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Chapter 1: Overview of the CDP Data Analyst Exam

Chapter 2: Understanding the Role of a CDP Data Analyst

Chapter 3: Exam Structure and Preparation Guidelines

Chapter 4: Introduction to Cloudera Data Visualizations

Chapter 5: Building Effective Dashboards

Chapter 6: Interpreting Data Visualizations

Chapter 7: Introduction to Apache Hive and Impala

Chapter 8: Working with Databases and Tables in Impala

Chapter 9: Formatting and Converting Data Types

Chapter 10: Joining Tables in Apache Hive and Impala

Chapter 11: Understanding Primary and Foreign Keys in Hive and Impala

Chapter 12: Creating New Tables and Views

Chapter 13: Writing Efficient Hive and Impala SQL Queries

Chapter 14: Understanding Data Lineage with Apache Atlas

Chapter 15: Defining Access Policies in Apache Ranger

Chapter 16: Roles and Responsibilities of a Data Steward

Chapter 17: Using Aggregate Functions in Hive and Impala

Chapter 18: Calculating and Interpreting Aggregate Statistics

Chapter 19: Understanding Filter Condition Pushing

Chapter 20: Implementing Bucketing for Performance Optimization

Chapter 21: File Format Optimization Techniques

Chapter 22: Using Compute Stats for Query Optimization

Chapter 23: Understanding HDFS Data Storage and Access

Chapter 24: Storing Query Results: Tables vs. Directories

Chapter 25: Differentiating External and Managed Tables

Chapter 26: Using Partitioning for Data Management

Chapter 27: Introduction to Cloudera Data Warehouse

Chapter 28: Managing Virtual Warehouses in CDP

Chapter 29: Using the Data Catalog Service

Chapter 30: Best Practices for Data Analysts Using CDP

Chapter 31: Common Pitfalls and How to Avoid Them

Chapter 32: Preparing for the CDP Data Analyst Exam

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