Business IntelligenceBusiness intelligence (BI) is the collection of strategies and tools used to analyze business information. It is a set of processes, technologies and architectures that analyzes raw data and transforms it into actionable information to help executives and end-users make informed business decisions, that drives profitable business actions. It is a suite of software and services to transform data into actionable intelligence and knowledge.

Business intelligence is a suite of software and services to transform data into actionable intelligence and knowledge. It is used to improve an enterprise’s access to data and utilizing that data to increase profitability. Firms that use business intelligence can use the collected data to get an insight into their business processes, make strategic business decisions for improved productivity, increased revenue, and accelerated growth.

Some of the potential benefits of Business Intelligence tools are;

  • Analyzing customer behaviors, buying patterns, and sales trends
  • Accelerating and improving decision-making.
  • Optimizing internal business processes.
  • Increasing operational efficiency.
  • Driving new revenues.
  • Gaining competitive advantage.
  • Assisting companies in the identification of market trends.
  • Spotting business problems that need to be addressed.

Business intelligence can help companies make better decisions by showing present and historical data within their business context which enables business intelligence tools to support both strategic and tactical decision making processes.

IT professionals and data analysts used to analyze and produce reports for business users using business intelligence. However, now business executives and other workers are increasingly using business intelligence tools like data discovery and dashboards. Every business and organization has questions and goals. They gather necessary data, analyze it, and determine what actions to be taken to reach their goals. Data analytics and business analytics are part of the business intelligence process. Business intelligence takes the models and algorithms drawn from data analytics and breaks the results down into actionable language.

Types of Business Intelligence Tools


Reporting is an important part of business intelligence that focuses on visualizing data in different types such as tables, graphs, and charts. End users can create, edit, and manipulate pre-build or canned reports with the help of ad hoc reporting. This ability has empowered end-users for quicker visualization of pertinent business data.

With smarter reporting tools, one can understand the insights in activities and use that knowledge to make better decisions for the company. Businesses can save more by using business intelligence reporting tools to evaluate their spending patterns and see where they may be spending more than the industry average. GPO (Group Purchasing Organization) and Una (a software company) offer great spend visibility and procurement strategy tool replacing spreadsheets and making it easier for businesses to understand their financial positions.


Dashboards spot pertinent information and present the data in a clean and easy to understand formats. For executives and business owners, a good dashboard tool can speed up the decision-making process by highlighting the most relevant data points. They can simply drag and drop dashboard widgets to customize their view and generate quick visualizations for presentations. Dashboards are also helpful by allowing executives and leadership teams to identify issues, intervene, and take corrective measures in near real-time rather than waiting for the reports.

Predictive Analytics

Predictive analytics tools help businesses predict potential shifts and make proactive moves and strategies before the others in the market respond. Consider an example of SAP, a major provider of business intelligence tools, including predictive analytics tools that can help executives test theories before trying them in real life. With the help of predictive analytics, companies can take quantitative risks, try new ideas before implementing them. With the help of such tools, companies get a better understanding of risks, rewards, and challenges and move ahead more confidently and quickly.

Data Exploration

Data exploration helps us to understand our data, its structure, strengths, and weaknesses. Data exploration is typically conducted using a combination of automated and manual activities. Automated activities can include data profiling or data visualization which gives the analyst an initial view into the data and an understanding of key characteristics. This is often followed by manual drill-down or filtering of the data to identify patterns identified through the automated actions. All of these activities are lined up at creating an understanding of the data in the mind of the analyst, and defining basic metadata (statistics, structure, relationships) for the data set for further analysis.

Data Cleaning

Data cleansing tools prepare data sets for analysis by removing false, incomplete, duplicated and outdated data points, fixes the problem, and makes sure that all such issues will be fixed automatically in the future. Businesses must ensure that the personal information of many different people and organizations is kept safe and organized.

Having accurate information is important for everyone. It’s important for businesses to have accurate customer information, so they can get to know their audience better and contact customers if needed. Having the newest, most accurate information will help you get the most out of your marketing efforts.

Data cleansing is important as it improves data quality and increases overall productivity. With all the highest quality information in hands, employees do not have to wade through countless documents and make the most of their work hours.