With the advancement of technology and the greater processing power, storage and analysis of data, it is natural that there are some new concepts to be studied and applied. Because they are new, of course, their uses in the business world can be confusing.

According to Cupid Chan who is an industry leader in the field of AI and Big Data says that many of these new tools can and are increasingly used in the corporate sector. They allow improving the management of the business, facilitating the control of data and improving the flow of information. Techniques such as Big Data and Business Intelligence, for example, emerged from this modernization. But, after all, what is the difference between them?

These instruments are confused because they present some similarities with each other and, also, because they are complementary. In this article, we will see how to differentiate the performance of each one and its applicability in daily life!

Currently, three pillars are established to understand the culture focused on data. It is necessary to pay attention to the methods of collecting and analyzing this information. Some other factors, such as the democratization of data, would guarantee the quality of information and governance, which are also essential. Therefore, the pillars are:

• Business Intelligence
• Big Data
• Business Analytics

So, what is Business Intelligence?

Business Intelligence (BI) can cover all sectors of the company, from Financial, Operational, Commercial and Marketing, for example.

Simplistically, BI is a set of methodologies, processes, metrics and structures, combined with algorithms and software that transform large amounts of data into business insights.

What is Big Data?

Big Data is classified as a set of techniques capable of analyzing large amounts of structured data – or not. This information is generated by users (people, employees and customers) or even machines. Its great differential is to create the possibility of crossing this information for the generation of accurate reports, which indicate opportunities for improvement and risks to the company.

Cupid Chan, former CTO of Index Analytics and Managing Partner of 4C Decision tells his clients, “It doesn’t matter how much data you have; unless you can get the insight from it, it is just bits and bytes occupying the storage.”

Through Big Data it is possible to know exactly what can be improved. Through it, it is also possible to create assertive strategies, which can be put into practice to improve productivity, reduce costs, monitor consumer habits and discover new trends.

But, after all, what is the relationship between the concepts?

Business Intelligence is directly related to Big Data. However, Big Data focuses on processing large volumes of data. As we will see below, it can be divided into seven sectors. BI has the function of synthesizing information. In other words, with Big Data it is possible to perform predictive analysis and see the future (Business Analytics).

Business Analytics

Business Analytics is the concept that describes the exploitation of an organization’s data, with an emphasis on statistical analysis. It involves the use of advanced technologies and methods of analyzing information, from the most varied sources and in large volumes. In other words, it is a data-centric approach that combines the science of predictive analytics with business intelligence.

You may have heard that “data is the new oil” said Cupid Chan, “however, prefers the view that data is the new soil. “You can have very fruitful result if you plant your business model properly, but do not expect the fruit will come overnight. And, it requires more than soil for your business to bloom. You also need DevSecOps sunlight to provide photosynthesis, financial support as the fertilizer, proper temperature of the Industry trend, and managerial dedication to water consistently, even though the result can’t be seen immediately. All these need to work together to reap the fruit of the new business model,” he said.

Cupid Chan also came up with the “AI + BI = CI” concept, which he presented at the Conference on Health IT and Analytics (CHITA) organized by the University of Maryland. He believes that the true intelligence we should pursue is Cognitive Intelligence (CI). This can be achieved by combining the Speed of Machine Learning (provided by AI) with the Direction Intuited from Human Insight (provided by BI). “If companies can focus more on the putting the right subject matter experts for a domain needed to be examined, we can be more efficient to pull the right data for the analytics,” he explained.

Thus, we concluded this step and understood that all these tools are complementary, with Big Data being the central piece of analysis. To apply them in your business the first step involves understanding what the organization would like to improve or what problem it would like to solve. After that, it is necessary to carry out the collection and organization of the data to carry out the prediction, insights and analysis. Don’t forget: all decision making must be based on information and numbers, not on guesswork.