Business Intelligence covers the strategies and techniques applied by businesses for the analysis of company data. This includes data analysis, market study, decision modeling, and forecasting, and learning. Business Intelligence provides essential services such as data cleansing, data mining, statistical analysis, and the verification of business process outsourcing processes. The major components of Business Intelligence are: Data Collection, Data Mining, and Decision Modeling. These three processes work together to build a solid platform for business intelligence (BI) models. BIS covers the various methods used in performing these three activities.
Business Intelligence provides crucial business information and strategic business decisions by gathering, organizing, analyzing, and presenting information to make business decisions. BIS can provide accurate, relevant, timely, and effective results depending on the quality of the resources. Business intelligence systems help companies gain competitive advantage through better understanding of their internal and external competition, competitor trends, and new trends emerging. Through a combination of traditional analytical processes and advanced BIS technologies, business intelligence systems help in the decision-making process by providing essential information that is critical for competitive positioning. By gathering and synthesizing information from a number of sources, these systems provide organizations with the necessary information for making business decisions.
Data mining is one of the techniques used in business intelligence. It involves the extraction of trends from large consolidated databases. Machine learning techniques, such as supervised learning and reinforcement learning, are also used for this purpose.
Another aspect of business intelligence is predictive analytics. This technique can be broadly categorized into two different categories, both of which are quite popular. While business intelligence tools are primarily designed for gathering and organizing data, predictive analytics attempts to make inferences and predictions from raw data. These methods have been quite successful and are being applied in various fields such as: online marketing, mobile marketing, e-commerce, consumer behavior research, and healthcare. Predictive analytics makes use of complex algorithms and artificial intelligence for generating and predicting future sales, customer behavior, demand, supply, pricing, location and other relevant factors that affect business performance.
Business intelligence can also be gathered and managed through the use of third party application development and platforms. Examples of such platforms include Salesforce, Axapta, and Solomon. There are a number of third party solutions that aim at providing insight and support through the use of advanced business intelligence tools and reporting. Most of these are available on a subscription basis and can be used by any company irrespective of its size. These third party platforms bring to organizations complete sets of business intelligence tools and reports that can help make decisions regarding performance management, strategic planning, business analysis, and other related activities. In fact, many organizations are now migrating from their current enterprise systems to these platform-based applications.
For companies that do not wish to invest in installing and maintaining their own business intelligence applications, there are several SaaS (Software as a Service) offerings available in the market today. Many of these SaaS applications provide a comprehensive view of business intelligence tools and reports and also offer complete automation of the entire process, thereby removing the need for IT assistance. Some of the SaaS solutions even enable organizations to analyze, make decisions and generate reports from their own internally built or purchased data. These SaaS applications help in managing the day-to-day activities and increasing productivity and profit by helping businesses make informed business decisions and achieve optimum performance metrics.