Big Data Framework — Hadoop vs Apache Spark

Big Data and Hadoop Online training are the most sought after online activity these days, let us understand why?. Technology changes faster than we think these days. A new language, technology, smartphone or a new word is trending before we reach home from the office. But, there is certain tech that leaves an impression and creates jobs. Big data has created a market need of its own. Hadoop and Spark are the open source frameworks used for the implementation of Big Data technologies. With more and more organizations preparing themselves for handling large amounts of data, these open source frameworks have seen a rise in demand. Hadoop is essentially used for Storage and managing considerable amounts of data, while spark helps process this data better. Since they go hand in hand, let’s take a closer look at Hadoop and Spark.

Starting the Data journey — Learning Hadoop
Hadoop has been the open source framework adopted by Data Scientists and Architects to help scale up operations. It helps identify business scenarios where data science can provide impactful results. Zeroing in on the statistical methods required to leverage business pipelines. Needless to say, Hadoop has been the first step or rather stepping stone for most companies aiming to leverage Big Data for putting a method to their business.

Ideally, students who have made a mark have had knowledge of Core Java and SQL but it is not a prerequisite. From there with the help of our Online and Classroom training tracks, they have gone on to master the concepts of Hadoop. This implies mastered skills in MapReduce, HDFS, Hadoop Streaming, and later Apache Hive. All are related Hadoop technologies and concepts. Once you gain a stronghold on Hadoop, the next stop is Apache Spark. Here is a look at whys and hows of Adobe Spark.

Graduating to the Advanced stage — Apache Spark
Once you have mastered Hadoop, you can then graduate to Apache Spark. It is an application programming interface that helps programmers and data analysts a faster way to analyze data, is easy to use and has in-memory features. This allows data scientists to work on data streaming, machine learning or SQL. With its ability to address the shortcomings of Hadoop, it has registered itself as a force in the world of Big Data. So, learning it and getting certified on Apache Spark has become an important career objective. Since Hadoop and Spark are different technologies, organization appreciate candidates who have mastered both.

Getting Certified — Making a Mark
Certifications help in two things. One, identifying subject areas and mastering them and second, finding a good job or project. Apache Spark Certification Course is a sure way of gaining attention to your resume. One of the most sought after certification right now in the market by recruiters looking to fill plum job positions in top notch organizations and Startups alike.

Show your support

Clapping shows how much you appreciated sandeep’s story.