Business Intelligence/Data Analytics: Differences and Complementarities

Business Intelligence (BI) or business intelligence

Business Intelligence (BI) records, studies and acts on company data for future action. Data that usually explains the company’s past performance. BI provides elements that help leaders and managers assess the company’s trajectory in terms of progress.
for treatment Business Intelligence (BI), There is a set of tools that can extract information about companies. These tools analyze a company’s history, including successes and underperformance. BI provides a flow of information, such as a single tool Click sense With a data visualization solution, to initiate improvement actions.

Concept of data analysis or business analysis

Data analytics transforms raw data into meaningful information to infer patterns, measure trends, and transform patterns into business growth. In this process business managers analyze data and try to bring innovation, analysis allows a business to make unique changes to increase the level of success.
Data analytics (DA) or business analytics involves predictive analysis based on past patterns that predict future growth. Many tools dedicated to data analysis help leaders and managers adopt a relevant strategy for their business.
Data analytics transforms raw data into meaningful information, and analyzes future trends using predictive models and technical tools, helping the manager grow the business based on a set of algorithms.

Differentiate between BI and Data Analytics

In terms of innovation

Business intelligence revolves around operations while the second leans more towards innovation. Because business intelligence collects raw data and evaluates a company’s historical growth, it may or may not emphasize innovation.
Data analytics transforms raw data, analyzes it to define future trends and patterns, enabling managers to engage in operations in innovative ways. Business intelligence, unlike data analytics, stores data in a raw format that is combined into an algorithm that helps extract fundamental patterns.

When the future can be predicted

Business intelligence is more backwards while data analytics is more forward. BI emphasizes the study of data based on situations that have already occurred in the company’s history. Data analytics highlights future patterns that are likely to occur in the future. BI is considered more relevant when it comes to past patterns of operations that lead to the formation of data for DA.
BI looks at the historical records of the business while DA applies future innovative trends for better growth Business intelligence is more concerned with achieving goals that are already part of business goals and data analytics adds goals to progress it according to following patterns. Hence a distinction is made between objective addition and objective achievement.

Different ideas fit together

Both concepts are essential, business intelligence and data analytics help collect raw data and analyze it for future action. Even though the 2 concepts seem similar, the main difference is the decision-making process for achieving objectives and data analysis, augmentation and study of business models according to data collected during operations passed for BI.
Business analytics deals with the transformation of raw data into meaningful elements to ultimately draw future trends on a predictive basis by questioning past patterns and strategies.
If the two concepts are very different from each other, they overlap in a way that business intelligence cannot do without business analytics and vice versa.

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