BUSINESS INTELLIGENCE FINAL PAPER 2025/2026
QUESTIONS WITH SOLUTIONS RATED A+
✔✔Common BI Mistakes - ✔✔Not defining the business problems that should be solved
Not involving end users in developing a solution
Not considering security and legal requirements
✔✔Builders - ✔✔Build system for consumers; central or business IT. (Bottleneck?)
✔✔Creators/Producers - ✔✔power users, create reports, analytics
✔✔Consumers - ✔✔little desire to create, task-oriented, need to make decisions
quickly; should be involved and supervise BI
✔✔Collaborators - ✔✔improve the info, add context and their knowledge, add
comments and links, rate the data
✔✔Example of Builders - ✔✔IT dept
✔✔Example of Producers - ✔✔Consultants, analytic professionals
✔✔Example of Consumers - ✔✔customers, public, suppliers, employees
✔✔Example of Collaborators - ✔✔independent data providers
✔✔Data selection considerations - ✔✔availability, quality, refresh rates, usefulness,
ownership
✔✔Steps to Agile BI - ✔✔Development: need for an agile, iterative process that speeds
the time to market
Project Mgmt: continuous planning and execution
Infrastructure: scaling capability to maintain near-real-time BI more than the ETL
(extract, transform, load) model
Cloud: cheaper alternative to store and transfer data
IT Organization: IT interact w/ business, address business problems
✔✔Self-service BI - ✔✔tools for data analysis and visualization
✔✔Features of self-service BI - ✔✔Cheap/free tools w/ high but limited capability
Decentralized, autonomous systems
Enables data visualization analysis: analysing graphs, not raw data
✔✔Advantages of self-service BI - ✔✔End-users have direct access to data, analytics,
and reporting tools
, End-users have greater control over decision-making needs
Leads to reduction of IT bottleneck, speeding decision-making processes
Allows more decision-making capability embedded in business lines
Employees can work independently
No expert knowledge required
Easy setup
Quick solution, visualizations
✔✔Disadvantages of self-service BI - ✔✔Misuse or misinterpretation of data
Data inconsistency leading to inconsistent output
Lack of proper training
Inadequate data governance
✔✔Data as an asset - ✔✔Collected, Stored, Maintained, Used wisely
Supports planning and management
✔✔Data Governance - ✔✔A set of tools, procedures, methods, a control that ensures
that the data entry by an operations team member or by an automated process meets
precise standards
✔✔Examples of data governance - ✔✔business rule, a data definition and data integrity
constraints in the data model
✔✔Purpose of data governance - ✔✔Ensure that the right data were collected, properly
transformed and stored
Ensure only authorized people have access
✔✔Data challenges in Information Management - ✔✔Existence of various data. Are you
collecting it?
Availability of various data. Is it accessible/reliable?
Ability to be easily understood. Is it interpretable?
Ability for the data to be included at decision points. Is it actionable?
✔✔Master Data Management (simple) - ✔✔set of tools, procedures, methods to ensure
data quality
✔✔Master Data Management (expanded) - ✔✔a comprehensive method of enabling an
enterprise to link all of its critical data to one file, called a master file, that provides a
common point of reference. When properly done, MDM streamlines data sharing among
personnel and departments.
✔✔Growing Pains in Information Management - ✔✔growth in data
greater expectation of users
increasing complexity of systems
QUESTIONS WITH SOLUTIONS RATED A+
✔✔Common BI Mistakes - ✔✔Not defining the business problems that should be solved
Not involving end users in developing a solution
Not considering security and legal requirements
✔✔Builders - ✔✔Build system for consumers; central or business IT. (Bottleneck?)
✔✔Creators/Producers - ✔✔power users, create reports, analytics
✔✔Consumers - ✔✔little desire to create, task-oriented, need to make decisions
quickly; should be involved and supervise BI
✔✔Collaborators - ✔✔improve the info, add context and their knowledge, add
comments and links, rate the data
✔✔Example of Builders - ✔✔IT dept
✔✔Example of Producers - ✔✔Consultants, analytic professionals
✔✔Example of Consumers - ✔✔customers, public, suppliers, employees
✔✔Example of Collaborators - ✔✔independent data providers
✔✔Data selection considerations - ✔✔availability, quality, refresh rates, usefulness,
ownership
✔✔Steps to Agile BI - ✔✔Development: need for an agile, iterative process that speeds
the time to market
Project Mgmt: continuous planning and execution
Infrastructure: scaling capability to maintain near-real-time BI more than the ETL
(extract, transform, load) model
Cloud: cheaper alternative to store and transfer data
IT Organization: IT interact w/ business, address business problems
✔✔Self-service BI - ✔✔tools for data analysis and visualization
✔✔Features of self-service BI - ✔✔Cheap/free tools w/ high but limited capability
Decentralized, autonomous systems
Enables data visualization analysis: analysing graphs, not raw data
✔✔Advantages of self-service BI - ✔✔End-users have direct access to data, analytics,
and reporting tools
, End-users have greater control over decision-making needs
Leads to reduction of IT bottleneck, speeding decision-making processes
Allows more decision-making capability embedded in business lines
Employees can work independently
No expert knowledge required
Easy setup
Quick solution, visualizations
✔✔Disadvantages of self-service BI - ✔✔Misuse or misinterpretation of data
Data inconsistency leading to inconsistent output
Lack of proper training
Inadequate data governance
✔✔Data as an asset - ✔✔Collected, Stored, Maintained, Used wisely
Supports planning and management
✔✔Data Governance - ✔✔A set of tools, procedures, methods, a control that ensures
that the data entry by an operations team member or by an automated process meets
precise standards
✔✔Examples of data governance - ✔✔business rule, a data definition and data integrity
constraints in the data model
✔✔Purpose of data governance - ✔✔Ensure that the right data were collected, properly
transformed and stored
Ensure only authorized people have access
✔✔Data challenges in Information Management - ✔✔Existence of various data. Are you
collecting it?
Availability of various data. Is it accessible/reliable?
Ability to be easily understood. Is it interpretable?
Ability for the data to be included at decision points. Is it actionable?
✔✔Master Data Management (simple) - ✔✔set of tools, procedures, methods to ensure
data quality
✔✔Master Data Management (expanded) - ✔✔a comprehensive method of enabling an
enterprise to link all of its critical data to one file, called a master file, that provides a
common point of reference. When properly done, MDM streamlines data sharing among
personnel and departments.
✔✔Growing Pains in Information Management - ✔✔growth in data
greater expectation of users
increasing complexity of systems
