What is Data Analytics?

Without Big Data Analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”

  • Geoffrey Moore, American Management Consultant and Author


Let us look at some of the stats related to Data Analytics which will make you come across why you should pursue one of the many Data Analysis courses available online.

Big Time Big Data Statistics-

  • The Big Data Analytics market is expected to reach USD 103 billion by 2023.
  • Nearly 97% of organizations are planning to or are already investing in Big Data and Artificial Intelligence.
  • It is the poor data quality that costs the US economy up to USD 3.1 trillion annually.
  • Nearly 95% of businesses state that they need to handle unstructured data as a problem for their business.
  • Netflix can save USD 1 billion per year on customer retention by utilizing big data analytics.
  • Around the world, Internet users around 2.5 quintillion bytes of data every day. 

The Big Data domain is ever-growing and, therefore, the demand for data analytics professionals across the world. Big data helps in a multitude of ways, but only when it is analyzed properly. Big data helps in avoiding treatable diseases by diagnosing them in the early stages. In the banking sector, Big data helps in identifying malicious activities such as online fraud.

Let us now explore what Data Analytics is and how to make a career in this domain.

What is Data Analytics?

Data Analytics is the science of analyzing raw data (that can be of any format), to conclude that information. There are many processes and techniques of data analytics that are now automated into algorithms and mechanical processes that work over raw data for human utilization.

Data Analytics is an umbrella term that covers many diverse types of data analysis. Any kind of data can be put through data analytics techniques to get meaningful insights that are useful in improving things.

Data Analytics techniques help in revealing trends and metrics that would otherwise have resulted in the loss of huge information. This information is generally utilized to enhance business processes, thereby increasing the overall efficiency of a business.

Understanding Data Analytics Process

An Example

In a manufacturing company, typically the runtime, downtime, and work queue for different machines are recorded and this data is then analyzed such that a better plan can be made for the workloads eventually making machines work closest to their peak capacity.

The Process

Some steps involved in the process of data analytics are:

  1. The first step requires you to identify the data requirements and how the data is grouped. Data may be grouped into different sections as name, age, sex, demographic, gender, income, UID number, etc. Data values can be divided into categories, maybe numerical or alphabetical. 
  1. Collecting the data is the second step of the data analytics process. Data collection can be done from various sources such as cameras, online sources, computers, environmental sources, or even through personnel.


  1. After collecting the data, the third step is to organize it to prepare it for analysis. Data organization can be done on a spreadsheet or any other type of software that can accept statistical data.


  1. The last step is to cleanse the data so that it can be analyzed. This implies that the data is scrubbed and checked to make sure that there are no bugs or replication and that it is complete. This step is crucial because it removes all the errors before going on to the data analyst for analysis.

Types of Data Analytics

The four basic types of data analytics are:

  • Descriptive Analytics

It goes with describing what has happened over a given period. For example, how have the sales grown from last month?


  • Diagnostic Analytics

It focuses or rather diagnoses on the reason why something happened. This kind of analytics involves more diverse data inputs and some hypothesizing. For example, how did the marketing campaign affect sales?


  • Predictive Analytics

It makes predictions about what is going to happen in the near term—for example, the number of models that predict a cold winter this year.


  • Prescriptive Analytics

This prescribes a course of action on the basis of the above steps. For example, if the winter is colder this year, then there is a need for an additional tank for the brewery.

Overview of Data Analytics Sector

There are plenty of jobs in the data analytics sector that pay high salaries with abundant career paths to take. This sector offers various opportunities across different industries and corporate levels. Some examples, according to the US Bureau Of Labor Statistics, are:

  • Business Analyst

Typically, analyses Business-related data.

  • Budget Analyst

Performs analysis and reports a specified budget.

  • Corporate Strategy Analyst

This role focuses on an analysis of company-wide data and advises management on strategic direction. 

  • Web Analytics

This role involves analysis of a dashboard of analytics all over a specific page, topic focus, or a comprehensive website.

  • Business Product Analytics

This role involves analyzing the characteristics and attributes of a product as well as suggesting optimal pricing of a product on the basis of market trends.

  • Social Media Data Analyst

The tech giants and social media depend on data to develop, control, and improve the technology and offerings that social media platforms depend on.

  • Machine Learning Analyst

Machine learning is all about programming and training a machine to make it capable of making cognitive decisions. So, a machine learning analyst may work on various aspects that may include data preparation, data feeds, results analysis, and more.

Other areas include Actuary, Fraud Analytics, Insurance Underwriting Analytics, Sales Analytics, Credit Analytics, Management reporting, and more.


We can observe from this article that the field of data analytics is very diverse and can open the doors of opportunities in almost every sector. You can choose from various roles available for data analytics and make a career accordingly.

To make a career in data analytics, you should go with an online training course. With an online training course, you don’t need to worry about arranging the study material and finding what to study. The industry experts make sure that you are prepared well, and real-life projects serve as icing on the cake.

Enroll yourself now!



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