Future growth prospects for Hadoop and Spark

Would like to know what are the future growth prospects for Hadoop and Spark?

Big Data with Hadoop & Spark is the most promising and high-potential technological domain for future.
Check the following projections:

  • IDC says that worldwide revenues for big data and business analytics will grow from $130.1 billion in 2017 to more than $203 billion in 2020, at a compound annual growth rate (CAGR) of 11.7%

  • “Data monetization” will become a major source of revenues, as the world will create 180 zettabytes of data (or 180 trillion gigabytes) in 2025, according to IDC.

  • The Hadoop market is forecast to grow at a compound annual growth rate (CAGR) 58% surpassing $16 billion by 2020. (Market Analysis)
    https://www.marketanalysis.com/?p=279

  • Global Apache Spark market will grow at a CAGR of 67% between 2017 and 2020. The global Spark market revenue is rapidly expanding and may grow up $4.2 billion by 2020, with a cumulative market valued at $9.2 billion.
    https://www.marketanalysis.com/?p=159

  • Spark will reinvigorate Hadoop, nine out of every 10 projects on Hadoop will be Spark-related projects. — said Monte Zweben, CEO of Splice Machine

  • According to a market forecast released this week by Allied Market Research, the Hadoop market is expected to grow at a 63.4 percent compound annual growth rate over the next five years, reaching $84.6 billion by 2021.

  • According to the McKinsey Global Institute, data scientists demand is growing by as much as 12 percent a year and there could be a shortage of as many as 250,000 data scientists by 2024 in US economy.

  • As per prediction by Robert half, Data Scientist salaries are predicted to range from $116,000 to $163,500 in 2017 which is an increase of about 6.4% over 2016 salary levels. Similarly Big Data Engineer salaries are predicted to range from $135,000 to $196,000 in 2017, increasing 5.8% over 2016 salary levels.

All the above projections explain why CloudxLab has such strong focus on Big Data, Hadoop & Spark.

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