Business Intelligence (BI)

Business intelligence is a data analysis process aimed at boosting business performance by helping corporate executives and other end users make more informed decisions.

Business intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information to help corporate executives, business managers and other end users make more informed business decisions. BI encompasses a variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against the data, and create reports, dashboards and data visualizations to make the analytical results available to corporate decision makers as well as operational workers.”

Companies can benefit greatly from business intelligence programs by improving decision making, optimizing business processes, increasing operational productivity, getting ahead of their business rivals with their competitive advantages. Identifying market trends can also be achieved with Business intelligence systems.

BI analysis can support strategic and tactical decisions by processing historical data and comparing it with present data to predict future movements.

In early stages of BI tools were used by data scientists and other IT personal but with development of self-service BI business managers and workers are able to use BI software themselves.

Business Intelligence tools

Business intelligence tools are application software that are used to retrieve, analyse, sort, filter, process and report data. Some of the top BI tools are:

  1. Spreadsheets – most commonly used is MS Office Excel
  2. Reporting and Querying – usually used companies own software to report, query, sort, filter and display data
  3. OLAP – Online Analytical Tools helps users with interactive analysing data from multiple sources in a multidimensional view.
  4. Digital dashboards – real-time user interfaces that are showing graphical presentation of the current status.
  5. Data mining – discovering patterns in large data sets involving different methods (artificial intelligence, machine learning, statistics, database systems)
  6. Data warehousing – central storage location of data. It is created by integrated data retrieval from different sources. It is used to store data for future analysis.
  7. Decision engineering – framework for decision making. Usually brings several techniques together (analytics, reasoning, machine learning) to overcome the issues in decision making
  8. Process mining – analysis based on events logs stored in an information system which is aimed at providing information for process analysis
  9. Business performance management – set of processes for managing the performance of a business
  10. Local information systems – designed to support geographic reporting

Business Intelligence


You can read below about one of the great examples where Tesco was using BI to save millions of pounds.

Tesco’s Legendary Big Data Benefits

Tesco, the largest retailer in the UK, was one of the first major companies to discover the endless benefits of big data analytics. Beginning in the mid 1990s, Tesco introduced its own loyalty program with the Clubcard. Many competitors used similar cards as a means to target discounts and coupons, however, Tesco realized the value of the insight it would give into its customers’ behavior patterns.

Tesco began processing the huge flood of data coming in from these cards, and was able to better target mailings of vouchers and coupons to customers, resulting in a huge increase from 3% to 70% in rate of coupon redemption. Seeing its analytics approach work, Tesco began applying it to other fields.

One of the company’s most profitable uses of analytics, was observing historical sales and weather data and using predictive analytics to optimize their stock-keeping system. By being able to forecast sales by product for each store, Tesco was able to save 100 million pounds ($151,718,000 US dollars) in stock that would have otherwise expired and thus wasted.

Now following Tesco’s lead, other competitive retailers are finding creative ways to use big data analytics in order to improve customer satisfaction and increase profits.”