Analytics

Top 6 big data tools to master in 2017

03rd Jan `17, 11:20 AM in Analytics

The market is flooded with a number of Big Data tools. All of them claim to provide real…

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Mythili Devi Contributor
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The market is flooded with a number of Big Data tools. All of them claim to provide real business value by bringing cost efficiency, better time management, and analyzing data to discover valuable business insights.

But there are only a select few that actually do this. We have picked out the best tools that are used by Dig Data professionals that will continue to be popular in 2017.

1. Hadoop

The name Hadoop has become synonymous with big data. Hadoop is an open-source software-framework for distributed storage of large datasets on computer clusters. In layman terms, this means that you have the ability to scale your data without the worry of hardware failures. Hadoop provides large amounts of storage for all sorts of data along with the ability to handle virtually limitless concurrent jobs or tasks.

Salary: Professionals with skills in Hadoop earn up to $121,313.

Certification: With Hadoop topping the list of Big Data tools, certification is extremely important to show employers that you have the skills that will meet the industry standards. Simplilearn offers certification training in Hadoop – Big Data Hadoop and Spark Developer. This course is designed to prepare you for your assignments in the world of Big Data. With access to practice tests, simulation exams, and content created by global thought-leaders, you can become the Hadoop expert companies are looking for.

2. Cloudera:

Cloudera is a company that makes a commercial version of Hadoop. Now, although Hadoop is a free and an open-source project to store large amounts of data, the free version of Hadoop is not easy to use. Thus, a number of companies have developed friendlier versions of Hadoop, and Cloudera is the most popular of them all.

Salary: Professionals with Cloudera skills earn up to $126,816.

3. MongoDB:

MongoDB is a good resource to manage data that is frequently changing or data that is semi-structured or unstructured. Most often, it is used to store data in mobile apps, product catalogs, real-time personalization, content management, and applications that deliver a single view across multiple systems.

Salary: Professionals with MongoDB skills earn up to $117,000.

4. Hive:

This software facilitates managing and querying large datasets residing in the distributed storage. Apache Hive provides a mechanism that helps project structure into this data and then query it using HiveQL – an SQL-like language.

At the same time, this language allows traditional map/reduce programmers to plug in their custom mappers and reducers when it is inconvenient or inefficient to express this logic in HiveQL.

Salary: Professionals with skills in Hive earn up to $120,873.

5. Spark:

An open-source data analytics cluster computing framework, Apache Spark fits into the Hadoop Distributed File System (HDFS). Spark promises a performance that is up to 100 times faster than Hadoop MapReduce.

Salary: Professionals with this skill earn an average salary of $105,000.

6. Tableau:

Tableau is a data visualization tool whose primary focus is on business intelligence. With Tableau, you have the ability to create bar charts, maps, scatter plots, and more without programming.

Salary: Professionals with skills in Tableau earn an average salary of $102,000.

Certification: Simplilearn offers certification training in Tableau – Tableau Desktop 9 Qualified Associate training course. With the option to attend live instructor-led classes or study on your own, this certification training offers simulation exams as well as practice tests for hands-on learning.

Well, there you have it – the top big data tools to master in 2017. Gear up for the opportunities in the New Year by updating your skills. Take up a certification today!

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