming specifications

643

649

Create a test plan with test cases and a test log

645, 646

650

Build and unit test the application programs

639

651

Create sample test data

 

652

Load the development databases with sample test data

 

653

Rewrite or enhance prototyping programs and scripts

 

654

Code the final report programs

 

655

Code the final query scripts

 

656

Code the final front-end interface programs

 

657

Code the online help function programs

 

658

Unit test each individual program module

654, 655, 656, 657

659

Test the application programs

650

660

Integration or regression test all programs and scripts from beginning to end

 

661

Integration or regression test report programs

 

662

Integration or regression test query scripts

 

663

Integration or regression test front-end interface programs

 

664

Integration or regression test online help function programs

 

665

Log the actual test results and document any test issues

 

666

Compare actual test results with expected test results

 

667

Revise the application programs and scripts

666

668

Retest the application programs and scripts from beginning to end

667

669

Performance test complex high-volume programs

668

670

Use full-volume data for performance testing

668

671

If using a stress test simulation tool, define test components and run a simulation test

668

672

Move databases, programs, and scripts into the QA environment

669

673

QA test the entire application from beginning to end

672

674

Obtain approval from the operations staff to move the application programs into production

673

675

Acceptance test the entire application from beginning to end

669

676

Obtain certification for the application from the business representative

675

677

Provide data access and analysis training

650

678

Identify help desk staff to be trained

 

679

Identify "power users" or other business liaison personnel to be trained

 

680

Identify business people to be trained

 

681

Create training materials

 

682

Create presentation slides and instructor notes

 

683

Create student workbooks with exercises

682

684

Create exercise solutions and other pertinent handouts

683

685

Schedule training sessions

684

686

Conduct training sessions

685

687

Measure training effectiveness

686

688

Step 13: Data Mining

 

689

State the business problem

491

690

Define the business problem

 

691

Obtain commitment for a data mining solution

690

692

Set realistic expectations for the data mining tool

691

693

Identify preliminary algorithms relevant to the business problem

691

694

Collect the data

689

695

Identify available data sources (operational as well as BI)

 

696

Extract pertinent data from various internal data sources

 

697

Acquire pertinent data from external data sources

 

698

Consolidate and cleanse the data

689

699

Merge data from various internal data sources

 

700

Match and merge internal data with external data

 

701

Review the structure of the merged data

 

702

Select a sample of data for each analytical data model

 

703

Select related meta data from the meta data repository

 

704

Review the data domains and measure the quality and reasonability of data values

702

705

Validate domain reasonability across active variables

702

706

Prepare the data

702

707

Review the frequency distribution of categorical variables

 

708

Review maximum, minimum, mean, mode, and median for quantitative variables

 

709

Use statistical distribution parameters to filter noise in the data

 

710

Eliminate or replace variables with missing values

 

711

Convert data formats to suit the particular data mining algorithm used

 

712

Derive new variables from original input data

 

713

Consolidate customers by assigning a household number to related customers

 

714

Relate customers with products and services

 

715

Apply data reduction

 

716

Apply data mining transformation techniques

715

717

Apply "discretization" technique

 

718

Apply "one-of-N" technique

 

719

Build the analytical data model

694, 698, 706

720

Create the analytical (informational) data model

 

721

Select data mining operations with the appropriate algorithms

 

722

Test accuracy using confusion matrices and input sensitivity analyses

 

723

Repeat prior steps to train and retrain the model

722

724

Interpret the data mining results

719

725

Review the data mining results

 

726

Look for results that are interesting, valid, and actionable

 

727

Present the new findings using visualization technology

726

728

Formulate ways in which the new information can be exploited

726

729

Perform external validation of the results

719

730

Compare data mining results to published industry statistics

 

731

Validate the selection of your variables and time frame against the variables and time frame of the industry statistics

 

732

Identify the variations between your analysis results and the industry statistics

 

733

Determine the reasons for the variations

 

734

Monitor the analytical data model over time

724, 729

735

Keep validating your analytical data model against industry statistics at regular time intervals

 

736

When industry statistics change, change your analytical data model and retrain it

735

737

Research the data mining capabilities of your competitors

 

738

Monitor your competitors' market share and adjust your model

 

739

Step 14: Meta Data Repository Development

 

740

Build the meta data repository database

575, 585

741

Run the DDL to create the physical meta data repository database structures

 

742

Run the DCL to grant CRUD authority on the meta data repository database structures

 

743

If licensing a meta data repository product, set up CRUD authority on the meta data repository product

 

744

Test all meta data repository product components, especially the meta data repository database

 

745

Build and unit test the meta data migration process

740

746

Code the tool interface programs or use the export facility of the various tools

 

747

Code the meta data transformation programs

 

748

Code the meta data load programs or use the import facility of the meta data repository product or the DBMS load utility

 

749

Code the meta data programs that will run during ETL

 

750

Code the meta data programs to capture load statistics

 

751

Code the meta data programs to capture reconciliation totals

 

752

Code the meta data programs to capture data-cleansing metrics

 

753

Code the meta data programs to capture rejection counts and reasons for rejections

 

754

Unit test the meta data migration programs

 

755

Unit test the tool interface programs

746

756

Unit test the meta data transformation programs

747

757

Unit the test meta data load programs

748

758

Unit test the meta data programs that will run during the ETL process

749

759

Build and unit test the meta data application

740

760

Code the access interface programs

 

761

Code the meta data report programs

 

762

Code the meta data query scripts

 

763

Code the meta data repository online help function programs

 

764

Unit test the meta data application programs (or meta data repository product modules)

 

765

Unit test the access interface programs

760

766

Unit test the meta data report programs

761

767

Unit test the meta data query scripts

762

768

Unit test the meta data repository online help function programs

763

769

Test the meta data repository programs or product functions

745, 759

770

Create a test plan with test cases

 

771

Create test cases for the meta data migration process

 

772

Create test cases for the meta data repository application programs or product modules

 

773

Create test cases for the meta data programs that run during the ETL process

 

774

Create test data for meta data repository testing

 

775

Create test data for the meta data migration process

 

776

Create test data for the meta data repository application or product modules

 

777

Create test data for the meta data programs that run during the ETL process

 

778

Integration or regression test the meta data repository

770, 774

779

Integration or regression test the meta data migration process

 

780

Integration or regression test the meta data repository application or product modules

 

781

Integration or regression test the meta data programs that run during the ETL process

 

782

Log the actual test results and document any test issues

778

783

Compare actual test results with expected test results

778

784

Revise the meta data repository programs

783

785

Retest the meta data repository programs from beginning to end

784

786

Conduct QA testing with operations staff

785

787

Conduct acceptance testing with the subject matter expert and the business representative

785

788

Prepare the meta data repository for production

769

789

Install and test the server platform for the production meta data repository

 

790

Create DDL and DCL for the production meta data repository database

 

791

Write operating procedures for the operations staff for running the meta data repository reports

 

792

Write a reference guide for the help desk staff and the business people

 

793

Develop performance monitoring and tuning procedures for the meta data repository database

 

794

Develop meta data repository usage monitoring procedures

 

795

Provide meta data repository training

769

796

Identify help desk staff to be trained

 

797

Identify "power users" to be trained

 

798

Identify business people to be trained

 

799

Create meta data repository training materials

 

800

Create meta data repository presentation slides and instructor notes

 

801

Create meta data repository student workbooks with exercises

800

802

Create exercise solutions and other pertinent handouts

801

803

Schedule meta data repository training sessions

802

804

Conduct meta data repository training sessions

803

805

Measure meta data repository training effectiveness

804

806

Step 15: Implementation

 

807

Plan the implementation

618, 622, 659, 719, 788

808

Select an implementation (rollout) strategy

 

809

Set the implementation date

 

810

Determine the number of business people for the initial rollout

 

811

Schedule the necessary resources to participate in implementation activities

 

812

Schedule the functions to be rolled out

 

813

Prepare for organizational impact

 

814

Set up the production environment

807

815

Set up the production ETL program library

 

816

Set up the production application program library

 

817

Set up the production meta data repository program library

 

818

Create the production BI target databases

 

819

Create the production meta data repository database

 

820

Grant appropriate authority on the production BI target databases

818

821

Grant appropriate authority on the production meta data repository database

819

822

Grant appropriate authority on all production program libraries

815, 816, 817

823

Write ETL operating procedures for operations staff

 

824

Write application reference guides for help desk staff and the business people

 

825

Implement production security levels for all BI application components

 

826

Install all the BI application components

814

827

Move ETL programs into the production ETL program library

 

828

Move initial load programs

 

829

Move historical load programs

 

830

Move incremental load programs

 

831

Move application programs into the production application program library

 

832

Move report programs

 

833

Move query scripts

 

834

Move front-end interface programs

 

835

Move online help function programs

 

836

Move meta data repository programs into the production meta data repository program library

 

837

Move meta data migration programs

 

838

Move meta data application programs or product modules

 

839

Set up the production schedule

814

840

Set up the ETL process on the job scheduler

 

841

Add to the job scheduler the meta data programs that run during the ETL process

 

842

Set up on the job scheduler the regularly scheduled application report programs

 

843

Set up on the job scheduler the regularly scheduled meta data repository programs

 

844

Set up the meta data migration process

 

845

Set up the meta data repository application

 

846

Load the production databases

826, 839

847

Run the initial load process

 

848

Run the historical load process

 

849

Run the meta data migration process

 

850

Prepare for ongoing support

846

851

Establish a schedule for on-call emergency support

 

852

Schedule database maintenance activities for the production databases

 

853

Schedule database backups

 

854

Schedule disaster recovery testing

 

855

Schedule database reorganizations

 

856

Schedule database monitoring activities for the production databases

 

857

Schedule performance monitoring activities

 

858

Schedule growth monitoring activities

 

859

Schedule usage monitoring activities

 

860

Schedule data quality monitoring activities for the BI target databases

 

861

Schedule activities for reviewing meta data metrics

 

862

Schedule quality spot checks

 

863

Develop or review capacity plans for the BI platform

 

864

Develop capacity plans for processors

 

865

Develop capacity plans for disk storage

 

866

Develop capacity plans for network components (including bandwidth)

 

867

Start production processing (go live)

850

868

Step 16: Release Evaluation

 

869

Prepare for the post-implementation review

850FS+30 days

870

Review budget expenditures

 

871

Review the original project plan and final schedule

 

872

Review the estimated and actual task completion times

 

873

Review the issues log (resolved and unresolved issues)

 

874

Review the change-control procedure and scope changes

 

875

Review unfulfilled requirements (dropped from scope)

 

876

Review the effectiveness of the development approach

 

877

Review the effectiveness of the team structure

 

878

Review the effectiveness of the organizational placement

 

879

Review the existing infrastructure (technical and nontechnical)

 

880

Identify missing infrastructure pieces (technical and nontechnical)

879

881

Assess the performance of the BI application

 

882

Review the effectiveness of training

 

883

Review the implementation (rollout) strategy

 

884

Review the effectiveness of the release concept

 

885

Organize the post-implementation review meeting

850FS+30 days

886

Create the preliminary post-implementation review agenda

 

887

List date, time, and place

 

888

List invited attendees

 

889

List topics for discussion

 

890

List and assign topics for research

 

891

List questions to be discussed and answered

 

892

Solicit additional topics and questions from attendees

 

893

Send out the preliminary agenda to attendees

 

894

Schedule the meeting at an off-site location

 

895

Arrange facilitation by a third party

 

896

Arrange for a third-party scribe to take notes during the meeting

 

897

Revise and send the final meeting agenda

893

898

Send out documentation to be discussed during the review

897

899

Conduct the post-implementation review meeting

869, 885

900

Introduce the attendees

 

901

Explain the rules for the facilitated session

 

902

Discuss each item on the agenda

 

903

Document discussions, suggestions, resolutions

 

904

Document action items

 

905

Assign action items

 

906

Establish completion or response date for each action item

 

907

Follow up on the post-implementation review

899

908

Document unfulfilled requirements to be bundled with the next BI release

 

909

Write the meeting minutes

 

910

Publish the meeting minutes

 

911

Work on assigned action items

 

912

Monitor the work performed on action items

 

913

Document the action item results

911

914

Publish the action item results

913

915

Implement nontechnical infrastructure improvements

 

916

Improve the development approach

 

917

Improve use of the development methodology

 

918

Improve processes and procedures

 

919

Improve guidelines

 

920

Improve standards

 


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

flylib.com © 2008-2017.
If you may any questions please contact us: flylib@qtcs.net