As we continue the discussion on the business intelligence perspective, let us review how this perspective is related to the business analysis scope.
With respect to the business intelligence perspective, there are some factors which include:
1 Change Sponsor: The change sponsor of a business intelligence initiative should be the highest ranking executive in the organizational unit that is influenced by the change.
This would allow for a stable, cohesive approach to the divided use of data assets within the cross-functional building of a business intelligence solution.
2 Change Targets: The aim of a business intelligence initiative is to help people and processes make better decisions in the organization. Business intelligence can help improve reporting, monitoring, and predictive modelling of performance-related data.
3 Business Analyst Position: The business analyst is the main liaison between the business intelligence stakeholders and the initiative team members in relation to business analysis activities.
They also take part in business intelligence technical activities such as:
- Enterprise data modelling.
- Decision modelling.
- Reports design.
- Query design.
These business analysts may also have the following roles:
- A business analyst who is capable of describing the business requirements and assessing the potential solutions.
- A functional analyst who understands data mining, predictive analytic and visualizations development.
- A data analyst who is skilled at describing source systems data which are to be used for analytical purposes.
- A data architect who is skilled at describing both the source and target data structures in logical data models.
4 Business Analysis Outcomes: Business intelligence business analysts focus is on the main elements of the solution architecture which include :
- The details of the business decisions to be affected or changed.
- The collection of data from source systems.
- The combination of differing sources into a merged enterprise framework.
- Supplying selected information and analytic insight to business stakeholders.
The business analyst is in charge of the analysis and specification of the business requirements for all these elements and works with the technical specialists to evaluate the solution artifacts.
The results of business analysis activities with respect to business intelligence include the following:
• Business process coverage: this describes the high level scope of business intelling change within the enterprise that are to be supported by the solution.
It explains how the information output will be used and what value it will provide.
• Decision models: this is used to pinpoint the information requirements of each business decision to be helped and states the business rules logic of how the individual information elements would help with the decision outcomes.
• Source logical data model and data dictionary: this provides a standard description of the needed data that is in each source system. The source data dictionary provides a description of each element and the business rules used by them.
The descriptions include a business description, type,format and length, legal values, and any inter-dependencies.
• Source data quality assessment: this is used to assess the completeness, rationality,and accuracy of the data from source systems.
It identifies if further verification and improvement of the source data is needed to ensure that there are stable business definitions and rules that apply across the enterprise-wide data asset.
• Target logical data model and data dictionary: the target logical data model provides a consolidated, standardized view of the data structures needed to support the business domain.
The target data dictionary supplies the standardized enterprise-wide description of data elements and their integrity rules.
• Transformation rules: these are used to plan the source and target data elements, state the requirements for the decoding and encoding of values and enhancements to the transformation process.
• Business analytics requirements: these are used to describe the information and communication requirements for decision support outputs.
These include:
- Preset reports.
- Dashboards.
- Balanced scorecards.
- On demand reports.
- Online analytical processing (OLAP) queries.
- Data mining.
- Prescribed analytics.
- Conditional alerts.
- complex event processing.
- Predictive modelling.
Definitions for each output might include:
- Data dimensions.
- Degree of granularity.
- Filtering criterion used.
- Drill down possibilities.
- Analytical options.
- User access rights and permissions.
And reporting rules to describe data element format, translation i.e. labels, look-ups, calculations and data collection.
• Solution architecture: this provides a high-level design view of how the decision support requirements of each functional area will be mapped to the business intelligence framework.
It is usually presented in the form of a process model that describes the following:
- Where the source data is kept.
- How and when the data will be extracted.
- Where these transformations will take place.
- Where the data will be physically stored.
- How the data will flow to the reporting outputs.