In the modern world of business, some terms have already become known, such as Data Science or Analytics, expressions that refer to the use or application of technology to perform and optimize processes in companies with the use of software or analytical intelligence. According to data released in a study entitled State of the CIO 2019, so-called data analysis shows potential to be the main initiative that will boost investments in 2019. It is, therefore, a priority for this year.

As a result, it has become evident that more and more companies need to pay attention to these factors and learn not to leave strategic planning out of the most important actions in order to guarantee a good base for faster and more accurate decision-making in face of challenges and demands they meet. Learn more about Data Science or Data Analytics in Business Intelligence (BI) and see how your business can benefit from these concepts:

What is Data Science?

Data Science incorporates an area that will be responsible for performing functions that do not only understand past events to understand important information, but also use statistics to assess probabilities of future occurrences. Through the structure to receive, interpret and organize information for correct “reading”, scenarios needs and formulating more accurate actions (another area, often complementary, which is better known as BI).

That is, it is also directly related to the company’s ability to deal with information from various parties to build a good foundation for action. Among the most popular tools on the market today, we have IBM, Watson Studio, SPSS and other tools that help in the intelligent exploration during the work of data scientists such as Jupiter, R, SAS VA, Amazon SageMaker.

The main characteristic of Data Science today is, therefore, not only to be able to interpret what has occurred or occurs in the company through its previous experiences, but also to perform “predictive” analyzes and statistical-based models to “predict” patterns that help in making decisions.

And Data Analytics?

Analytics goes hand in hand with Data Science, and it is often quite difficult – or almost impossible – to completely disassociate both.

Data Analytics refers more to the set of features that are available and the capabilities/ functionalities they offer to transform Data Science into a reality applicable in companies.

What does this have to do with BI?

Finally, as we can see, all these concepts are intertwined with what we call “business intelligence” or even, “data intelligence”, which exemplifies all the potential of extracting important insights for innovation, management, or knowledge in the business through analysis of data and study of what they point out and of what it is possible to do from them.

In some cases, even the so-called “AI” (or artificial intelligence) can be used to some extent in certain applications to customize care and services according to the demands of each consumer. This is the case of bots or retail, more recently, in some situations involving product strategy.

By customizing more and more customer options and developing a better way to study your market based on structured data, companies can find out what is more advantageous to invest in and how to work the added value of what they have to generate more business.

According to the same survey on CIOs (State of the CIOs 2019), mentioned above, it is not only IA that in some cases intertwines with this idea. It has also been raised that 10% is geared towards machine learning (Machine Learning – read more about it here) which in some situations can be employed to facilitate data mining and governance.

Therefore, the company that needs to work efficiently with data and invest in cutting-edge tools can achieve greater potential to compete.

Postado por Kyros Tecnologia em 25 July, 2019