The concept of business intelligence was first given in the year 1865 by Richard Millar Devens. Later in 1958, Hans Peter Luhn, a famous computer scientist at IBM, made efforts to explore the potential of technology in the field of business intelligence. His extensive research helped IBM to establish some valuable methods for effective analytics platforms.
The recent developments in the field of business intelligence are focused on self-service BI applications, and they allow non-tech-savvy users to benefit from automatic analysis and reporting. If you are new to the field of business intelligence, you may have several questions in your mind. Don’t worry! The article below will provide you essential information to understand the core definition of business intelligence and its working.
What is business intelligence?
Business intelligence is basically an umbrella term that links to the processes, tools, and infrastructure used by organizations to analyze, identify and access relevant business information. The growing range of businesses these days prefers using the potential of business intelligence software to extract valuable insights from large volumes of data available from the field.
Business intelligence software provides some easy-to-digest details about data in the form of user-friendly dashboards, reports, graphs, and charts. Business intelligence users can access a variety of information from third parties, in-house sources, and social media as well. Moreover, these software are capable enough to process all types of data, including current, historical, unstructured, and semi-structured as well.
The business intelligence systems and tools are used with both external and internal data sources to capture information like market trends, competitive intelligence, industry pain point, commonalities in several lost opportunities, and insights about key stakeholders.
Within the past few years, the role of business intelligence has shifted from IT management to core business functions. Years ago, companies were able to address complex reports, data analysis via business intelligence solutions. However, today it has become the most preferred tool for creating accessible and intuitive business intelligence solutions in almost every sphere of work.
How does business intelligence works?
Business intelligence mainly relies on data warehouses for accessing baseline information. The data warehouse aggregates information from multiple sources into a central system while extending support to business reporting and analytics. The software sends queries to the warehouse and provides results to end-users in the form of maps, charts, and reports.
Data warehouses may have an online analytical processing engine that can handle multidimensional queries actively. For instance: What are the profits of our eastern region versus western region for the year 2021 as compared to the year 2020. For such queries, it is important to use some powerful technologies in the system that can work efficiently for complex analytic calculations, handle data discovery, perform predictive analytics and facilitate business intelligence. The main benefit of using efficient analytical processing engines is that they can provide consistent information and perfect, accurate calculations to enhance product quality, process improvements, and customer interactions. The latest business intelligence solutions are capable enough to ingest and extract raw data with the help of advanced technologies such as Hadoop.
Organizations can receive a desired range of benefits from technologies only when they can fully access processes, operations, gauge market, drive improvement, and understand the needs of end-users. They require the right set of tools to handle data patterns and to find the best solutions. The best Business Intelligence software supports the decision-making process by:
- Connecting to an extensive range of data systems as well as data sets, including spreadsheets and databases.
- Offering deep analysis, understanding patterns in data, and helping end-users to uncover crucial hidden relationships.
- Presenting relevant answers with more compelling and informative data visualizations such as graphs, charts, maps, and reports.
- Enabling comparisons of data in different scenarios.
- Providing drill-down, drill-through, drill-up features while enabling users to investigate various data levels.
The ongoing advances in business intelligence and analytics systems are expected to integrate machine learning and artificial intelligence to streamline complicated tasks. These capabilities can also accelerate the enterprise’s ability to analyze data and gain insights at a deeper level. The artificial intelligence-based systems can read all sources automatically while grabbing the most relevant information to lead decision-making.