Big Data is getting Bigger!

Posted on: 10-Jul-2019 | Created By: 361 Career-Care Team

“We are so obsessed with Big Data; we forget how to interpret it!” – Danah Boyd

She said it right, but have you also heard that Data is absolutely useless without the right skill to analyze it? Well, it is true! Today, with every tap on your phone and click of a mouse, you are generating data. “What? That’s simply exaggerated!” In fact no, even when you just finish reading this blog, the world would have created a few terabytes or even petabytes of data followed by data. Really surprising isn’t it? So, let me explain to you everything you need to know about #BIGDATA- right from What is Big Data, How to Learn Big Data from Scratch to How to grab the Boiling Big Data Career as a Data Scientist!

What is the “Big Data” concept? “Why” and “Where” is it used?

Big data in different sectors

Let me keep it very simple. When you scroll down the internet you can find a million definitions on “What is Big Data?” as there are these Businesses, Government, Non-profit organizations and whatnot, waiting to seize the benefit of Big Data! I would like to explain Big Data as a ‘Complex Data Set derived from various Data Sources’.  These data can be highly voluminous that the conventional Data Processing Software simply cannot manage them. But these massive data are absolutely precious that they can be used to tackle any business problem you wouldn’t have been able to resolve before!

Big Data application drives the industry and it is no news. Many industry influencers and other prominent stakeholders undeniably go with the opinion that Big Data is the new Big Thing! It’s an absolute game-changer. The importance of Big Data application is relevant when it comes to understanding one’s customers, their behavioral patterns and moreover their preferences. Today, every business is keen to expand its traditional data to get a more accurate picture of their prospects using various social media data, text analysis, and even the browser logs.

Consequently, with the highly accelerated demand for the data scientists, this discipline provides an enticing career path for aspiring candidates and even for the existing professionals who would like to leverage their existing skills.  Here comes the question “What are the necessary skills needed to be a Data Scientist?”

What are the prerequisites to learn Big Data?

Data Science Job Analysis

  1. First of all, I would emphasize that the basic quality that one must possess is Quantitative Skills. This primarily includes some statistics and mathematics knowledge. The idea is simply that you being an industry professional must always be super curious about how to solve various business problems!
  2. Machine Learning and Excellent Communication skills are a must. This makes you a storyteller, in a way that will help you share valuable business insights so that others find it easy to comprehend and confront real-world problems with much clarity.
  3. Basic technical computer skills are a must because without which, you cannot effectually function. This includes a number of necessary skills in R & Python (in other languages too), Hadoop, Spark, Data Visualization tools such as Tableau.

The recent report by iCIMS Hiring Insights reveals that 94% of recruiting professionals believe an employee with stronger soft skills has a better chance of being promoted to a leadership position than an employee with more years of experience but weaker soft skills.

Apart from the above-mentioned skills, certain soft skills are also unavoidable to secure a Big Data Job:

  1. Research: Data Scientists should have the soft skill of being creative; thinking outside the box and inquisitiveness to research. This allows them to often discover patterns and solutions that others might miss.
  2. Writing: Writing and creating a story with data is crucial. It helps to engage your audience and draws their attention to the information and story within the data. Your audience can be anybody from people who you work with, work for, or even your prospects, but by creating a story about the data or from the data, you can engage with them. 
  3. Problem-solving: While it is important for a data scientist to keep themselves abreast on the latest tools and developments, it is mandatory for them to work on solving problems. You must be able to analyze and learn the situation, the processes, the data, and the circumstances related to it. It is wise to characterize everything around the problem in order to understand exactly what an ideal solution is.
  4. Teamwork: Being selfless, constant iteration and sharing knowledge with others is a significant part of a Data Scientist. The methods will include back-and-forth feedbacks and constant communication.
  5. Creativity: Creativity in data science can be anything from innovative features for modeling, development of new tools, different methods to visualize data, or even the types of data that is pulled for analysis. It is fascinating to find that everyone does things differently depending upon how big or small the issue is.

The present and future of the IT world and tech market is Big Data Technologies. No industry can expand without making use of Big Data tools, Big Data applications, and technologies. The professionals can gain a lot in their career if they learn Big Data technologies. Not to mention, there is a rise in the demand for highly talented professionals with the requirement of Big Data implementation and data analysis tools for each and every business. Hence Big data is a bigger deal and is the part of changing the world that we live in today.

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