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Business Intelligence Lifecycle


While data is captured in complex structures and databases to facilitate specific transaction requirements, organizations and businesses find it difficult to extract and capture the required information from data in transaction systems.

Thus, there was a need to develop a system that can dependably take out data from the source systems and restructure the content appropriate for business analysis. The restructuring of data must be done in a way such that the meaningful data and information is provided to business people through the useful tools they are able to access.

Nonetheless, business intelligence projects are more time consuming and they require a successful methodology to employ all the business-related operations. According to Kimball’s approach, the business intelligence model suggests:

  • Understanding the requirements and delivering the valuable business output
  • Act in accordance with the proven DW Lifecycle.
  • Building and delivering progressively within the organization’s data framework
  • Designing flexible, useful and high-performance datasets.
  • Providing a complete business solution via reports, query tools, documentation.

All the BI projects require design, development and testing as a part of the BI lifecycle. The lifecycle gives them the overall perspective including technical and managerial for the end-to-end considerations in deploying the complex data warehousing systems. Below image signifies how the Business Intelligence Lifecycle process:

business intelligence lifecycle process


Project Planning: The first phase of the BI lifecycle includes Planning of the business Project or Program. This makes sure that the business people have a proper checklist and proper planning considerations to design complicated systems in data warehousing. Project Planning decides and distributes the roles and responsibilities of all the executives involved in a particular project. The working executives then designs a detailed project plan before performing any relevant action.

Besides, planning also comprises setting task priorities as to what task needs to be performed at what time interval or in what order. Further, all the business requirements for designing and developing the project are evaluated and accessed before starting to work in real-time.

The phase two refers to Business Requirements Definition, which is a detailed project plan where key team members of the projects should develop proper estimates for the tasks. The unique characteristics of the project like cross-functional, high visibility and iterative- should be kept in mind. Further, the team members should identify the data problems well in time. It must be noted that all activities in the Project Plan must be accomplished within two weeks.

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Defining business requirements also include prior preparation, conducting interviews to ensure the presence of Data Experts in the project and preparing documentation.  Debriefing of the project planning must be done with the whole team involving required data, opportunities, user analytical and technical sophistication and others. A consolidated document including initial data warehouse matrix and main content and description must be prepared.

Later, the experts need to define the business process dimensional model, which includes the primary dimensional modeling concepts, changing dimensions, the modeling process and data profiling and stewardship. The business process dimensional model is also referred to as star schema which is an easy-to-understand and better performance relational model having entities/objects/dimensions with all attributes. There is one active row per occurrence of the object, and the dimensions are open to any further changes. All in all, a normalized table for a single business process at atomic detailed level is prepared like below:

normalized table

Later, it is important to create conformed dimensions ensuring that all the fact tables that share the dimensions must use the same dimension with the same key agreeing on column names and definitions.

Then, the BI System Architecture is designed, which is a set of functions and components to meet the business requirements. The BI architecture is same as explained in the DWH Architecture segment, which includes processes like Product selection and installation and the whole ETL processing.

BI Application design refers to developing standard templates and navigation. The BI Application development includes standard and flexible reporting and complex analysis and the current business review. The templates and reports are designed such that they allow end-to-end user navigation. The application development phase also covers data validation, performance tuning, maintenance and enhancement resources and data quality check.

As per the names, after all the design and development, Security, Deployment (documentation) and Maintenance (system and user support) tasks must be performed. Growth refers to the ongoing/iterative process for business. It focuses on revisiting opportunities and setting the next priorities. Besides, building additional dimensions, successful delivery of BI applications and rollout and repeat are the other processes included in the growth phase.

As you can see in the main diagram, the growth is again connected to the Project Planning suggesting the starting over of the business dimensional lifecycle again. To gain best results following the BI lifecycle, business people must be value-focused, believe in performing short, iterative delivery cycles and providing end-to-end solutions.

Learn more about Business Intelligence in this insightful blog now!

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