Throughout our blog, we have discussed the importance of being able to collect data and make decisions based on the analysis of the data presented.
But, what is?
Is a process that consists of analyzing information to extract meaningful data from a certain 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 make decisions based on patterns, behaviors, trends or preferences, thanks to a collection of data.
A clear example would be that companies can use analytics to identify their customers’ preferences, purchasing habits and market trends and then build from those learnings, create strategies to address them and manage changing market conditions.
Now, you’re probably wondering: What are the different types of analytics?
According to this article bcm.com, there are multiple analysis methods and techniques for data analysis, but there are four types that apply to any data set:
1.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.
2.Diagnostic: A descriptive analysis based to understand the “why” something specific happened. It enables users to gain insight into the exact information of the root causes of past events, patterns, etc.
3.Prophetic: Predictive analytics that will predict what will happen in the future. This will combine descriptive and diagnostic analysis data and use ML ( Machine Learning) and AI ( Artificial Intelligence) techniques to predict trends, patterns, problems, and more.
4.Preceptive: Taking predictions from analytics and that go one step further by exploring how the assumptions will happen. This can be considered the most important type of analysis as it allows users to understand future events and adapt strategies to handle any predictions effectively.
It’s clear that data is the future and easily accessible data is a key component for any industry. Big data, data analysis and data science all help decision makers understand and extract essential information.
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