This post is part of Series Business Intelligence – Tools & Theory
Currently running topic for this series is listed as below :
Series Business Intelligence – Tools & Theory
>>Chapter 1 : Business Intelligence an Introduction
>>Chapter 2 : Business Intelligence Essentials
>>Chapter 3 : Business Intelligence Types
>>Chapter 4 : Architecting the Data
>>Chapter 5 : Introduction of Data Mining
>>Chapter 6 : Data Mining Techniques
>>Chapter 7 : Introduction to Data Warehousing
>>Chapter 8 : Different Ways of Data Warehousing
>>Chapter 9 : Knowledge Management
>>Chapter 10 : Data Extraction
>>Chapter 11 : Business Intelligence Life Cycle<You are here>
Continuing from my previous post on this series, If you have missed any link please visit link below
We are going to Cover the Following Points in this article
- Business Intelligence Life Cycle
By now you must be familiar with the concepts of Data Extraction. In this unit you will learn in detail about the Business Intelligence lifecycle and the EPLC Framework. You will be familiarized on how successful implementation of a project is effected by human factors and the strategies used in business intelligence like creating a roadmap and project planning. In this chapter, we will discuss on choosing between centralized or decentralized BI architecture, the stages in developing BI.
Business Intelligence Life Cycle
Business Intelligence (BI) lifecycle refers to the computer-based techniques used in gathering, evaluating business information, such as sales revenue by products and/divisions associated prices and profits. The BI lifecycle frequently aims to enhance superior business decision-making techniques. The BI lifecycle representation mainly highlights on the iterative approach which is necessary to effectively pull out the greatest profit from investment in Business Intelligence. This approach is iterative as the BI solution needs to progress as and when the business develops.
A quick example is a customer who developed a good product for standard selling cost per unit. This made sense and facilitated them to discover price demands in their market and take suitable action.
Figure shows BI lifecycle phases.
Figure BI Lifecycle phases
On the other hand when they obtained a company whose standard selling cost was 100 times greater than the metric became deformed and required a second thought. The BI lifecycle model begins with Design phase which has suitable key performance indicators;
It executes the structure with proper methodologies and equipment’s. The
Utilize phase involves its own performance cycle.
Plan phase concludes what value the key performance indicators should be, and Monitors what they are.
Analyses phase is to recognize the variations. Monitoring will use the control panels and scorecards to explain the information quickly and evidently.
Analyses will take the benefit of new BI tools such as Excel Microsoft ProClarity, QlikView or other professional software to investigate the information and genuinely know trends in the essential data. A significant step is then to take stock of the procedure. It is to find out how it is performing or it requires any alterations.
The Refine phase is critical as it takes BI to the next significant phase, and is often misplaced from a BI program in the excitement of a successful execution.
The Business Intelligence Lifecycle acts similar to the Data Maturity1
Lifecycle to offer a complete maturation model on information intelligence.
Also this model gives a roadmap to utilize certain rules which helps in the development of a business intelligence program. BI Program is a long term scheme but not a short term. As the business goes on changing, and knowledge that supports analytics also improves, this lifecycle can repeat and forms a complete new performance management.
Note: Key performance indicators (KPI) are very significant factors in business intelligence operation. It is the aspect, which gives information about present status of business and future action plan to develop the business.
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