Business Intelligence (BI) or business intelligence
Business Intelligence (BI) records, studies and works with company data to perform in the future. Data that generally explains the company’s past performance. BI provides elements that help the leader and managers to assess the course of the company in terms of progress.
To treat the Business Intelligence (BI), there is a set of tools that can extract information about the company. These tools analyze the company’s history with successes and underperformances. BI provides a flow of information, a single tool like QlikSense with a Data Visualization solution, to initiate improvement actions.
The concept of Data Analysis or Business Analytics
Data Analytics transforms raw data into meaningful information to infer patterns, gauge trends, and transform patterns to drive business growth. In this process business managers analyze data and strive to bring innovation, analytics allow 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 reflect future growth. Many tools dedicated to data analysis help leaders and managers adopt a relevant strategy for their business.
Data Analytics converts raw data into meaningful information, and analyzes future trends using predictive models and technical tools, helping the manager to grow the business based on a set of algorithms.
Differentiators Between BI and Data Analytics
In terms of innovation
Business Intelligence revolves around the operation while the second is more inclined to innovation. Since Business Intelligence collects raw data and assesses a company’s historical growth, it may or may not emphasize innovation.
Data Analytics converts raw data, analyzes it to define future trends and patterns, enabling managers to engage in operations in innovative ways. Business Intelligence, unlike Data Analytics, saves data in a raw format which is merged into an algorithm which helps to extract the basic patterns.
When it comes to predicting the future
Business Intelligence is more backward-looking when Data Analytics is forward-looking. BI emphasizes the study of data based on situations that have already occurred in the company’s history. Data Analytics tends to highlight future patterns that may occur in the future. BI is found to be more relevant when it comes to past patterns of operations that led to the formation of data for DA.
BI targets historical records of the business while DA implements innovative trends in the future for better growth. Business Intelligence is more concerned with achieving goals that were already part of business goals, and Data Analytics leads to adding goals to progress it according to the patterns to follow. A distinction is therefore made between the addition of objectives and the achievement of objectives.
Different concepts that fit together
Both concepts are essential, with Business Intelligence and Data Analytics helping to collect raw data and analyze it for future operations. Even if the 2 concepts seem similar, major differences, the achievement of objectives and the decision-making processes for Data analysis, the study of growth and business models according to the data collected during operations passed for BI.
Business Analytics deals with the transformation of raw data into meaningful material to ultimately draw the trends of the future on a predictive basis by questioning past patterns and strategies.
If the two concepts are very distinct from each other, they overlap in such a way that Business Intelligence cannot do without Business Analytics and vice versa.