Owing to business intelligence, businesses obtain a great variety of analytical tools at their disposal. Regardless of the distinction in the definitions and business intelligence synonyms, it is worth paying greater attention to the features and components encompassed in BI for a better understanding of the very process. Under the definition, BI included concepts and methods to improve business decision making by using fact-based support systems. Thereafter Howard Dresner suggested an umbrella phrase to define business intelligence without compromising it through a certain technique or approach. The main peculiarity of DSS is that it mostly deals with unstructured or semi-structured decision issues. A decision support system (DSS) in its turn is an information system which involves a knowledge-based system and an interactive software-based system directed at backing decision-taking processes. The dictionary stated business intelligence as an opportunity ability to detain the interrelationships of presented facts in a way to direct to business towards a set goal.Īlthough today’s term of BI acquired its meaning from the decision support systems introduced in the 1960s. Later on, in 1958 Hans Peter Luhn from IBM employed this collocation in his article using a Webster's dictionary definition. Roughly speaking BI is an opportunity to gather meaningful information for the purpose of thorough analysis. That is how business intelligence concept and meaning appeared.
The banker surrounded himself with business intelligence technologies and benefited due to the early awareness of the news. The author described a story where a banker made a profit from the information about the situation around, which he was the first to receive. However, the very term was firstly used in the Cyclopædia of Commercial and Business Anecdotes in 1865 by Richard Millar Devens. Nevertheless, some say BI had descended from business reporting and didn’t reach far since then. Today business intelligence is often taken as a marketing catchword in relation to the splash of big data and data analysis. Consequently, owing to business intelligence systems and services organizations get empowered to estimate current product demand and supply in the market and choose the most appropriate development pattern. After being combined the data serve as a completely new set of information through which a user can create complex reports and attain new insights for the competitive edge and long-lasting sustainability. Whereas internal data are drawn from inside company sources (finance, marketing, sales, hr), external data represent all data outside the company’s operating systems. To that end, the best method for a business will be to merge external and internal data to analyze them combined together. As a rule business intelligence programs are utilized both for taking rapid business decisions and strategizing.Īs for rapid solutions, also known as operational decisions, they customarily comprise product marketing and price formation when it comes to strategy developing - a user would need to determine priorities, targets and the field of concern. Those technologies and methods are traditionally intended to facilitate big data interpretation by searching insights for a business, which otherwise wouldn’t be obtainable. Depending on a tool used by an enterprise or a company BI includes current, historical and predictive information of operations and transactions. To put it simply Business intelligence with a help of BI architecture incorporates all the technologies and methods to analyze data belonging to the business. According to Gartner glossary business intelligence (BI) is an umbrella phrase that involves applications, infrastructure, tools, and best practices which ensure access to the analysis of the requisite information to boost and enhance performance and decisions with the help of multidimensional libraries, forecasts, ad-hoc analytical reports, etc.
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