What is the Business Intelligence Cycle?

In order to gather, integrate, analyze, and present data in a way that helps corporate decision-making, business intelligence (BI) also entails the use of technology, tools, and methodologies. Data warehouses or data marts are frequently used to store and manage the data in BI, which includes a variety of activities like data mining, reporting, dashboards, and visualizations. By offering insights into operations, clients, and markets, business intelligence (BI) ultimately aims to assist organizations in making more educated and data-driven decisions. Businesses can use BI to find growth possibilities, streamline processes, and enhance overall performance.

Business Intelligence is the process of analyzing unprocessed data and turning it into knowledge that the company can use to make decisions. Organizations can better understand their marketing strategies, earnings and losses, effective development and management, and market trends and consumer behavior by using business intelligence.

Phases of Business Intelligence Life Cycle 

Business Intelligence Life Cycle

Phase 1: Analyze Business Requirements 

The first step in the Business Intelligence life cycle is to analyze the business requirements. The user identifies the business requirements in order to determine the type of analysis that the user then needs to perform. Identifying the requirements, let the user decides the further action to be performed. 

For example, any retail company can analyze the sales data to figure out the products that are top-selling and the products that least sell. 

Phase 2: Design Data Model 

Once the requirements are identified the user needs to design the logical model according to the requirements. This logical model helps the user to analyze the relationships that exist within the data entities. 

For example, For any retail company, the data model consists of products, their customers, and the sales data

Phase 3: Design the Physical Schema 

Once the logical model is prepared the next step is to design the physical schema using the data model. The physical schema describes the structure and the content of the data warehouse. 

For example, in any retail company, physical schema consists of sales-related facts, product-customer relationships, and the sales transactions

Phase 4: Build the Data Warehouse 

Once the logical and physical schema is designed, the next step is to build the data warehouse. The design of a data warehouse depends on the physical and logical schema. After the design of the data warehouse, the data and the content from the source system are loaded into the data warehouse for further steps. 

For example, for the retail system, designing the data warehouse consists of developing a database that would store the details of customers, products, and other requirements for the business. 

Phase 5: Create the Project Structure (Metadata) 

The next step after designing the data warehouse is to create a project structure also known as metadata. With the help of this created project structure, the mapping of the tables and data in the data warehouse is easier. Creating the project structure describes the further steps and types that need to be implemented. 

For example, The project structure of the retail company consists of the attributes of the data, the design, and the working flow of the system. This project structure or metadata gives a brief idea about the working of the system. 

Phase 6: Develop The BI Objects 

The next step is to develop the BI objects such as metrics, attributes, dashboards, reports, and facts. This step consists of developing the reports and dashboards that can be used to analyze the data in the data warehouse.
For example, the retail company can develop reports and statistics charts that can describe the profit and loss margins.

Phase 7: Administer and Maintain the Project 

The last step is to administer and maintain the project continuously as it undergoes changes. The project needs to be monitored to maintain the changes, security, and performance of the system. 

For example, the retail company needs to monitor the reports and statistics accordingly to increase the profit of the sales.

Conclusion  

Business Intelligence provides the proper approach for the data analysis and decision-making process. It helps the business to achieve goals and gain profits. The overall phases of business intelligence make the further development and maintenance process easy.