Business intelligence (BI) is a decision support system, whose aim is to help make business decisions, strategic as well as operational/tactical. It uses an assortment of resources and techniques for gathering, transforming, storing, and analyzing data.
The technologies utilized include data warehousing, online analytical processing (OLAP) or multidimensional analysis, data mining, analytical and statistical tools, querying and reporting tools, data visualization, dashboards, scorecards, among others.
In the current environment, business intelligence and data warehousing are used synonymously. Most data warehouse vendors now promote their products as business intelligence software, rather than data warehouse software. In practical terms, a data warehouse is the infrastructure component of a popular and widely used system that is implemented to achieve business intelligence.
Typically, we use the following broad definition: Business intelligence is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making. When using this definition, BI also has to include technologies such as data integration, data quality, data warehousing, master data management, text, and content analytics, and many others that the market sometimes lumps into the information management segment. Therefore, we also refer to data preparation and data usage as two separate, but closely linked, segments of the BI architectural stack. We define the narrower BI market as: A set of methodologies, processes, architectures, and technologies that leverage the output of information management processes for analysis, reporting, performance management, and information delivery.
As this definition indicates, data warehousing is a technology that is included in business intelligence. However, it needs to be noted that although data warehouses provide data to business intelligence applications, all BI applications are not dependent on data warehouses to provide them with the data that they need.
Business intelligence has historically been focused on strategic decision making and analytics. Operational business intelligence, or operational BI, aims to provide information and insights that are operation-focused, with a time frame that can extend from near real-time to a few years. Its objective is to enable decision making that focuses on day-to-day operations rather than strategic decisions which, previously, was the primary focus of business intelligence. Operational business intelligence benefits an extensive range of users who, sometimes within minutes or a few hours, can use it to run, manage, or optimize time-sensitive business operations.
The growth in business intelligence will be apparent in some of the current trends. For example, it is expected that there will be an increase in the use of software-as-a-service, as companies try to obtain business intelligence capabilities without being encumbered with the implementation and support of a BI infrastructure. Other trends in the business intelligence space include advanced analytics, cloud computing, unstructured data analysis, visualization, and so forth.