Since the beginning of history, data has been the starting point of all the amount of information that surrounds the world, especially since a few years ago, where the technological capacity at infrastructure level has been growing by leaps and bounds to support the storage of Bytes until reaching Tebibyte, and with the certainty that new measures will have to be invented; mainly in companies, where data as a unit has been the input that generates sources of information that allow within the organization to generate indicators and metrics for future decision making.

Data Analytics methods have a very important relevance in the digital transformation of companies, since they allow us to transform data into concrete actions for the business. The analytical universe contemplates different complexities depending on the value to be obtained with the data and the challenge that this implies from the technological point of view.

Through this article we will understand the approach of each of the types of analytics and the use case for companies:

The different types of analytics have made it possible to analyze the behavior of a process, analyzing past data through descriptive analytics and allowing a better understanding of the data through BI and Data Mining tools, understanding what happened.

Diagnostic Analysis

Data Analysis allows us to answer the questions why things have happened and to identify behaviors and patterns that allow organizations to define an action strategy to correct or improve.

Predictive Analytics

Based on real-time information and using statistical modeling tools or Machine Learning, they allow us to predict the behavior of a process and anticipate the future in order to make decisions that may favor a particular business case.

Predictive Analytics

It aims to generate an action plan or recommend other actions based on the resources and data being taken, predictions and other external variables leveraged on the use of combinatorial optimization algorithms called Operational Research.

From these concepts we can see the importance of Analytics as an engine of digital transformation within organizations during different timelines being a technological trend that helps us to improve efficiency in the company and generate new experiences for the customer in the improvement of a service or process, according to the following major stages to be taken into account by the Management of the Organization in the implementation of this type of projects:

• The selection of Digital Analytics tools according to their cost-effectiveness, field of expertise and according to the complexity of the business case
• Processing of the information collected through the selected analytical models and the questions to be answered
• Data-driven decision making to meet the organization’s strategic objectives as reflected in its KPIs

During my experience in the position of presales Software Architect of my organization, the interaction with several customers and the understanding of their needs, I have identified that it is of great importance the Data Analytics, using it as the main input to the tools that allow the analysis, collection, organization and processing of the same, of what has happened in the past, with what is currently available, including the improvement of processes and organizational culture, formed by each of the members of the organization and the future projection reflected in its Vision, to help its customers in solving their business problems; all this will not be possible if the sponsor or management roles of the organization are not clear about it.

Understanding that data is dynamic, as well as its processes in companies and interaction with people, will serve organizations to identify their Roadmap towards their digital transformation !