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4 Popular Big Data Jobs – Roles & Responsibilities

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29th Jul, 2019
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4 Popular Big Data Jobs – Roles & Responsibilities

Big data has been declared the oil of today; and who does not want to become a part of the forever growing venture? Everyone claims to be up and about the entire subject, but no one really knows how to indulge in it properly. But since we are feeling benevolent today, we shall give you some leads on how you could have the “world’s hottest job”. 

Big data is…well, big, and it depends on how you wish to mold, alter, cut, analyse it to benefit your business or organisation, but usually, it takes more than just a couple of hands to figure out how to use that data in your favour. That’s celebratory news for all that wish to seek jobs in this field.

Let’s start from the very basic question— what kind of scope does this field have? 

Big Data refers to this extremely large and complex data which cannot even be fully analysed by the various data processing systems that exist- they have been deemed insufficient. Do you realise how much data there has to be to deem the current systems insufficient? Apparently, by next year, every person in the world will have over 5200GB of data on every person in the world (current population lies on the seven billion paths). 

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Of course, what some might consider Big Data, might be considered traditional data by others, so it is an approximation, it could be more, who knows?

It is still a lot of data to analyse, engineer etc. If you are at par with the ongoings and developments in the IT field and have the passion and zeal to work towards making all that data beneficial to your company. The main factor driving the adoption of data-intensive computing is a rapid analysis of exponential amounts of data, all at the point of its creation and scale.

It is because all these traditional methods are now incapable of keeping up with the amount and speed that all these data management systems have been scraped out. The system should be able to generate leads and beneficial insights in deem time for it to make any quality impact. 

According to Forbes, over 53% of companies are into Big Data, and around 95% of those businesses need systems to mair unorganised data. Industries dealing with electronics, retail, finance, insurance, the public sector- all require ways to do it. 

In short, yes, if you are passionate about analysing data, and can produce valuable data to back up the suggested changes in an organisation then you will ace in the Big Data field, with a bright future tucked away under your arm.

What are the different career opportunities that are available in this field? 

It can be overwhelming the number of job profiles that require you to be an absolute maestro of analysing, and the expectations and responsibilities that are attached to the job profile are nothing short of impossible to keep up with, but here is a brief guide on how to choose the right job profile for you. 

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Big Data jobs are plenty, but not every profile is suitable for you.

1. Data Analyst

Job Profile: A Data Analyst uses all the big guns (tools) to process the data. They primarily have to deal with various data types such as unstructured, semi-structured, and structured data, and in the process of analysing the various kinds of data, they are acquainted with a number of tools like Pig and Hive, and frameworks like Spark and Hadoop. 

The main aim of a Data Analyst is to detect the hidden potentials that the data has, to help companies increase their revenue, and alter their strategies. Exceptional problem-solving skills, and out of the world arithmetic skills are needed to become a data analyst because they need to study past trends, generate patterns, and produce reports for the same. 

Role & Responsibility:

  • A Data Analyst must Identify, Analyze, and Interpret trends or patterns in complex data sets.
  • He / She must have the ability to explore and understand large database designs and table relations within the database.
  • He / She must analyze a large volume of data and define a clear strategy in assurance analytical work.
  • Data Analyst must support the extraction of data from multiple sources by understanding data structure requirement.
2. Software Developer

Job Profile: The programmer is the vital pawn who writes all the code that performs repeated and conditional actions on data sets. The most common language, which programmers generally deal with are Shell Scripting, Java, and Python. All the code that programmers produce is stored in a database or in flat files — which means that one needs to have a basic understanding of the file and database system. 

To be able to generate outstanding code, it is integral to have a firm grasp on the various programming languages, possess mathematical and statistical skills, and have an analytical thought process.

Role & Responsibility:

  • A Python developer must create & maintain Advanced Dashboard on Real-Time Monitoring Platform.
  • Programmer must develop interfaces with third-party solutions for data onboarding.
  • He / She must ensure high reliability and high-availability of the features delivered.
  • Collaborate with cross-functional teams to define, design, and ship new features.
  • Work on bug fixing and improving application performance.
3. Admin

Job Profile: It the Admin who takes care of the entire infrastructure that manages all the tools related to data and big data ecosystem. The role involves taking care of all the nodes which lie in their network configurations. Admins have to make sure that there is high availability of time to support all the significant data operations. The installation of a variety of tools, managing hardware clusters – all is taken care of by the Admin.

Skills that an admin needs to have included a good understanding of the file system, the operating system, computer hardware, and networking.

Role & Responsibility:

  • Experience with Configuration Management Tools.
  • Managing an application cluster in Big Data infrastructure.
  • Responsible to proactively identify the risks in the application and manage mitigation actions.

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4. Solution Architect

Job Profile: A Solution Architect is one who has to analyse real-world problems and accordingly develop a strategy to tackle them, solve problems, all by using their expertise and power of the big data framework. All the decisions regarding what tool and programming language are to be used to lie with the Solution Architect.

In-depth knowledge of the various big data tools, knowledge of frameworks, licensing costs and their alternative open source tools are all imperative characteristics that a Solution Architect should have. 

Role & Responsibility:

  • Big Data Solutions Architect well versed in dessigning big data architectures.
  • Proficient in Real Time & Batch-based Big Data Processing, Business Intelligence, and Machine Learning
  • Performs necessary storage infrastructure maintenance and necessary data migration.
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Big Data is something that will only grow over time. Getting on board with this phenomenon will assure a great and stable future!

If you are interested to know more about Big Data, check out our Advanced Certificate Programme in Big Data from IIIT Bangalore.

Learn Software Development Courses online from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs or Masters Programs to fast-track your career.

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Frequently Asked Questions (FAQs)

1Is a data scientist a real scientist?

A data scientist is one who deals with Big Data. Their role is primarily a combination of statistics, mathematics, and computer science. Data scientists analyse enormous voluminous sets of data that can be both unstructured and structured. Then, they process and model that data to draw valuable insights based on which companies can develop actionable plans to boost their profits. Data scientists are essentially analytical experts skilled in both social sciences and technology to detect and forecast market trends from available data sources. They must also be industry experts and have a deep contextual understanding to propose strategic solutions to various business challenges.

2Can you build a data science career, being a student of Humanities?

The switch from academia to data science is pretty much common among students who hold a degree in science. This is relatively uncommon among students who hail from non-science educational backgrounds. However, non-science students can also transition to a career in data science. A degree in Humanities can be very useful in the data science industry, as far as analytical thinking and researching capabilities are concerned. But a background in mathematics and computer programming helps to understand the fundamentals of data science more efficiently and move on to its functional aspects with more advanced concepts.

3What kind of data is Big Data?

Big Data consists of enormous and highly complex sets of information or data derived from a wide variety of sources and platforms. It keeps increasing in capacity and arrives at considerable speed in real-time. These sets of data are so voluminous that conventional software applications meant for processing data are rendered insufficient to handle them. The most significant value of Big Data lies in the valuable insights it contains, which can address complex business problems and help generate more profits. In today’s times, Big Data is of capital significance and can immensely benefit organizations, thereby enabling them to achieve high efficiency in terms of service and product delivery.

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