Thomas Henson

  • Data Engineering Courses
    • Installing and Configuring Splunk
    • Implementing Neural Networks with TFLearn
    • Hortonworks Getting Started
    • Analyzing Machine Data with Splunk
    • Pig Latin Getting Started Course
    • HDFS Getting Started Course
    • Enterprise Skills in Hortonworks Data Platform
  • Pig Eval Series
  • About
  • Big Data Big Questions

35 Reasons to Learn Hadoop Today

June 13, 2016 by Thomas Henson Leave a Comment

The best time to plant a tree was 20 years ago, the second best time to plant one is today.

Okay so what does this old Chinese proverb have to do with learning Hadoop? Let’s break down the proverb. Trees are awesome when they are huge and provide a ton of shade or have large branches for tire swings. However to enjoy a tree like this it has be planted a long time ago. I live in a new neighborhood so I’m out of luck.

Reasons to learn Hadoop Today

Learning a new technology is like planting a tree. Everyone wants to enjoy the shade or be an expert without having to put in the time.

Hadoop & Spark are hot topics right now in the Dev/IT space. Many companies are looking for experts in Hadoop. Truth be told there aren’t many out there. The technology is new and evolving daily. Just checkout this blog post I wrote over a year ago about the popular frameworks, the number of new projects has doubled since that post was written.

Reason to learn Hadoop today..

So why don’t you become an expert in the Hadoop space? The best time to to start is today. Sign up for my newsletter to learn how you can become a Hadoop expert.

  1.  You can command a higher salary (average 140K/year).
  2. You can get in on the ground floor of the Big Data movement.
  3. You can contribute to the “Big Data” frameworks through the opensource community.
  4. Chance to work with enormous data sets. Well it is BIG data…
  5. Opportunity to change the world with data.
  6. Huge community support.
  7. Work some of the biggest companies on the planet. Facebook, Verizon, Netflix, MLB,…..
  8. Cutting edge technology that is constantly evolving.
  9. Internet of Things
  10. Get to play with Hadoop’s friends Sqoop, Kafka, Pig, Hive, HBase, and many more.
  11. Top required skill employers are looking for.
  12. Unstructured data is exploding. Think Exabytes.
  13. Many available languages to write to write Map Reduce jobs with. Java, Python, Scala.
  14. Telling people at a dinner party that you do Machine learning is great conversation starter.
  15. Chance to learn something new EVERYDAY.
  16. Self driving cars.
  17. You run Hadoop on Linux.
  18. Hadoop is a scale out architecture.
  19. You will learn to love statistics.
  20. You will blow people away with your knowledge of algorithms.
  21. You get to us Mahout for K-means, Singular Value Decomposition, Least Squared, and more.
  22. You will begin to says phrases like “it was a small data set of only 10 terabytes”.
  23. Autonomous agents are mind blowing.
  24. Your Marketing friends are going to love you.
  25. The Elephants, Hives , and Pigs are going to need a Zookeeper.
  26. You can analyze video data.
  27. Data Scientist is ranked the #1 sexiest job of 21st century.
  28. MapReduce can be easy. 
  29. high demand + talent gap = multiple opportunities
  30. Hadoop runs from the command line.
  31. Java is your friend.
  32. Future proofing your career.
  33. You can become a Chief Data Officer
  34. Predictive and prescriptive analytics are cool.
  35. All companies are becoming data companies.

How many more reasons do you need to learn Hadoop today? If you are ready then I suggest you with my Hadoop from the command line course to learn the basics.

Related

Filed Under: Hadoop Tagged With: Big Data, Hadoop, Machine Learning

Subscribe to Newsletter

Archives

  • February 2021 (2)
  • January 2021 (5)
  • May 2020 (1)
  • January 2020 (1)
  • November 2019 (1)
  • October 2019 (9)
  • July 2019 (7)
  • June 2019 (8)
  • May 2019 (4)
  • April 2019 (1)
  • February 2019 (1)
  • January 2019 (2)
  • September 2018 (1)
  • August 2018 (1)
  • July 2018 (3)
  • June 2018 (6)
  • May 2018 (5)
  • April 2018 (2)
  • March 2018 (1)
  • February 2018 (4)
  • January 2018 (6)
  • December 2017 (5)
  • November 2017 (5)
  • October 2017 (3)
  • September 2017 (6)
  • August 2017 (2)
  • July 2017 (6)
  • June 2017 (5)
  • May 2017 (6)
  • April 2017 (1)
  • March 2017 (2)
  • February 2017 (1)
  • January 2017 (1)
  • December 2016 (6)
  • November 2016 (6)
  • October 2016 (1)
  • September 2016 (1)
  • August 2016 (1)
  • July 2016 (1)
  • June 2016 (2)
  • March 2016 (1)
  • February 2016 (1)
  • January 2016 (1)
  • December 2015 (1)
  • November 2015 (1)
  • September 2015 (1)
  • August 2015 (1)
  • July 2015 (2)
  • June 2015 (1)
  • May 2015 (4)
  • April 2015 (2)
  • March 2015 (1)
  • February 2015 (5)
  • January 2015 (7)
  • December 2014 (3)
  • November 2014 (4)
  • October 2014 (1)
  • May 2014 (1)
  • March 2014 (3)
  • February 2014 (3)
  • January 2014 (1)
  • September 2013 (3)
  • October 2012 (1)
  • August 2012 (2)
  • May 2012 (1)
  • April 2012 (1)
  • February 2012 (2)
  • December 2011 (1)
  • September 2011 (2)

Tags

Agile AI Apache Pig Apache Pig Latin Apache Pig Tutorial ASP.NET AWS Big Data Big Data Big Questions Book Review Books Data Analytics Data Engineer Data Engineers Data Science Deep Learning DynamoDB Hadoop Hadoop Distributed File System Hadoop Pig HBase HDFS IoT Isilon Isilon Quick Tips Learn Hadoop Machine Learning Machine Learning Engineer Management Motivation MVC NoSQL OneFS Pig Latin Pluralsight Project Management Python Quick Tip quick tips Scrum Splunk Streaming Analytics Tensorflow Tutorial Unstructured Data

Follow me on Twitter

My Tweets

Recent Posts

  • Tips & Tricks for Studying Machine Learning Projects
  • Getting Started as Big Data Product Marketing Manager
  • What is a Chief Data Officer?
  • What is an Industrial IoT Engineer with Derek Morgan
  • Ultimate List of Tensorflow Resources for Machine Learning Engineers

Copyright © 2023 · eleven40 Pro Theme on Genesis Framework · WordPress · Log in

 

Loading Comments...