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Building a Big Data Analytics Stack

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Building a Big Data Analytics Stack
Building a Big Data Analytics Stack
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 277 MB
Genre: eLearning | Language: English

Building a Big Data ecosystem is hard. There are a variety of technologies available and every one of them has its pros and cons. When building a big data pipeline for software engineers, we need to use more low-level tools and APIs such as HBase and Apache Spark.

In this course, we’ll check out HBase, a database built by optimizing on the HDFS. Moving on, we’ll have a bit of fun with Spark MLlib. Finally, you’ll get an understanding of ETL and deploy a Hadoop project to the cloud. Building Big Data Ecosystem is hard. There are a variety of technologies available and every one of them has own pros and cons. Software Engineers we need to use more low-level tools and APIs like HBase and Apache Spark while building big data pipeline.

By the end of the course, you’ll be able to use more high-level tools that have more user-friendly, declarative APIs such as Pig and Hive.

Building a Big Data Analytics Stack

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