business intelligence dr. mahdi esmaeili. step 4: project requirements definition
TRANSCRIPT
Deliverable Resulting
1.Application requirements document- 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 SLAs
Roles Involved in This Step
• Application lead developer
• Business representative
• Data administrator
• Data quality analyst
• Meta data administrator
• Subject matter expert
Step 5: Data Analysis
Data analysis are geared toward understanding and
correcting the existing discrepancies in the business
data, irrespective of any system design or
implementation method.
Data analysis is therefore a business-focused activity,
not a system-focused activity.
• Data archeology (the process of finding bad data)
• Data cleansing (the process of correcting bad data)
• Data quality enforcement (the process of
preventing data defects at the source)
are all business responsibilities—not IT responsibilities.
1. Normalized and fully attributed logical data model
2. Business meta data
3. Data-cleansing specifications
4. Expanded enterprise logical data model
Deliverable Resulting
Roles Involved in This Step
• Business representative
• Data administrator
• Data quality analyst
• ETL lead developer
• Meta data administrator
• Stakeholders (including data owners)
• Subject matter expert
Step 6: Application Prototyping
There is nothing business people like more
than to see their requirements turn into a
tangible deliverable they can "touch and
feel" very quickly. A prototype accomplishes
that goal
Best Practices for Prototyping
Limit the scope
Understand database requirements early
Choose the right data
Test tool usability
Involve the business people
Types of Prototypes
• Show-and-Tell Prototypeserves as a demo for management and business people
• Mock-Up PrototypeThe purpose is to understand the access and analysis requirements and
the business activities behind them
• Proof-of-Concept PrototypeThe purpose is to explore implementation uncertainties
• Visual-Design PrototypeUnderstand the design of visual interfaces &
Develop specifications for visual interfaces and displays
• Demo PrototypeConvey the vision of the BI application to the business people or to external groups.
Test the market for the viability of a full-scale BI application
• Operational PrototypeCreate an almost fully functioning pilot for alpha or beta use of
the access and analysis portion of the BI application
Building Successful Prototypes
• Prototype CharterThe primary purpose of the prototypeThe prototype objectivesA list of business people The DataThe hardware and software platforms The measures of success An application interface agreement
• Guidelines for Prototyping
• Skills Survey
Prototyping Guidelines
1.Do not deviate from the basic purpose for which the prototype is being developed.
2.Develop a working prototype quickly; therefore, keep the scope small.
3.Acknowledge that the first iteration will have problems.
4.Frequently demonstrate the prototype to stakeholders.
5.Solicit and document top-down as well as bottom-up feedback on the prototype.
6.Ask for ongoing validation of the prototype results.
7.Continue to cycle between demonstrating and revising the prototype until its functionality is satisfactory to all parties.
8.Review your prototyping approach and modify it if necessary before proceeding with the next prototype iteration
Business Functions knowledge Beginning (B) Advanced (A) Expert (X)
Beginning (B) BB BA BX
Advanced (A) AB AA AX
Expert (X) XB XA XX
Computer Skill
Skills Matrix
Deliverable Resulting
• Prototype charter
• Completed prototype
• Revised application requirements document
• Skills survey matrix
• Issues log
Roles Involved in This Step
• Application lead developer
• Business representative
• Database administrator
• Stakeholders
• Subject matter expert
• Web master
Step 7: Meta Data Repository Analysis
Meta data describes an organization in terms of its business activities and the business objects on
which the business activities are performed.
a sale of a product to a customer by an employee.
Meta Data Mandatory Important OptionalOwner +Business data name +Technical data name +Definition +Type and length +Content (domain) +Relationships + Business rules and policies +Security +Cleanliness + Applicability +Timeliness +Origin (source) +Physical location (BI databases) +Transformation +Derivation +Aggregation +Summarization +Volume and growth +Notes +