How to use Cloudera Data Platform (CDP)

Here’s a detailed training path for mastering Cloudera, moving from beginner to advanced levels:

Beginner Level

1. Introduction to Big Data and Hadoop
   • Objective: Understand the basics of Big Data and Hadoop ecosystem.
   • Key Topics:
     • Introduction to Big Data
     • Hadoop architecture
     • HDFS (Hadoop Distributed File System)
     • MapReduce
2. Cloudera Essentials
   • Objective: Familiarize with Cloudera platform and its components.
   • Key Topics:
     • Overview of Cloudera Distribution
     • Cloudera Manager basics
     • Introduction to Cloudera components (Hadoop, Hive, HBase, etc.)
3. Cloudera Certified Associate (CCA) Certification Preparation
   • Objective: Prepare for the CCA certification exam.
   • Key Topics:
     • Data ingestion with Sqoop and Flume
     • Transforming data using Pig and Hive
     • Data analysis using Impala and Hive
     • Understanding data storage in HDFS and HBase

Intermediate Level

4. Advanced Hadoop
   • Objective: Deep dive into Hadoop and its advanced features.
   • Key Topics:
     • Advanced HDFS and MapReduce concepts
     • YARN resource management
     • Performance tuning and optimization
     • Hadoop security
5. Cloudera Administration
   • Objective: Learn to manage and administer Cloudera clusters.
   • Key Topics:
     • Cloudera Manager deep dive
     • Cluster planning and installation
     • Cluster monitoring and troubleshooting
     • Upgrading and managing clusters
6. Data Analysis with Cloudera
   • Objective: Perform complex data analysis using Cloudera tools.
   • Key Topics:
     • Advanced Hive and Impala
     • Data warehousing with Cloudera
     • Spark integration with Cloudera
     • Using Hue for data analysis

Advanced Level

7. Cloudera Data Science and Machine Learning
   • Objective: Implement data science and machine learning projects using Cloudera.
   • Key Topics:
     • Introduction to Cloudera Data Science Workbench
     • Data preprocessing and exploration
     • Machine learning with Spark MLlib
     • Advanced analytics with Cloudera
8. Cloudera Security and Governance
   • Objective: Ensure security and governance in Cloudera environments.
   • Key Topics:
     • Kerberos and LDAP integration
     • Data encryption and masking
     • Auditing and compliance
     • Data lineage and governance
9. Cloudera Certified Professional (CCP) Certification Preparation
   • Objective: Prepare for the CCP certification exam.
   • Key Topics:
     • Real-world data engineering tasks
     • Complex data transformations and analysis
     • Performance tuning and optimization
     • Comprehensive case studies

Resources and Practice

• Books:
  • “Hadoop: The Definitive Guide” by Tom White
  • “Data Science and Big Data Analytics” by EMC Education Services
  • “Hadoop Operations” by Eric Sammer
• Practice and Hands-on Labs:
  • Cloudera Live (Cloudera’s own cloud-based platform for practice)
  • AWS and GCP for setting up your own Cloudera clusters
  • Practice projects and case studies
• Communities and Forums:
  • Cloudera Community Forum
  • Stack Overflow
  • LinkedIn Groups and other professional networks

By following this guided path, you can progress from a beginner to an advanced Cloudera professional, equipped with the skills needed to manage and analyze big data using Cloudera’s suite of tools.