Business intelligence (BI) is a technology-driven process for analyzing data and providing actionable information that helps executives, managers and workers make informed business decisions. It includes data analysis and business analysis, but uses them only as parts of the entire process. There are three main types of BI analysis, which cover many different needs and uses: predictive analysis, descriptive analysis, and prescriptive analysis. Tableau is a popular BI tool known for its easy-to-use data visualization capabilities.
It supports data sources such as Microsoft Excel, Box, PDF files, Google Analytics and more. Its versatility extends to the possibility of connecting to most databases. It also offers live visual analysis, an interface that allows users to drag and drop buttons to quickly detect trends in data. QlikSense is another BI tool that emphasizes the self-service approach, meaning that it supports a wide range of analysis use cases, from applications and guided panels to personalized and integrated analytics.
It offers an easy-to-use interface optimized for touchscreens, sophisticated artificial intelligence, and high-performance cloud platforms. Its associative exploration capability, Search & Conversational Analytics, allows users to ask questions and discover useful information, helping to increase data knowledge for those who are not familiar with BI tools for the first time. Dundas BI is a browser-based BI tool that has existed for 25 years. Like Tableau, Dundas BI includes a drag-and-drop feature that allows users to analyze the data on their own, without involving their IT team.
The tool is known for its simplicity and flexibility through interactive dashboards, reports and visual analysis. Since its creation as a data visualization tool in 1992, it has evolved into a comprehensive analysis platform that can compete with the new BI tools available today. Sisense is an easy-to-use BI tool that focuses on simplification and streamlining. With this tool, you can export data from sources such as Google Analytics, Salesforce, and more. Its on-chip technology allows faster data processing compared to other tools.
Key features include the ability to integrate white label analytics, which means that a company can fully customize services to their needs. Like others, it has a drag and drop function. Sisense allows you to share reports and dashboards with your team members as well as externally. Every day, in every company, thousands of operational tasks are executed. Companies rely on these activities, and any inefficiency or error can significantly affect performance.
Business intelligence tools can be used to support the type of operational reports that allow real-time monitoring of day-to-day events. Therefore, problems can be identified and corrected instantly. A company's ability to anticipate trends is critical to maintaining organizational flexibility and agility. In addition, historical data must be used to predict future events to ensure effective strategic planning. That's why many business intelligence tools include predictive analytics that allow for fast and highly accurate forecasting. Nowadays, companies maintain enormous volumes of information.
And sometimes, sorting through that data to find what's most relevant can be a daunting task, especially for business users who don't have technical knowledge. The data mining functions of many business intelligence tools can help locate and extract the most important information from large data sets, making it much easier for users to access and take advantage of the information they really need. If business conditions change, intelligent tools can automatically detect anomalies and you can react to disruptions as they arise. Most business intelligence tools offer in-depth online analytical processing (OLAP) capabilities, allowing users to manipulate data instantly in an unlimited number of ways so that it can be reviewed from multiple perspectives. As organizations strive to become more customer-centric, they are turning to business intelligence tools to collect and consolidate customer data found in various systems such as CRM, accounting, and support service applications. Access to a central business intelligence platform allowed Schwab to view its branch data in a single view.
