Among other things, it will be possible to know what is needed to improve from previous events.
Written by William Díaz Tafur
Data analysis is vital for companies because, from this point on, it will give the answers that the business needs to be able to innovate in any area.
Furthermore, it is that the determinations taken from the data give a very high rate of effectiveness. In this way, it will be possible to know what is needed to improve from previous events, since it is not the same to make a decision blindly or guided by instinct as one taken from data obtained from the previous operation.
To carry out operations.
On the other hand, the data can be used in an application that works automatically in the performance of operations and in which, based on previous situations, it makes the decision itself or in the visualization step, it can be used to that a person look at them and make decisions from them.
Similarly, the hypotheses or theories raised by companies in their business area are validated with the results of the more or less intelligent analysis of the data they already possessed or are beginning to process thanks to data engineering.
Uses and tools
The most common uses are log analysis, e-commerce personalization or recommendation engines, fraud detection and financial reports, among many others.
Moreover, if we refer to tools for data analysis, some depend on the type of analysis needed. The best known are the Apache frameworks for big data, or they can be used on AWS in the EMR service.
Machine Learning
In data analysis, there is also what is known as machine learning techniques, which allow a “machine” to learn from the past data for the analysis of current information.
For example, being a company dedicated to electronic commerce, a machine learning model can be trained so that, given a transaction, it says whether it is fraud or not.
This model, previously trained with the historical transaction data of the business and the more data from the past it has, the more effective it is and, in turn, it learns the more it is used.
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