What Is Business Intelligence?
What is Business Intelligence? Business intelligence refers to the strategic plans and technologies applied by businesses for the analysis of organizational data. BI technology provide predictive, historical, and current views of organizational data. It is used to make business decisions. In other words it is concerned with the “big data”.
The first step in understanding what is business intelligence is to understand that it refers to the strategic plan implemented by a business, which deals with the collection, processing, analysis, and use of data obtained through a variety of sources. This may include the results obtained from current business research, traditional business practice, or historical data about past performances. These data are used to guide strategic decisions. Such decisions can be commercial, political, or environmental.
Some of the major areas in which this type of analysis is required include marketing, customer service, supply, engineering, human resources, and other areas. Today, what is business intelligence has become a very important area, as companies have become increasingly dependent on their IT systems for data mining. Without the necessary tools, processes, and training, data mining will not be efficient. Without IT resources, organizations risk being unable to mine valuable data in a timely manner. Organizations also risk spending excessive amounts of time and money on data mining endeavors that result in little or no productivity.
Data mining can be effective when executed properly. However, if data mining techniques are not well understood and implemented, it can result in a loss of competitive advantage, incur high operational costs, lead to organizational failure, reduce employee productivity, and create significant negative implications for business decisions. Traditional business decision making processes often rely heavily on what is known as “business intelligence”. This is based upon a set of methods, which have been developed over the past several decades, that are designed to support the critical analysis required in making sound business decisions.
In order to create intelligence systems, companies must first build a data warehouse. This is a collection of structured information used to support all of the key decisions made throughout an organization. This data warehouse will contain all of the products, services, marketing trends, technical data, customer preferences, supplier relationships, investment data, and other key decision making criteria.
Building an intelligence platform is much easier than building the actual intelligence system. There are several options available today. Companies can purchase analytic programs created by outside vendors. Most intelligence platform providers provide analytics modules that integrate with traditional data warehouse applications, such as Microsoft SQL Server, Oracle, and the like.
Companies can also directly apply intelligence techniques to their own organizations. These techniques can focus on two main components: measurement results and consumption models. Measurement results are key performance indicators (KPIs) supported by clear and consistent metrics. Consumption models describe how users actually use a service or product. The beauty of applied intelligence lies in its ability to take an intuitive idea and give it clear-cut measurements and scenarios under various business conditions. Apply this concept to operational processes, and the process becomes more data-driven and more sustainable.
Machine learning refers to the process of taking pre-existing data and training computers to recognize it. The best of these techniques can lead to extremely accurate and robust measurement results. Data warehouses and intelligence platforms support the development of data sources. Data sources can be anything from behavioral surveys to financial statements, human behavior profiles to product reviews and more.
Business intelligence solutions can also be called predictive analytics. They are typically used in the areas of marketing, customer service, and business processes. Predictive analytics takes data sources and identifies patterns that can indicate new opportunities. These patterns are then used to create new business processes, or algorithms for existing business processes to further analyze the data. This type of intelligence is most commonly used in the area of advertising and digital media.
Historical data analysis is the opposite of predictive analytics. It looks back at past market conditions to predict where similar situations might occur in the future. While predictive analytics focuses on the future, historical data analysis focuses more on the present. A great example of a descriptive analytics solution is how companies build out their supply chain over time to improve efficiency and sustainability.
As you can see, there is no one answer when people ask what is business intelligence. The answer varies depending on the focus of the researcher. Data-driven business is based around artificial intelligence, Hadoop and other big data solutions, predictive analytics and other forms of data-driven insights. If you are interested in working with any of these fields, an internet-connected home office is a great place to start.