Spark SQL & Hadoop (For Data Scientists & Big Data Analysts)

• Students will get hands-on experience working in a Spark Hadoop environment that’s free and downloadable as part of this course.
• Students will have opportunities solve Data Engineering and Data Analysis Problems using Spark on a Hadoop cluster in the sandbox environment that comes as part
• Issuing HDFS commands.
• Converting a set of data values in a given format stored in HDFS into new data values or a new data format and writing them into HDFS.
• Loading data from HDFS for use in Spark applications & writing the results back into HDFS using Spark.
• Reading and writing files in a variety of file formats.
• Performing standard extract, transform, load (ETL) processes on data using the Spark API.
• Using metastore tables as an input source or an output sink for Spark applications.
• Applying the understanding of the fundamentals of querying datasets in Spark.
• Filtering data using Spark.
• Writing queries that calculate aggregate statistics.
• Joining disparate datasets using Spark.
• Producing ranked or sorted data.

Who this course is for:

• This course has been designed specifically for data scientists, big data analysts and data engineers looking to leverage the power of Hadoop and Apache Spark to make sense of big data.
• This course is also well suited for university students and recent graduates that are keen to land a job with a company that’s looking to fill a big data-related positions or anyone who simply wants to apply their SQL skills in a big data environment using Spark-SQL.
• Software engineers & developers who are looking to break into the Data Engineering field will also find this course helpful.