In other of our articles we have explained the great importance of being able to collect data and make decisions based on the study of them, but to get to that point, we must first go through the analysis of that data. That is why in this article we will tell you everything you need to know about it.
So without further ado, let’s get started!
What is data analysis?
It is a process that consists of analyzing information to extract meaningful data from a given set. This analysis technique is carried out with Big data in most cases, although it can be applied to any data set.
The main objective of data analysis is to help people and organizations to make decisions based on patterns, behaviors, trends or preferences, thanks to a collection of data.
A clear example of this is that companies can use analytics to identify customer preferences, buying habits and market trends and then build strategies to address them and manage changing market conditions.
What are the types of analytics?
According to the bcm.com article, there are multiple analysis methods and techniques for data analysis, but there are four types that apply to any data set:
- Descriptive: refers to understanding what happened in the data set. As a starting point in any analysis process, descriptive analysis will help users understand what happened in the past.
- Diagnostics: Consider descriptive analysis and rely on it to understand why something specific happened. It thus allows users to gain insights into the exact information about the root causes of past events, patterns, etc.
- Prophetic: Predictive analytics will predict what will happen in the future. This will combine descriptive and diagnostic analytics data and use ML and AI techniques to predict trends, patterns, problems, among others.
- Prescriptive: this takes predictions from predictive analytics and goes a step further by exploring how the predictions will happen. This can be considered the most important type of analytics, as it allows users to understand future events and adapt strategies to handle any predictions effectively.
Finally, we can assure that data is the future, which is why everything related to it, such as big data, data analytics and data science, will help people and industries to deal with a large amount of data and extract valuable information from it.
As data is understood to be very important, it will become essential technology components for any industry.Want to learn about all the things we can do with data? Click here