5 Big Data Tools You Should Know to Make Your Career Count

by | Jan 18, 2018 | Big Data

7 Min Read. |

Technology is never the same. Ever since the industrial revolution, we have always been evolving in the way we approach work and the means of simplifying it. Today, technology is an integral part of whatever we do and is at the fulcrum of businesses and personal life.

Due to this, we have given rise to two consequences – a simplified work environment and processes and cutthroat competition. As technology continued to evolve over time, it has carried with it the fact that we consistently have to be updated at whatever we do to not just pave the way for convenience at work but evolve in our careers too.

The job market today is cluttered with skills of diverse types. People from different walks of life and academic backgrounds are looking forward to making a mark in whatever they do. To survive this wave of talent and move up the corporate ladder, you need to possess skills that are not just new but the most in demand.

When spreadsheets were in a decade ago, people upskilled and grew in their careers. Today, we are knocking on the doors of a similar situation, wherein we need to upskill to one of the hottest job profiles of the 21st centuryBigData.

Big Data – the Most in-demand Skill Today

Big data is one of the hottest industries of the decade, and companies around the world are waking up to the importance of this technology. Tons of companies are reinvesting on Big Data for optimized customer service, detection of touchpoints for better workflow management and more.

From automation and Machine Learning to Artificial Intelligence, Big Data is the basis of almost every futuristic technology, and if you are looking at a lucrative career path, you need to upskill to Big Data.

To help you get started, we have compiled a list of big data tools you should master this year to make your career count and put it on a steady graph. For beginners, you need to have a basic exposure and knowledge of the essential big data analytics tools.

Once you are familiar with common big data tools, you can build on your basics by specializing on any tool that you have a flair for or the tool that you think you can use to implement your innovations, strategies, and ideas. So if you are looking to make a career out of Big Data, here is the big data tools list you need to be familiar with.

Big Data Analytics Tools You Should Master

  1. Apache Hadoop



One of the most popular and the immensely distributed big data analytics tool, Apache Hadoop is like the foundation for your career path in this industry.

With companies making every decision today considering data collected from various touchpoints, Apache Hadoop shines in the fact that it is easy to use, smooth, and is designed to seamlessly handle tons of data, which can be either structured or unstructured.

Once you are familiar with Hadoop, you can go on to learn the other offerings from the developer such as Apache Pig, Apache Cassandra, Apache Spark and more.

Also, the feature that makes Apache Hadoop stand out from the rest is that it does not rely on hardware to detect and troubleshoot errors and offer high availability, its library is designed to handle all these at the application layer to provide you with error-free computational services.

Apache Hadoop includes Hadoop MapReduce, Hadoop Common, Hadoop Distributed File System and Hadoop Yarn – each of which is a distinct offering from Apache that handles common utilities, cluster resource management services, job scheduling frameworks, parallel processing spaces for massive data sets and more.

Key Takeaways:

Hadoop is one of the most widely used big data tools and is a must-learn for any big data aspirant. It is easy to learn and use, versatile and efficient.

  1. Apache Storm

    Apache Storm


Any big data tools list is incomplete without Apache Storm. Thanks to its scalability and speed, companies are increasingly turning to Apache Storm for processes involving real time results. This is also one of the most commonly used big data tools for streaming data, where accuracy and super fast results are the need of the hour.

You can use integrate Storm with Hadoop or use it as a standalone tool or even streamline it with any other programming language you are comfortable with, making Storm one of the most versatile big data tools out there.

Key Takeaways:

Apache Storm is scalable, super fast and is integrable with any programming language. It is a developer’s delight to work with Apache Storm.

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  1. MongoDB



Actually derived from the word humongous, MongoDB is built to tackle humongous amounts of data with ease and precision. It was initially designed to support massive databases, and today it is one of the most commonly used big data tools deployed by companies globally.

Technically, MongoDB features full index support, document-oriented storage, high availability and replication and is programmed in C++. Being a no-SQL database, MongoDB arrives as the perfect tool to store and analyze big data and even develop applications.

Key Takeaways:

Designed to manage and work on humongous data sets and offer precision and seamless speeds simultaneously. Yet another globally popular big data analytics tool.

  1. Elasticsearch



As the name suggests, Elasticsearch is flexible, versatile and seamless. It is one big data tool that allows you to talk to your data and ask it questions.

You can search across diverse data types – from structured and unstructured to metric or geo, and get insights on your requirements and see the bigger picture for your project or company.

It is an opensource big data tool that allows you to extract data from any source and use it for analytics and visualization. It supports all formats of data and is built for ease of management, horizontal scalability, and reliability. Being extremely user-friendly, Elasticsearch allows for real-time data processing and visualization in one of the most précised manner.

Key Takeaways:

Search-engine based, Elasticsearch supports every other data format and gives you a myriad of ways to communicate with your data and extract information. It is also perfect for analytics and data visualization.

 5. R

R - Analytic Tool


One of the fascinating aspects of R is that it is both a programming language and software. While the software side of R takes care of data extraction and data mining, the programming language aspect of the popular big data tool takes care of sophisticated analytics of the extracted data.

Again, it is an opensource tool and is written in R programming language. It is popular amongst developers and data miners across the globe who are into statistical data analysis.

Apart from serving as a data mining tool, R also offers features like nonlinear and linear modeling, time series analysis, clustering, graphical and statistical techniques, classical statistical tests and more. R is one of the most complementary big data tools out there and is user-friendly.

Key Takeaways:

It is popular among data miners for offering features like clustering, statistical analytics techniques, time series analysis and more. Again, a user-friendly tool that beginners will find easy to adapt and learn.

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How Tools Will Influence Your Career Path

If you are aware of the current recruitment pattern in the industry, you’d know that most companies lookout for a competitive edge in employees. Apart from experience and relevance, they also look for employees who are proactive and always intend to stay updated in their respective sectors.

With Big Data seeping into every other industry and with IoT or the Internet of Things becoming more real and advanced, companies both big and small are on the lookout for experts who can work with data, talk to it and get insights that could actually benefit consumers and businesses.

Mastering the tools will give you the right exposure to the industry and help you understand the requirements of companies. Besides, the tools will also fetch you lucrative paychecks and a perfect work-life balance that perhaps every IT professional looks forward to.

Being in the IT industry, you must also be aware of the retrenchments that plague companies. Employees with redundant skillsets who don’t intend to upskill to newer technologies are fired first. To save your career from such downturn, you need to know the latest tools and possess mastery over them.

Also, it’s not just the exposure to these tools that will create an impact on your career. To stand out from the crowd, you need to have the right exposure. You need to be aware of how the industry functions and your Big Data course should bridge the gap between what you learn and the industry requirements.

Most graduates tremble because of this gap and to overcome this; you need to learn from the pros – from industry experts and veterans. To get started with Big Data, check out our courses and gear up to put your career on the right path this 2018.

Good luck!

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