What is Business Intelligence (BI)?

Thebestindonesia.com – Business Intelligent (BI) identifies new opportunities and implements effective strategies based on deep knowledge that can give a business a competitive sales advantage and long-term stability. BI consists of the methods and technologies used by companies to analyze business information. BI technologies provide predictive, current, and historical views of business operations. The main functions of BI are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, predictive analytics, and prescriptive analytics. BI technologies can handle large amounts of structured data to help identify, develop, and create new business opportunity strategies.

According to previous studies, BI is a set of processes, architectures, and technologies that transform raw data into useful information in the form of reporting, online analytical processing, analytics, data mining, complex event processing, business performance management, benchmarking, predictive analytics and analytical computing for support in recommending business decisions. In addition, BI is a process, a technological tool capable of converting data into information, information into meaningful knowledge that is used to plan corporate strategies for profit. In addition to increasing profitability can also reduce business risk and improve Customer Relationship Management (CRM).

In terms of management support for structured and unstructured data, BI is a process of integrating and unifying components to handle data that can be seen in the BI framework. This approach will be carried out using three methods: integrating structured and unstructured data, analyzing data collections and distributing the analysis results in a form that suits your needs. The above approach can take advantage of several tools: a Data Warehouse, Data Mining, Extraction Transformation Load (ETL), and Online Analytical Processing (OLAP).

A data warehouse collects accurate, clean, and detailed data from multiple sources for in-depth analysis. At the same time, OLAP supports multidimensional analysis in real-time and allows users to apply aggregation, filtering, roll-up, and drill-down details (e.g., product, customer, time, country, and region) and pivoting.

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According to Kimball et al. (2013), nine methodology and data warehouse design stages exist. The following is a lifecycle diagram according to Kimball et al. (2013):

Nine methodological stages in database design for data warehouses, according to Kimball et al. (2013), include Technical Architecture, Product Selection and Installation, Dimensional Modeling, Physical Design, ETL Design and Development, BI Application Design, BI Application Development, Deployment, and Maintenance. ETL is a set of processes to retrieve and process data from one or many sources into new sources. In addition, the dashboard server as a front-end application is used for data visualization and performance monitoring from management. It allows users to create graphs, charts, widgets, ad hoc reports, and decision-makers to track key business performance indicators.

A report from IBM Smarter Planet in 2015 shows that in the last two years, 90% of the world’s data has been generated, and most of the data created is visual. Therefore, it can be seen that the BI dashboard can help users recognize patterns and interpret data more quickly (Suprata, 2019). This BI dashboard is the foundation for various business applications, such as management performance monitoring, planning, budgeting, forecasting, financial reporting, analysis, simulation models, knowledge discovery, and data warehouse reporting. Therefore, the BI dashboard for banking performance is based on an analysis of the products offered to customers.

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This system can assist company leaders in making decisions regarding potential bank product development strategies and provide significant benefits for the company. With a reporting display in the form of a dashboard, the performance of companies in offering banking products and the decision-making process can be carried out faster and more accurately. BI dashboards enable enterprise management to receive valid and up-to-date information that is customizable, highly accessible, and available in real time. Furthermore, BI dashboards are created to inform decision-making and subsequent actions such as forecasting or predictions. An effective dashboard display can also speed up company decision-making, track performance results, and increase productivity.