Apache Zeppelin is a web-based notebook for capturing, exploring, visualizing, and sharing Hadoop and Spark-based data.
Lara Online Training will provide instructor-led, live training that introduces the concepts behind interactive data analytics, and walks participants through the deployment and usage of Zeppelin in a single-user or multi-user environment.
By the end of this training, participants will be able to:
- Install and configure Zeppelin
- Develop, organize, execute and share data in a browser-based interface
- Visualize results without referring to the command line or cluster details
- Execute and collaborate on long workflows
- Work with any of a number of plug-in language/data-processing-backends, such as Scala (with Apache Spark), Python (with Apache Spark), Spark SQL, JDBC, Markdown, and Shell.
- Integrate Zeppelin with Spark, Flink, and Map Reduce
- Secure multi-user instances of Zeppelin with Apache Shiro
Target audience
- Students
- Big Data and Hadoop Professionals
- IT professionals
Prerequisites
Professionals with experience in IT and Students eager to learn can undergo this training.
Why Should I choose Lara Online Training?
- We provide Very in-depth course material with Real Time Scenarios for each topic with its Solutions for, Apache Zeppelin Online Training.
- At Lara, we provide case studies in real-time applications with a professional explanation.
- We do Schedule the sessions based upon your comfort by our Highly Qualified Trainers and Real-time Experts.
- Class recordings are available immediately after the session for future reference.
- We do Normal Track, Fast Track, and Weekend Batches for Apache Zeppelin Online Training.
- We assist you with cost Effective and Flexible Payment Schemes.
- At Lara, we provide Placement Assistance.
- We provide Assessment and Mock Interviews
1
Introduction
2
Installing and Configuring Zeppelin
3
Overview of Zeppelin Features and Architecture
4
Navigating the Browser Interface
5
Understanding the Data Analysis Workflow
6
Organizing Data for Analysis
7
Visualizing Data
8
Sharing Data and Collaborating with Other Analysists
9
Working with Plug-in
10
Backend Data Processing
11
Working with Scala and Apache Spark
12
Working with Python and Apache Spark
13
Working with Spark SQL
14
Working with JDBC
15
Using Markdown and Shell
16
Integrating Zeppelin with Spark, Flink and Map Reduce
17
Setting up and Securing Multi-user Instances
18
Troubleshooting
19
Summary and Conclusion
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