How the Apache Spark and Scala Training Course Can Transform Your Career in Big Data

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(Newswire.net — May 28, 2019) — No conversation about the importance of Big Data analytics is complete without mentioning its enabling technologies like Hadoop, Apache Spark, and Scala. A December 2018 article published by Forbes revealed that Big Data adoption continues to grow in the year 2018 with 59% of the enterprises adopting Big Data practices (as compared to just 17% in the year 2015). Apache Spark continues to be among the major technologies being used to access and analyse Big data.

A 2018 study conducted by Dresner Advisory Services reveals that Big Data is no longer an exclusive IT function but is being implemented in multiple areas like R&D, Business intelligence, Sales & Marketing, and Operations.

How Apache Spark and Scala Training Can Benefit You

A McKinsey industry report reveals that the U.S. alone is facing a shortage of up to 190,000 professionals skilled in Big data and analytical skills in the year 2018. Additionally, American corporations are facing a shortage of 1.5 million data analysts and managers skilled in the use and adoption of Big data technologies.

The increasing industry demand and shortage of Big Data specialists trained in technologies like Apache Spark and Scala make it the best time for software developers and data scientists to be trained in these skills. Apache Spark programmers and developers are earning the highest average salary among those skilled in Big data and Hadoop development.

A comprehensive Big data training program conducted by a reputed training institute can train you in writing machine learning algorithms on Big data sets using the Apache Spark data processing framework and the Scala programming language.

Listed below are some of the key reasons why you should go for an Apache Spark and Scala course from a premier training provider:

  • Seamless integration with the Hadoop distributed file system and as a viable replacement for MapReduce.
  • Deployed use of Apache Spark in production in multiple industry sectors.
  • Increasing investments made by corporations in Big data technologies.
  • Lucrative career opportunities for data engineers skilled in Apache Spark and Scala.

An additional industry trend is that organizations are increasingly hiring Hadoop developers who have also gained expertise in the practices and implementation of Apache Spark.

How to Be Trained in Apache Spark and Scala Skills

To be designated as an Apache Spark and Scala specialist, you can go for a certification course in Apache Spark and Scala from a reputed institute. By completing this training program, you can obtain detailed and practical knowledge about Apache Spark and Scala concepts along with key elements like Apache Spark Core, Spark Internals, Spark SQL, Spark Streaming, GraphX, and Spark MLlib. You can also gain detailed working knowledge about the functioning of Scala programming language.

Completing the Apache Spark and Scala training can prepare you to appear for the Spark and Hadoop Developer Certification examination conducted by Cloudera Certified Associate (or CCA).

What Is the Prerequisite for Students Going for Apache Spark and Scala Training?

Candidates going for the Apache Spark and Scala training program must be familiar with the basics of how Hadoop works. The Apache Spark and Scala course are most beneficial for the following professionals:

  • Data scientists and analysts.
  • Data engineers.
  • Software developers and programmers.
  • Business intelligence and ETL specialists.
  • Software architects and engineers.
  • Professionals and freshers aspiring for a career in Big Data analytics.

How Are the Apache Spark and Scala Courses Conducted?

Generally, Apache Spark and Scala courses are of 24-hour (or 3-day) duration that is conducted through instructor-led classroom sessions on the fundamentals of the Apache Spark environment. Through interactive learning and hands-on sessions, students can master the concepts of Apache Spark from a certified and industry-experienced instructor.

Students attending Apache Spark and Scala training are also required to complete an industry project in Apache Spark, which is then reviewed by the instructors or Spark experts.

At the end of the Apache Spark and Scala training course, students learn:

  • Basic concepts of Hadoop and HDFS architecture.
  • Differences between Hadoop and Apache Spark.
  • Core elements of Apache Spark.
  • Understanding of Spark Internals RDD and the use of Spark functions to create and transform RDDs.
  • SQL-related operations using Spark SQL and Hive SQL.
  • Spark programming using Scala tool.
  • Scala-related functions and collections.
  • Overview of Spark streaming, Kafka streaming, Spark MLlib, and Spark GraphX.

If you are looking for a lucrative career in the field of Big data analytics, then getting trained in Apache Spark and Scala would be the ideal start to a long and lucrative career.