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Data analysis: Essential methods, applications and tools.

Data analytics is an essential tool today to gain valuable insights from large data sets. In this article, methods, applications, tools and examples applied in data analysis will be discussed.


Data analysis methods


There are different methods of data analysis, such as (Types of Data Analysis - Saint Leo University, 2023):

  • Descriptive analysis: Allows you to describe the data found in a sample.

  • Exploratory analysis: Investigate and evaluate data about which you have little knowledge to identify patterns or trends.

  • Diagnostic analysis: Specifically addresses the question of why something has occurred.

  • Predictive Analytics: Relies on historical and current data to make predictions.

  • Diagnostic Analysis: Classifies and predicts the probability of a future event or state.

  • Prescriptive analytics: Draws on historical and current data to propose recommendations or solutions.



Data analysis applications


Data analysis has real-life applications in different sectors, such as:

  • Retail commerce

  • Healthcare industry

  • Transport

  • Energy

  • Marketing and publicity


Data analysis and visualization tools


To process and analyze large data sets, special tools and techniques are used (Staff, 2023). Some of the most popular data visualization tools are:

  • Excel

  • Power BI

  • Google Charts

  • Tableau

  • Zoho





Data Analysis Examples


Here are some examples of data analysis in different fields (BlogAdmin & BlogAdmin, 2023):

  • Identification of behavioral patterns in e-commerce customers.

  • Analysis of medical data to identify risk factors in patients.

  • Study of energy consumption trends in an electricity distribution system.

  • Analysis of sales data to identify the best marketing strategies.


In conclusion, data analysis is an essential skill today, and with the right tools and techniques, valuable information can be extracted from large data sets to make informed decisions and improve data understanding.


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