Cloudera University’s four-day data analyst course is for anyone who wants to access, manipulate, transform, and analyze massive data sets in the Hadoop cluster using SQL and familiar scripting languages. This is the core curriculum in the data analyst learning path.
Cloudera University’s Data Analyst Training course focuses on Apache Pig, Apache Hive, and Apache Impala. You will learn how 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 Pig applies the fundamentals of familiar scripting languages to the Hadoop cluster. Apache Hive makes transformation and analysis of complex, multi-structured data scalable in Hadoop. Cloudera Impala enables real-time interactive analysis of the data stored in Hadoop via a native SQL environment. Together, Pig, Hive, and Impala make multi-structured data accessible to analysts, database administrators, and others without Java programming expertise.
Who should attend
This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. 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.
- Knowledge of SQL
- Basic Linux command-line familiarity
- Knowledge of at least one scripting language (e.g., Bash scripting, Perl, Python, Ruby)
- Prior knowledge of Apache Hadoop is not required
Through instructor-led discussion and interactive, hands-on exercises, participants 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
- 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
- Apache Hadoop Fundamentals
- Introduction to Apache Pig
- Basic Data Analysis with Apache Pig
- Processing Complex Data with Apache Pig
- Multi-Dataset Operations with Apache Pig
- Apache Pig Troubleshooting and Optimization
- Introduction to Apache Hive and Impala
- Querying with Apache Hive and Impala
- Apache Hive and Impala Data Management
- Data Storage and Performance
- Relational Data Analysis with Apache Hive and Impala
- Complex Data with Apache Hive and Impala
- Analyzing Text with Apache Hive and Impala
- Apache Hive Optimization
- Apache Impala Optimization
- Extending Apache Hive and Impala
- Choosing the Best Tool for the Job