Big Data Skills in 2022

8 Big Data Skills in 2022 You’ll Need to Succeed

With its ever-growing prominence, Big Data is paving the way for large organisations in almost every industry to make informed business decisions. Judicious data analysis provides managers with insights on developing new products, analysing customer behaviour and buying patterns based on their demographics.

Thus, it will not be wrong to say that acquiring Big Data skills can help you land your dream job, making data proficiency one of the most in-demand skills today. In this article, we will tell you the top Big Data skills you need to get the best placements. The information provided here applies to students looking for career prospects, technologists and business professionals looking to brush up their skills, or looking for a career change.

Why is Big Data one of the Best Jobs in the Market?

Big Data is the most trending term in the current job market. Websites have been generating data and information all the time at an unprecedented rate. Thus, it is essential to extract all relevant information from these data sets. Organisations collect and store data to gain a competitive edge in building strategies, cutting costs, and making better business decisions.

Thus, Big Data professionals such as data scientists and analysts are crucial as they analyse, manage, and store the data effectively. The Big Data market will be worth $ 46 billion, and this is a clear indication that Big Data makes for a lucrative career choice. Let us now discuss the top Big Data skills demanded in the market today that can land you the perfect job you desire.

Top Big Data Skills

Undoubtedly, Big Data technology is bringing more innovations every day. To cope with these innovations, some unique skill sets are required. To become a successful Big Data professional, here are the topmost skills that you must have:

1) Programming Languages

Coding will always remain one of the prerequisites for landing a suitable job in Big Data. Thus, knowledge of programming languages such as JavaScript, SAS, Python, SQL/NoSQL, MapReduce, and Apache Spark is sought by employers today. Let us see how these languages help in Big Data projects:

i. Apache Hadoop: Apache Hadoop has seen tremendous growth over the last few years. Many companies use Hadoop clusters and components such as HBase, HDFS, Hive, MapReduce, Pig, in large volumes.

ii. SQL: SQL works as a base data language. Knowing SQL gives programmers a big advantage, and it is an integral part of Hadoop Scala warehousing.

iii. NoSQL: The NoSQL database includes Couchbase and MongoDB, which serve as a replacement for traditional SQL databases such as DB2, Oracle, etc.

2) Analytics: Predictive and Quantitive

Predictive analytics in Big Data involves data forecasting and modelling different scenarios. It entails anticipating and modelling multiple possibilities and consequences, and is quickly gaining traction as a crucial component of perfecting the art and technology of Big Data. This technology uses mathematical tools to look into the patterns in the data to realise future events, customer behaviour and ROIs.

Apart from that, quantitative analytics is all about numbers. A strong background in mathematics and statistics will help you master tools such as SPSS and R better and understand the algorithms, probability and statistics used in Big Data projects.

3) Data Mining

Businesses can acquire detailed insights about their consumers by mining and utilising algorithms to detect patterns in massive quantities of collected data. It allows them to create more targeted and individualised marketing tactics, increase sales and save costs. There is a high demand for knowledge of data mining methods and equipment for landing Big Data jobs. Proficiency in data mining technologies such as RapidMiner, Apache Mahout, and Knime is one of the most in-demand skills in today’s market.

4) Data Visualisation

You must use data to tell a story that the target audience understands. If the data insights aren’t found efficiently, the chances are that the data visualisation affects your data’s impact. Data analysts must use high-quality graphs for presenting the results concisely.

It is essential to know the Big Data skills you need to run data analysis and work on it. Companies are in constant search of such skilled professionals with this in-demand skill. Improving your Big Data skills attracts more opportunities and more lucrative packages.

5) Knowledge of Technologies

Individuals in the Big Data field should be conversant with efficient technologies and techniques commonly used in this field. Thorough knowledge of the Big Data tools aid in the analysis and conclusion of the study. It is usually preferable to use as many Big Data tools and technologies as possible, such as Hadoop, Linux, MatLab, R, SAS, Excel, SPSS, etc. Professionals with dynamic skills and understanding of coding and analytics are in greater demand today.

6) Cloud Computing

Dealing with Big Data necessitates using cloud computing products and services for data professionals to access the resources for managing and processing data and analysing the data stored in the cloud.

Big Data and cloud computing work together, and data professionals can use the platforms such as AWS, Azure, and Google Cloud to access databases, frameworks, and tools. Cloud Computing is applied in Big Data processes such as data acquisition, parsing, munging and wrangling, validating predictive models, and data variable tuning.

7) DevOps

DevOps combines software development and IT operations to reduce the development life cycle and provide high software quality. DevOps helps in extracting data with the help of Apache Airflow, Apache Hadoop, Apache Kafka, and Apache Spark languages. DevOps configure and manage data clusters and information infrastructure by continuously integrating, deploying, and monitoring data. It also creates scripts for automating the configuration of the data environments.

8) Business Knowledge

For focused data analysis, validating, sorting and evaluating data, Big Data professionals must have adequate knowledge of the domains they are working on. Big Data Analysts are in demand because professionals with a thorough understanding of technicalities, statistics, and business are rare.


As Big Data is proving to be necessary for almost every industry, having the Big Data skills mentioned above gives professionals a further edge over the competition. Professionals may advance their Big Data careers by learning and acquiring expertise in these skills, thus creating a bright future for themselves.

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