Course Outline
Introduction
Overview of "Open Studio for Big Data" Features and Architecture
Setting up Open Studio for Big Data
Navigating the UI
Understanding Big Data Components and Connectors
Connecting to a Hadoop Cluster
Reading and Writing Data
Processing Data with Hive and MapReduce
Analyzing the Results
Improving the Quality of Big Data
Building a Big Data Pipeline
Managing Users, Groups, Roles, and Projects
Deploying Open Studio to Production
Monitoring Open Studio
Troubleshooting
Summary and Conclusion
Requirements
- An understanding of relational databases
- An understanding of data warehousing
- An understanding of ETL (Extract, Transform, Load) concepts
Audience
- Business intelligence professionals
- Database professionals
- SQL Developers
- ETL Developers
- Solution architects
- Data architects
- Data warehousing professionals
- System administrators and integrators
Testimonials (4)
how the trainor shows his knowledge in the subject he's teachign
john ernesto ii fernandez - Philippine AXA Life Insurance Corporation
Course - Data Vault: Building a Scalable Data Warehouse
I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.
Aurelia-Adriana - Allianz Services Romania
Course - Python and Spark for Big Data (PySpark)
A lot of practical examples, different ways to approach the same problem, and sometimes not so obvious tricks how to improve the current solution
Rafał - Nordea
Course - Apache Spark MLlib
This is one of the best hands-on with exercises programming courses I have ever taken.