Insight On Data Analytics

What is Data Analytics?

Data analytics is the science of analyzing raw data in order to make decisions about that information.

So, in simple terms, it means     Data  +  Analytics

Data: is a collection of facts(such as words, numbers, observations)

Analytics: systematic computational analysis of data or statistics.

 

This article is a simple guide for data analytics for beginners, after going through this article you would be having good knowledge about data analytics and the future scope of this field.

Life Cycle of Data Analytics?

DALifeCycle

Types of Data Analytics?

There are majorly four types of data analytics.

So, here we start with the simple one and go further to the more sophisticated types, As it happens the more complex an analysis is , the more value it brings.

  • Descriptive: What is happening?  This type of DA is related to the examination of data or content, usually manually performed, to answer the question “What happened?” (or What is happening?), characterized by traditional business intelligence (BI) and visualizations such as pie charts, bar charts, line graphs, tables, or generated narratives.

 

  • Diagnostic: Why is it happening? This type of DA is a form of advanced analytics that examines data or content to answer the question, “Why did it happen?” It is characterized by techniques such as drill-down, data discovery, data mining, and correlations.

 

  • Predictive: What is likely to happen? PA is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal here is to go beyond knowing what has happened to provide the best assessment of what will happen in the future.

 

  • Prescriptive: What do I need to do? This type of DA mainly focuses on finding the best course of action in a scenario, given the available data. It’s related to both types of DA that are descriptive analytics and predictive analytics but emphasizes actionable insights instead of data monitoring.
Types Of DA
Types Of DA

Why Data Analytics can be the best option for you?

Below are the topmost reasons, why DA is the best option for you:

  1. Soaring demand for analytics professionals
  1. Huge job opportunities & meeting the skill gap
  1. Salary aspects
  1. Big Data Analytics is the top priority in a lot of Organizations
  1. Adoption of big data analytics is growing
  1. Analytics: A key factor in decision making
  1. The rise of unstructured and semistructured data analytics
  1. Big data analytics is used everywhere
  1. A lot of choices in Job titles and type of analytics

 

Also, a lot of e-commerce companies and digital marketers are using DA tools to capture data and are doing analysis on these data points to grow their business, which is helping them achieve more revenues.

DA Key benefits and usage across industries

 

TrendsMarket

 

Top 10 Data Analytics Tools/Softwares You Must Aware

Word ‘Data’ has been in existence for ages now and data plays a crucial role in taking decisions.

Let’s talk about some big figures about data by various sources before exploring data analytics tools that you must aware of.

  • Well, 1.7MB of data is created every second by every person during 2020. (Source: Domo)
  • In the previous two years alone, an astonishing 90% of the world’s data has been created.
  • 2.5 quintillion bytes of data are produced by humans every day, that is huge. (Source: Social Media Today)
  • 463 exabytes of data will be generated each day by humans as of the 2025 year. (Source: Raconteur)
  • 95 million photos and videos are shared every day on Instagram, which shows your much data we produce and consume every single day.
  • By the end of 2020, 44 zettabytes will make up the entire digital universe, which is huge.
  • Every day, 306.4 billion emails are sent, and 5 million Tweets are made, So it means we are dependent on data. (Source: Internet Live Stats)

You must be thinking about how we can deal with so much huge data?:) Well, there are several different roles in the industry today that deal with data to gather insights, and that is known as “Data Analyst”

Data Analysts need many tools to gather insights from data before start working on it.

Now let’s talk about the top 10 Data Analytics Tools:

  • R and Python are the top computer programming languages used in the Data Analytics field. Both R and Python are free and you can easily download both of them from their respective official websites.R is an open-source tool used for Statistics and Analytics whereas Python is a high-level programming language, an interpreted language that has an easy syntax and dynamic semantics.
  • Microsoft Excel: Microsoft Excel is a platform that will help you get better insights into your data and it is one of the most popular tools for Data Analytics.
  • Tableau: Tableau is a market-leading BI(Business Intelligence) tool used to analyze and visualize data in an easy format. Tableau allows you to work on live data-set and spend more time on Data Analysis rather than Data Wrangling.
  • RapidMiner: RapidMiner is the next tool on our list.RapidMiner is a platform for data processing, building Machine Learning models, and deployment.
  • KNIME: Konstanz Information Miner or most commonly known as KNIME is a free and open-source data analytics, reporting, and integration platform built for analytics on a GUI based workflow.
  • Power BI: Microsoft product used for business analytics. Power BI provides interactive visualizations with self-service business intelligence capabilities, where end users can create dashboards and reports by themselves, without having to depend on anyone else.
  • Apache Spark: One of the most successful projects in the ASF and is a cluster computing framework that is open-source and is used for real-time processing. Active Apache project at the moment, it comes with a fantastic open-source community and an interface for programming.
  • QlikView: This tool accelerates business value through data by providing features such as Data Integration, Data Literacy, and Data Analytics and QlikView is a Self-Service Business Intelligence, Data Visualization, and Data Analytics tool.
  • Talend: It is one of the most powerful data integration ETL(Extract, Transform, and Load) tools available in the market and is developed in the Eclipse graphical development environment. Using this tool you easily manage all the steps involved in the ETL process and aims to deliver compliant, accessible, and clean data for everyone.
  • Splunk: This tool is used to search, analyze, and visualize the machine-generated data gathered from different applications, websites, etc. It has evolved products in various fields such as IT, Security, DevOps, Analytics.

You can check this video as well

I hope you like my article and get insight on data analytics from a bird’s view perspective, thanks for your time and patience.

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About the author

Mohit Sehgal a technophile & entrepreneur, blogger. Having 10+ years of hands-on experience in the Software industry.

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