Modified:2019-10-09  Published:2019-10-09  Views: 1713
Author: Rakshit
Published in: Information Technology
A Tour Guide To The World Of Data Analytics

Data Analytics is one of the most widely used techniques of almost all the companies in today’s digital world. In this blog, I have given a brief yet sufficient information that will help you in understanding all about Data Analytics. So get ready to understand the fascinating zone of Data Analytic.

 

 

What is Data Analytics?

 Data Analytics

Well, in simple terms, it is a technique used to sort big volume of data in order to extract more direct information in the form of patterns, algorithms, relations, connections, models, etc. that, in turn, add value to companies. The three important attributes of it are volume, variety, and velocity.

Why sudden demand for Data Analytics?

With the increasing digital footprint, there is a surge in demand in understanding the mind of today’s digital consumer. Companies all over the world want to track and sort previous data of their consumers to predict demand of their future needs.
Well, you may wonder if data analytics is so important then what kind of career opportunities it can provide?

Let me quote a study done by IBM that predicts that demand for DATA ANALYSTS will soar up to 28% by the year 2020. That means 150,000 new jobs per year. So, it’s easy to say Data Analytics can’t be ignored in today’s professional world. For a better career in future enroll in data analytics courses.

What are the categories of data analytics?

Descriptive

It is used to describe past occurrences or records. It is REACTIVE IN NATURE because it helps in creating a summary of previous data.

Predictive

It is one of the most popular data techniques because it tells us what will happen in the future as a result of what has happened in the present. It is PROACTIVE IN NATURE as it helps businesses forecast future results.

Prescriptive

As the name suggests, it prescribes the right course of action. It not only tells us what will happen in the future, but it also tells us what actions we can take, in case, some previous prediction materializes in the future.

 

So, what are the languages used in Data Analytics? Actually, a lot of open sources software are available on the internet, but two of the most popular languages are-:

R

PYTHON

 

What are some of the practical uses of data analytics?

Text Analytics

It is used to analyze a customer’s sentiment through his digital remarks.

HR Analytics

Sounds unreal, but data analytics has techniques that can precisely predict the intention of an employee whether to stay with the company or not. Such predictions will help the company save a lot of money as well as resources.

Customer Lifetime Value

It expresses the company’s goodwill towards their existing customers, it also keeps a track of customer’s shopping records which helps the company to provide better services in the future.

Crime Prevention

Data Analytics has been used to create hotspots for tiger poaching prevention in India.

Healthcare

Data analytics is used to collect information about the daily lifestyle of people and predict their risk scorecard for catching diseases like a cardiovascular problem, dementia, aneurysms, etc.

What are the companies that use Data Analytics?

Google-:

As we all know, Google provides several billion search results daily, hence it hires the maximum number of Data Analysts.

Facebook-:

It deploys Data Analytics to understand what its users are talking about so that it can provide better services in the future. It also helps them in distributing advertisements. If you like what you just read about data analytics and want to know more then just enroll in data analytics courses from ExcelR.

Article Comments

0 comments.

There are zero comments yet, why not be the first?

You must be logged in to post a comment.

Please log in or register to comment or reply to a comment.

Articles Search

Featured Articles

Most Popular Articles

Article Categories Expand

10  
1  
1  
1  
0  
6  
0  
85  
7  

There are zero sub-categories in this parent category.

127  
4  
63  
6  
3  
3  
10  
5  
9  
4  
12  
6  
3  
0  
1  
73  
16  
1  
1  
25  
2  
2  
0  
2  
1  
2  
2  
7  
0  
1  
0  
2  
2  
2  
13  
2  
1  
3  
2  
1  
0  
2  
3  
3  
0  
1  
5  
0  
3  
4  
1  
17  
62  
2  
1  
0  
1  
0  
0  
6  
1  
1  
41  
1  
1  
2  
0  
12  
0  
0  
0  
0  
7  
3  
0  
2  
2  
2  

There are zero sub-categories in this parent category.

4  
1  
5  
6  
0  
3  
2  
1  
0  
2  
1  
2  
0  
4  
2  
0  
5  
1  
26  
1  

There are zero sub-categories in this parent category.

0  
1  
0  
1  
0  
1  
0  
1  
0  
0  
0  
2  
31  
1  
20  
3  
2  
0  
0  
0  
0  
1  
1  
0  
1  
0  
0  
0  
1  
0  
46  
0  
1  
5  
0  
2  
2  
0  
0  
0  
0  
2  
10  
2  

Sponsor