Big Data and AI Careers in 2018: Hadoop, Spark and Scala are Key

From Apple Watch reminders to breathe, to advertisements for recent purchase considerations appearing in your feed, Big Data, AI and Data Analytics has moved beyond “the next big thing.” Big Data – a term originally coined for data that has various attributes such as volume, variety, validity and volatility to name a few – has fundamentally changed business practices across every company. It is now ubiquitous across every function and department of enterprises both large and small. The complex challenge for enterprises to capture, understand, analyze, interpret and harness big data in a meaningful and relevant way is led by data scientists, business intelligence analysts, data architects, and developers.

Facts about Big Data Careers
​

• Six analytics and data science jobs are included in Glassdoor’s 50 best jobs In America for 2018. These include Data Scientist, Analytics Manager, Database Administrator, Data Engineer, Data Analyst and Business Intelligence Developer. 
• 94% of U.S. graduates in the data science sector obtained a job within six months, with an average salary of $114,000 a year since 2011. (Glassdoor)
• Data scientists rate their job satisfaction rating a 4.2 on a scale of 5 (Glassdoor) – the highest for any profession.
• Hadoop and the Big Data markets are projected to grow from $17.1B in 2017 to $99.31B in 2022 attaining a 28.5% CAGR. The greatest period of projected growth is in 2021 and 2022 when the market is projected to jump $30B in value in one year. (StrategyMRC and reported by Statista)

What’s Hadoop got to do with it?

Hadoop, as a framework, has proven its worth in the Data Analytics revolution because of its unique feature set – cost effectiveness, flexibility and scalability. Big Data Hadoop is synonymous to a golden goose for IT professionals. The more proficient you are in big data related technologies like Hadoop and its ecosystem and real time in-memory computing framework Spark, the more likely it is that you can command higher pay checks.
 
To be a part of the Big Data revolution, here are some basics:
 

1. Understand how to work with varied and large datasets for processing and insight gathering using programming languages such as Python, Scala, Java or even C++. See upcoming dates for Mindteck’s Python course
2. Understand how to manage the stack with DevOps tools and technologies such as Docker, Linux/Bash, Jenkins, Git, Puppet, etc.
3. Understand how to work in virtualization enabled environments or cloud solutions, such as AWS, Google Cloud or Azure.
4. Add Big Data fundamentals with Apache Hadoop. While free tutorials will give you the basics, an instructor-led course will provide hands-on instruction, real-life Hadoop application assignments, and live feedback to ensure your skills are on track with market demand. Mindteck Academy’s enterprise-focused and Course Report recognized Hadoop with Spark and Scala course starts September 17th.
5. Learn a concise way of programming in Scala and data acquisition, transformation and performance efficient in-memory processing of varied datasets using Spark and its components.
6. Embrace change and stay looped into learning. Big Data is moving fast and staying ahead of the curve requires a commitment to adapting skills and lifelong passion for learning.
7. Learn by doing. Mindteck Academy’s Hadoop course incorporates real-life challenges and projects that not only build your skills but expand your project portfolio, providing you with demonstrable skills to prospective employers. Learn from discussions about real time use cases where Big Data technologies are used to help you visualize the landscape and understand why companies are preferring Big Data solutions over their existing technology stack.
8. Be a problem solver. If you’re already intrigued by programming and math, you are by nature a ‘problem solver.’ Take that skillset to each experience and let the data drive your decisions.

 
 
So why add Spark with Scala?

Apache Spark is a second-generation Big Data toolset, providing both batch and streaming processing capabilities for faster data processing. Spark works seamlessly with Hadoop, leveraging the same hardware and resource management layer – Yarn. Apart from this, Spark can process the data stored in HDFS (Hadoop Distributed File System). Since Spark projects are developed using Scala, becoming an expert in Scala is imperative.

Now what?
 
There is currently a shortage of skilled resources who can work in the Big Data space -- Big Data Developer, Data Analysts, Big Data Consultants, Big Data Platform Engineers, Architects, Solution Analysts, Data Scientists and many other roles. All of these positions require profound knowledge of Big Data tools and technologies, i.e. Hadoop ecosystem and its components, with an emphasis on in-memory and real-time processing frameworks, such as Spark.
 
Mindteck Academy’s live, instructor-led Hadoop, Spark and Scala course is a structured program covering detailed learning on the Hadoop ecosystem components, curated and taught by an industry expert. Mindteck Academy’s rigorous course prepares students for enterprise-level positions, broadens their skillset, and increases their value to an organization.
 
Click to book your seat today