Cloudera Data Analyst Training: Using Pig, Hive and Impala with Hadoop (CDAPHIH)
Who should attend
This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators.
Prerequisites
Knowledge of SQL is assumed, as is basic Linux command-line familiarity. Knowledge of at least one scripting language (e.g., Bash scripting, Perl, Python, Ruby) would be helpful but is not essential. Prior knowledge of Apache Hadoop is not required.
Course Objectives
Through instructor-led discussion and interactive, hands-on exercises, you will navigate the Hadoop ecosystem, learning topics such as:
- The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysis
- The fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with Hadoop tools
- How Pig, Hive, and Impala improve productivity for typical analysis tasks
- Joining diverse datasets to gain valuable business insight
- Performing real-time, complex queries on datasets
Course Content
Cloudera University’s four-day data analyst training course focusing on Apache Pig and
Hive and Cloudera Impala will teach you to apply traditional data analytics and business
intelligence skills to big data. Cloudera presents the tools data professionals need to
access, manipulate, transform, and analyze complex data sets using SQL and familiar
scripting languages.
Apache Hive makes multi-structured data accessible to analysts, database administrators, and others without Java programming expertise. Apache Pig applies the fundamentals of familiar scripting languages to the Hadoop cluster. Cloudera Impala enables real-time interactive analysis of the data stored in Hadoop via a native SQL environment.
Classroom Training
Duration 4 days
Price (excl. tax)
- Eastern Europe: 2,495.- €
Online Training
Duration 4 days
Price (excl. tax)
- Eastern Europe: 2,495.- €
Slovenia
Currently no local training dates available. For enquiries please write to info@fastlane.si.
Europe
United Kingdom
26/03/2019 - 29/03/2019 | Online Training Time zone: Europe/London Course language: English | Enroll |