The main types of data analysis

 

There are four main types of data analysis: predictive, prescriptive, descriptive, and diagnostic. Get to know these types of data analysis and see which one will be ideal according to the objective of your project.

 

 

Data-based decisions

The importance of companies’ strategic decisions being based on data (data-driven) is no longer debatable. It is true that all businesses must analyze the data collected in order to use them as a tool to support decision-making. For this, we have to analyze case by case which type of data analysis we should use according to the problem we are going to try to answer.

 

Data analysis project phases

In a data analysis project we go through several phases in order to transform data into knowledge, as well as to be able to give the best answer to a business problem.

 

The main phases of a data analysis project are:

– Definition of the problem/objective of the project;

– Collection of data from different sources of information;

– Data preparation and processing;

– Data analysis (using Artificial Intelligence techniques – Machine Learning and Deep Learning, Cognitive Computing, Data Mining, Text Mining, …);

– Creation of reports with Insights / Presentation of project results.

 

An important phase is data analysis, and this is where we define what type of data analysis we are going to use according to the purpose of the project.

 

 

 

4 main types of data analysis

Each problem requires a different type of data analysis according to its specificities. There are four main types of data analysis, which are as follows:

 

– Predictive analysis: This type of data analysis is based on predicting future scenarios/trends based on past patterns and facts (historical data). Models are built, usually based on Machine Learning, Deep Learning and Artificial Intelligence techniques. However, this is not a “crystal ball”, it does not say what will happen. The objective is, through these models, to say what is likely to happen in the future under certain conditions.

 

– Prescriptive analysis: It is also known as “recommendation analysis”. It uses predictive analysis models and descriptive analysis tools. These aim to generate action recommendations in order to optimize the strategies adopted and thus achieve the best results.

 

– Descriptive analysis: Also known as “exploratory analysis”, this analysis aims to describe the objects, behaviors or events that are being analyzed. It is an analysis unrelated to the past and future. Uses statistical tools in order to understand and explain the data.

 

– Diagnostic analysis: Uses data to seek to understand the causes of a particular event or event that has already occurred. This analysis seeks to identify cause-effect relationships as well as relationships between data. It is also intended to answer the following questions: Who? When? Where? As? Why?

 

 

 

Make data analysis part of your business day-to-day

Now that we have listed the 4 main types of data analysis, it is important to mention that it is advantageous for companies to automate data analysis processes regardless of the type of data analysis applied. For this, there are several tools that can help with data analysis, for example IBM SPSS.

 

PSE provides consulting services in the analytical development of organizations and carries out data analysis studies and projects to respond to business problems.

 

If you want to start using data analysis as the basis for your informed strategic decisions, PSE is the ideal partner as it has around 30 years of experience transforming data into knowledge.