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 |
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 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 nontechnical infrastructure changes -
Proposed BI solution | -
Improved nontechnical infrastructure -
Development guidelines for project core team | -
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 | -
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 assessment -
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 success -
Approved BI project -
Approved budget | -
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 -
Project plan |
4. Project Requirements Definition | -
Approved BI project -
Project charter -
Project plan -
Identified business sponsor (and an alternate sponsor, if possible) -
Business (process) ownership defined -
Unfulfilled requirements from previous BI project -
New requirements -
Request for infrastructure changes (technical as well as nontechnical) -
Critical success factors -
Measures of success | -
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 |
5. Data Analysis | -
Approved project -
Project charter -
Project plan -
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 | -
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 [*] |
6. Application Prototyping | -
Project charter -
Project plan -
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 prototype -
Revised application requirements document with detailed project requirements (data and functions) -
Skills survey matrix -
Issues log |
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 |
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 |
9. 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 (both internal and external) -
Business meta data -
Data-cleansing specifications -
Physical BI target databases | -
Expected performance of ETL process -
Identified meta data to be produced by the ETL process: -
- Load statistics -
- Data quality metrics -
- Reconciliation totals -
Decision whether to license (buy) an ETL tool -
ETL product and vendor evaluation -
Installation of ETL tool | -
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 -
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 |
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 |
11. Extract/Transform/Load Development | -
Source-to-target mapping document -
ETL process flow diagram showing process dependencies -
ETL program design document -
Staging area | -
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 tools) -
Physical BI target databases | -
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 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 tool | -
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 market share -
- Increase customer satisfaction -
New business strategies based on knowledge discovery | -
Data mining database -
Analytical data model |
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 -
- 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 guides |
16. Release Evaluation | -
Project charter -
Project plan -
Issues log -
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 learned -
Process improvement items -
Repeatable success | -
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 list |