What Is Data Analysis?

Date First Published: 28th February 2024

Topic: Computer Systems

Subtopic: Computer Software

Article Type: Computer Terms & Definitions

Difficulty: Medium

Difficulty Level: 5/10

CONTENTS

Data Analysis Process
Types Of Data Analysis

Learn about what data analysis is in this article.

Data analysis is the process of working with data to discover useful information, support decision-making, and make conclusions. An example of a data analysis technique is data mining, used to discover patterns, trends, and other valuable information. Data analysis makes use of a range of analysis tools and technologies, such as SQL, data visualisation, machine learning, and spreadsheets.

Data Analysis Process

The process of data analysis includes:

Data requirements - The data is specified based on the requirements of those conducting the analytics. The problems that need to be solved, what will need to be measured, and how it will be measured need to be considered.
Data collection - The data is collected from a variety of sources. A list of data sources is available for study and research. Data collection can come from primary sources, such as internal records or secondary sources, such as social media.
Data processing - Data must be processed or organised for analysis. This may involve placing data into rows or columns in a table format.
Data cleansing - The process of correcting incomplete, duplicate, or incorrect data. The need for data cleansing comes from problems in the way that data is entered and stored.
Data analysis - Finally, the data can be analysed once the data is cleansed. To understand the data, analysts may create analytical models that can help make informed decisions.
Communication - Once data is analysed, it may be reported in different formats to users of the analysis to support their requirements. The users may have feedback, which will result in additional analysis.

Types Of Data Analysis

Types of data analysis include:

Descriptive analysis - This helps describe or summarise quantitative data by presenting statistics, such as averages, lowest values, highest values, and more.
Diagnostic analysis - Diagnosis analysis determines the "why" behind the data rather than a summary.
Predictive analysis - Uses data to form predictions about the future. It answers what might happen in the future.
Prescriptive analysis - Takes all the insights gathered from the first three types of analysis and uses them to make recommendations.