Machine Learning and Business Intelligence are complementary but different.
These two A.I. disciplines are often used in the business world, but they have significant differences in their approach and objectives. How to distinguish one from the other…?
BI focuses on the collection and analysis of business data in order to improve decision making and operational efficiency. It uses specialized techniques and tools to transform data into useful information and present it in a clear and accessible way. Its approach is more structured and systematic, relying on historical data to make predictions and decisions.
On the other hand, ML develops systems that can learn and improve themselves through the analysis of large amounts of data. Instead of relying on predefined rules and algorithms, these systems use machine learning techniques to identify patterns and trends in the data and make decisions based on them. ML is a more dynamic and flexible discipline, and can be used to solve a wide variety of problems, from predicting the price of a product to fraud detection.
What are the two main differences between BI and ML?
1.The approach – While BI focuses on collecting and analyzing historical data to improve decision making, ML is based on developing systems that can learn and improve themselves through data analysis. This means that ML is better suited for solving problems that change over time or are difficult to define precisely, while BI is better for more structured and predictable problems.
2. The amount and type of data used – BI works with structured data, i.e., data that is organized in a clear and easily accessible way (sales or inventory records, for example). ML, on the other hand, is able to handle large amounts of unstructured data (images or text, for example) and can extract valuable information from it.
In short, ML and BI are two branches of A.I. that differ in approach and type of data used, both being indispensable in any area for decision making and operational efficiency.
Nubeprint offers a managed MPS solution with dynamic algorithms and filters. In 2013, it develops the first A.I. engine for MPS and, since 2017, it has a Machine Learning (ML) developed specifically for MPS: through this machine learning, the system develops pattern recognition and the ability to learn continuously, with predictions based on Big Data, after which it makes the necessary adjustments without having been specifically programmed to do so.
Nubeprint invests 30% of its resources in R&D&I, currently developing BI systems, and obtained at the end of 2022 the Innovative SME certificate (Innovative SME, AENOR EA 0047).
