7 Top Big Data Skills In 2024: Highly Demand

01 Feb, 2024 surbhi shringi 1 Comment

• Data Employers Crave
• Data Employers, Data Employers Crave, Skills

7 Top Big Data Skills In 2024: The volume of data is increasing every single day, and so is the market size of Big Data to get the most out of the collected information. Currently, there are over 2.7 Zettabytes of digital data on the internet.

The estimation is that the volume of business data doubles every 1-2 years. Businesses desperately need a skilled workforce with the power to play with data to capitalize on their collected data. Do you want to learn data science in depth and make a career in it, then Intellipaat big data training is for you.

Intellipaat is one of the leading e-learning and professional certification companies for IT professionals who provide training courses on AI, Big data, DevOps, and online Data Science courses.

 

The majority of businesses are not able to get the most out of their database. According to the report, businesses on average lose 20-35% of their operating revenue due to low-quality data. If you can bring your skills to the marketplace to minimize the losses for companies, they will be more than happy to pay you a considerable sum of money.

Also Read: Data science: A new way to explore data

Top 7 Skills to Acquire this Year For Data Analyst

To offer value to the marketplace, you need some serious skills. I bet that most of you already have some skills that I am about to mention. However, some of the skills that I will suggest will be new to you guys. Let’s check out the list of skills that you should aim to acquire this year.

1) SQL

SQL is a must for you if you want to get a job in the field of Big Data. It is a base for every single type of data analysis. The programmers/analysts also need SQL to work efficiently on Hadoop Scala warehouses and NoSQL technology.

2) NoSQL

The NoSQL databases are getting more and more popular due to their extensive ability to meet the big data storage and access requirements. The NoSQL databases include technologies like Couchbase, which is rapidly replacing traditional database technologies like Oracle and DB2.

The professionals with the knowledge of NoSQL along with Hadoop will quickly get them off their feet to contact them.

3) Knowledge of programming languages

There are two popular languages when it comes to Big Data analysis, and they are Python and R Programming Language. The developers prefer Python for performing all sorts of projects. However, the case for R is different. R Programming language is explicitly for dealing with data analysis and modeling.

R was not so popular when Ross and Robert first introduced it. However, it has started gaining attention from developers after the increment in the craze of Big Data due to its unique abilities in dealing with data.

The expertise in both R and Python will make you a gem in the eyes of corporations.

4) Ability to play with data

Your importance will increase if you can bring out key insights from the collected data. Critical abilities like data mining, quantitative analysis, and data visualization are what hirers are looking for in their data analysts and data scientists.

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• Data mining: Various data mining technologies are available on the market. Your ability to play with tools like KNIME, Rapid Miner, and Apache will increase your value.
• Quantitative Analysis and Problem Solving: Big Data is all about dissecting the collected data to get as much critical information as possible. You need to use statistical and mathematical tools to deal with the massive volume of data. The developers use tools like SPSS, SAS, R, and so on to analyze the data. After examining the data, you must also be able to come up with efficient solutions for corporations.
• Data Visualization: After the use of analytical tools, we use tools like Tableau, QlikView, and so on to represent the data. It is not an easy task for the layman to grasp the insights extracted from Big Data technologies. You as a professional must be able to simplify the ideas by making use of visualization tools. Represent the information in the forms of graphs, charts, and so on.

5) Apache Spark and Apache Hadoop

Spark makes an alternative to MapReduce. It simplifies the processing part of Big Data. On the other hand, Apache Hadoop tools like HBase, HDFS, Pig, Hive, and so on enable reliable and scalable computing.

6) Machine Learning

The knowledge of machine learning is like adding a cherry to a cake. It will make you look pretty in the eyes of hirers. The professionals who can make use of machine learning and Big Data for predictive and prescriptive analysis are rare in the market. Having this unique combination of skills will undoubtedly make your employers love you.

One study revealed that staff use 12.5% of their total time on tasks like data collection. The use of machine learning can minimize this loss for sure. Here is one more shocking fact. The report revealed by Kaggle found that only around 4.5% of data scientists have specialized knowledge of machine learning. Just by looking at these facts, we can conclude that the combination of machine learning and Big Data can immediately make you a star.

7) Ability to learn quickly

Being able to learn quickly will make companies want to hire you. Businesses are rapidly changing these days. Corporations do not want to get stuck with employees who are resistant to change. Make yourself able to learn and adapt quickly, and your chance of hiring will dramatically increase.

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Over to You – Big Data Skills and Tools

How many skills do you already have in your arsenal? The more skills you have, the better your chances of getting hired. According to the report, the demand for data scientists is still on rising along with their pay scale. Always be willing to walk an extra mile to increase your chances of landing a job or raising your pay.

You must keep on sharpening your skills and updating your knowledge. Last but not least, do not forget to put all of your skills and certifications on your portfolio/resume. I hope you’ve found value in this article. Do you feel like adding more value to this article? If yes, feel free to comment below. We would be more than happy to answer your queries.