Data Analytics: An Comprehensive 7 Step Guide

Ajay Ohri


Do you know what is data analytics? You might have heard the term for the most promising business opportunities today. Data analytics techniques are mostly used by companies processing larger data and turning them into useful resources. This article will discuss various aspects of data analytics, including the definition, application, use, various data analytics tools used in the process along with certain examples to explain the same.

In this article let us look at:

  1. What Is Data Analytics?
  2. Why Data Analytics?
  3. Data Analytics Tools
  4. Data Analytics Lifecycle Process
  5. Data Analytics Software
  6. Types Of Data Analytics
  7. Data Analytics Examples

1. What Is Data Analytics?

In simple terms, the data analytics definition uses and analyzes raw data of the complex company, making it easier to be read by everyone. With the help of various tools, one will extract the meaning from the raw data or data that is difficult to understand. This is done with the help of data scientists and analysts and various data analytics tools. These data analytics tools are integrated with machine learning and artificial intelligence, which helps with analyzing data. Data analytics techniques can be used by a business to help analyze their business, including their market value, customer types, plan to be executed, area to be focuses, total sales, profit, etc.

2. Why Data Analytics?

Talking about the importance of data analytics can be used by the business for better research and market study. Given below are a few important use of data analytics that one should know about.

  • Data Analytics will help one with decision making. Based on the past reports of the market and the company’s performance, one will judge how the company will perform in the long term. This will help them make various important decisions related to marketing strategy, correct audience, or development of the product.
  • It also helps with the effective marketing of the product the brand has developed—data analytics help understand the audience better. Once you know your audience, it gets easier for you to know the strategy you require to work on. This will also help you know what your audience demands, so you will be able to work on their requirements. Data analytics technologies help you identify your audience.
  • This also helps provide better customer service to your audience. Data stored by the companies can provide insights into the audience’s interest and what they are there for. Therefore, data analytics tools and techniques can help the brand by providing better customer service.
  • Helps you with the efficient operations of your team. This is possible because your company already knows what your audience already wants, so this will help them make products or services as per the audience’s requirements.

These are some of the benefits of data analytics that a company will notice.  

3. Data Analytics Tools

There is various type of data analytics tools that can be used by a company to help with converting raw data. These tools use machine learning and artificial intelligence to analyze and convert the company’s raw data. These data analytics tools are used at a high level to help make the process faster.

4. Data Analytics Lifecycle Process

Talking about the data analytics lifecycle process, the whole process of data analytics is divided into five steps. Given below is the process of data analytics basics.

  1. Know your questions, such as the data analysis for, what it will help with, etc. If you question yourself such questions before you start analyzing data, this will help you know what your end goal is after the data analytics. 
  2. Once you are done questioning yourself, you will have to set your measurement priorities. You should know what to measure. This can be anything such as the total products sold, total revenue, profit or loss faced in the particular month or throughout the year, information about your staff, current market value, what your audience wants, and users’ preferences. You will then have to think about how you will measure the value. This will include certain values, such as measuring in a time frame, different currencies or units, and different factors that affect the performance in the short term or the long term. 
  3. Then you will also have to figure out a way to collect the data as well. Data analytics is not only about recording new data; it also includes using old data. So the company needs to store the old data as well as the old data. There are certain things one should know to help them collect their data. First, think about what data to collect from your old databases or set of data. Then determine the storing system and the naming system for the file, so data the same data is not copied twice. You will also have to organize the data that is collected in your database. 
  4. Now you will have to analyze your result. This is an important part of data analytics that you will have to analyze the converted data. 
  5. Once you have analyzed your data, you will then have to interpret the results. Know what your data suggests you based on the research. Know what actions are required and work accordingly. 

5. Data Analytics Software

Professionals use various data analytics software to help convert the raw data and know the outcome. Various data analytics software are-

  • Tableau
  • Microsoft Excel
  • SAS
  • Apache Spark
  • RapidMiner
  • Splunk

6. Types Of Data Analytics

Companies can use various types of data analytics. Some data analytics techniques are-

  • Descriptive Analytics- This type of analytics helps you analyze what has happened over some time.
  • Diagnostic Analytics- This type of analytics focuses on the reason for something that has occurred. For instance, this focuses on why the sales were affected, why profit was less, etc.
  • Predictive Analytics- This analytics helps you with predicting the upcoming future. For instance, this type of analytics can be used to know what the sales will be for a particular product.
  • Prescriptive Analytics- This type of data analytics helps suggests a course of action. Based on the past circumstances, one can know what to do next. 

7. Data Analytics Examples

Various data analytics examples can help understand the actual data analytics meaning.

  • Netflix, one of the biggest OTT platforms, uses data analytics to target their audience with their ads. Their audience knows what their audience prefers watching; thus, it helps push them content that their audience prefers.
  • Amazon shows users suggested products based on the search result of other users buying the same product.


Data analytics techniques over the long term help one analyze what their actions can lead them to. Also, this can be helpful for companies looking for higher sales and growth of the company and earn their revenue. 

If you are interested in making it big in the world of data and evolve as a Future Leader, you may consider our Integrated Program in Business Analytics, a 10-month online program, in collaboration with IIM Indore!

Also, Read

Scope and Future of Data Analytics in 2021

Top 8 Applications Of Data Analytics to look out for in 2021

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