Data Analytics vs Data Analysis: What’s The Difference?

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Posted By IN2INGLOBAL on 2021-11-16 4:04 AM

Description

Is Data analysis and data analytics are Two terms for the same concept or different having related terms? 

Normally, the common misunderstanding is that both data analysis and data analytics are the same, but the difference is:

Data analytics is the broad field of using data and tools to make business decisions.
Data analysis, a subset of data analytics, refers to specific actions.
To make more clear, let’s look at both terms with examples, and tools.

What is data analytics?
The term data analytics refers to the process of examining datasets to draw conclusions about the information they contain. Data analytic techniques enable you to take raw data and uncover patterns to extract valuable insights from it. 

Data experts, including data scientists, engineers, and analysts to play around the data and make it easy for the rest of the business process and understand these insights.

Initially raw data does not reflect value, but to provides value, data analytics used both human- and machine-enabled steps to determine, interpret, visualize, analyze and provides data patterns in order to leverage business strategy and meaningful outcomes.

A data analytics experts provides a better strategy for the business to run. Data analytics can support on:

Find historical trends
Discover opportunities
Predict actionable insights
Business decisions
The approach of a data analytics is very organized and structured, consisting of many calculated and business process steps. The systematic approach guides data analytics to uses many different activities and work on different types and volumes of data sources.

In current data world, data analytics is majorly covered in data science, machine learning, and applied statistics. One of the main outcome of data analytics is to provide business reports including different data visualization that can tell the story of the most undiscovered points of the rest of the business.

The major highlight areas of data analytics leverage business opportunities are:

to understand the actual facts and how to engage customers for the sales or marketing processes. A cloth seller might use its data to realize that its demand for woolen cloth increases in winter season, that means there is no need to give discount the prices during high demand.
An increase mortality in pandemic might suggest to take proactive preventative measures.
Data analytics processes:
The data analytics involves many different processes. The process flow are:

Collecting and ingesting the data
Categorizing the data 
Managing the data 
Storing the data 
Performing ETL 
Analyzing the data 
Sharing the data