7/25/2019

Big Data Vs Data Science Vs Data Analytics | Comparison

We are going to discuss the Comparison Between Big Data Vs Data Science Vs Data Analytics. Similar as these terms may seem to you phonetically, there is a lot of difference between data science, big data and data analytics.

If you do not know the differences you will not be able to use any of these properly. You will not excel if you want to take up analytics as your career or use these analytics for your business purpose.

Comparison Between Big Data Vs Data Science Vs Data Analytics- Table of Content


  • Big Data Definition
  • Data Science Definition
  • Data Analytics Definition
  • Big Data Vs Data Science Vs Data Analytics Infographic
  • Applications of each field
  • Big Data Financial Services
  • Big Data Uses
  • Big Data in Tele-Communications
  • Big Data in Retail Businesses
  • Data Science Uses
  • Data Analysis Uses
  • Big Data Vs Data Science Vs Data Analytics | Comparison Table

Big Data Definition


Big Data, on the other hand, refers to enormous volumes of data that you cannot analyze or process effectively with the help of the traditional applications that are available on the market.

Big Data starts its work with the raw data that is not aggregated both unstructured and structured. The Big Data analysis helps the modern business to make better decisions and formulate more strategic business moves on a day to day basis.

Data Science Definition


In simple terms ‘Data Science’ is the umbrella of different techniques that deals with a large volume of structured and unstructured data. This is an aspect that involves everything of data utilization including data preparation cleansing, and analysis.

This is actually a science that is a combination of stats, math, programming, capturing data, and problem-solving in a more ingenious way. Now we get the basic idea about the Big Data Vs Data Science

This will give you the ability to look into things differently and align the data in the best possible way to extract valuable insights and information from them.

Data Analytics Definition


Data Analytics is another segment of the raw data examination process. This is again a science that primarily involves drawing conclusions about the information received from the collection of data.

Data Analytics typically involves the application of a specific mechanical or algorithmic process that is extremely useful to derive better insights. This system will help you to find meaningful correlations between a large number of data sets.

Data analytics is used in a large number of industries that allows them to make better business decisions as well as validate or disprove any existing models or theories. This is the main difference between Big Data Vs Data Analytics.

However, the main focus of Data Analytics lies in the inference which means deriving conclusions from the data insights that are exclusively based on what the examiner already knows.

The primary objective of all three is however on data analysis and examination that helps businesses and even the branding firm to take more strategic and productive steps to ensure more profit for their business.

Infographic Big Data Vs Data Science Vs Data Analytics Comparison

Image Source: Click Here

Applications of Each Field


When it comes to the applications of each field, it is also different and you must also know it to make the best use of Big Data or the others as per your need or choice.

Read Also: JavaScript Frameworks for Frontend Development

The application of Big Data is diverse but it is mostly used for financial services, telecommunications and retail business, which involves a large amount of data that traditional systems cannot manage or analyze.

Big Data Financial Services


When you consider the Big Data application for financial services it includes several different organizations such as:

  • Credit card companies
  • Insurance firms
  • Retail banks
  • Venture funds 
  • Private wealth management advisories and 
  • Institutional investment banks.

This analytics tool helps them to solve the most common problem among them all: massive amounts of data that is multi-structured and living in numerous disparate systems.

Big Data Uses


In these financial institutions, Big Data is used in a number of ways such as:

  • For customer analytics
  • For operational analytics
  • For compliance analytics and 
  • For fraud analytics.
  • Big Data in Tele-Communications

When it comes to telecommunications Big Data helps in diverse fields but the top priorities are:

  • Gaining new subscribers
  • Retaining the existing customers and 
  • Expanding within the present subscriber bases.

The telecommunication service providers can find easy and effective solutions to these specific challenges with Big data that enables them to combine and analyze the huge number of customer-generated data along with the machine-generated data on a daily basis.

Big Data in Retail Businesses


The retail businesses Big Data helps all types and forms of retailers including the off-line brick and mortar stores and the online eCommerce stores.

Big Data helps them to analyze all disparate data sources that these stores have to deal with every day that includes:

  • Weblogs
  • Social media accounts
  • Customer transaction data
  • Loyalty program data
  • Offers and promotions
  • Sales and revenue data
  • Store-branded credit card data and much more.

It helps these stores to understand their customers more so that they can serve them in a better way.

Data Science Uses


For the applications of data science, it is also used for different purposes that include:

  • Internet search wherein the search engines use their data science algorithms to provide the best results for all search queries within a fraction of a second.
  • Digital advertisements that involve the entire digital marketing spectrum and includes everything from digital billboards to display banners and helps the businesses to get higher click-through rates as compared to any other forms of traditional advertisements.
  • Recommender systems that need to find the most relevant products from billions of similar products that are available on the market based on the user experience.

Data science is also used by a lot of companies to promote their business, products and suggestions according to the demands of the users.

As well as the relevance of the information and all recommendations are typically based on the previous search results and history of the users.

Data Analysis Uses


The applications of data analysis, it is extensively found in business segments such as:

  • Healthcare that experiences cost pressures but have to treat as many patients as possible most efficiently keeping in mind specific things such as quality of care, instruments and machine data along with the optimized patient flow.
  • Travel that needs mobile, weblog and the social media data analysis to provide travel insights and better user experience according to the desires and preferences of the customers, correlate current sales and increase browse to buy conversions, customized packages, offers, personalized travel commendations and analysis of social media data and 
  • Gaming that needs to analyze data to optimize dislikes, likes and relationships with the users and spend within the limits of the game.

Comparison Table of Big Data Vs Data Science Vs Data Analytics

Moreover, firms also use data analytics for energy management, optimization, and distribution.

Now that you know the difference, choose which data analytics you would like to use for your business.

See Also: 

No comments:

Post a Comment