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Hadoop Salary: A Complete Guide from Beginners to Advance

Knowledge Hut

Developers proficient in various programming languages, tools, and frameworks are likely to get paid more. Skills: Develop your skill set by learning new programming languages (Java, Python, Scala), as well as by mastering Apache Spark, HBase, and Hive, three big data tools and technologies. A Master's or Ph.D.

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Hadoop Jobs Salary Trends in India

ProjectPro

Major industries driving demand for analytics talent in India are - e-Commerce & Retail , Insurance, Finance, Manufacturing and IT with e-Commerce being the highest paymaster for Hadoop salaries in India. If you are looking for big leap in your career, then this is the best time to master big data skills.

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Global Big Data & Hadoop Developer Salaries Review

ProjectPro

Having highlighted the demand for open source developers, one cannot ignore what’s trending in the open source technology domain. As open source technologies gain popularity at a rapid pace, professionals who can upgrade their skillset by learning fresh technologies like Hadoop, Spark, NoSQL, etc.

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Data Scientist Salary-The Ultimate Guide for 2023

ProjectPro

This blog breaks down the data science salary figures for today’s data workforce based on which company they work for, years of experience, specialization of data science tools and technologies, location, and other factors. The salary of a data scientist usually increases in the first few years.

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How to Become a Big Data Engineer in 2023

ProjectPro

Big Data refers to the massive volumes of data which is no longer possible to manage using traditional software applications. Automated tools are developed as part of the Big Data technology to handle the massive volumes of varied data sets. from tons of free online resources.

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Top 20 Data Analytics Projects for Students to Practice in 2023

ProjectPro

Table of Contents Skills Required for Data Analytics Jobs Why Should Students Work on Big Data Analytics Projects ? Data analytics projects for practice help one identify their strengths and weaknesses with various big data tools and technologies.