Unlock the Power of Data Warehousing with Comprehensive Apache Hive

Apache Hive is a data warehousing and SQL-like query engine built on top of Hadoop, designed to
handle large datasets and enable interactive querying. Hive simplifies the process of working with
vast amounts of data in the Hadoop ecosystem, making it an essential tool for data engineers and
analysts looking to efficiently manage and query structured data. Hive enables you to write SQL-like
queries for Hadoop, allowing you to interact with big data without needing to learn complex
programming languages.

ENCODE-IT’s Comprehensive Hive Certification Course offers a deep dive into the fundamentals and
advanced features of Apache Hive. From setting up Hive on Hadoop clusters to writing complex
queries and optimizing performance, this course is designed to help you master Hive and leverage its
capabilities for data analytics and reporting. You will learn to manage large-scale data in Hadoop and
use Hive's powerful features like partitioning, bucketing, and indexing to improve query
performance. Whether you're a data analyst, data engineer, or someone looking to start a career in
big data, this course provides the essential skills to succeed in the world of data warehousing.

Salary Scale in India
The demand for professionals skilled in big data tools like Apache Hive is rapidly increasing in India.
Entry-level roles, such as Data Engineers or Data Analysts familiar with Hive, can expect to earn
between ₹6,00,000 to ₹9,00,000 annually. With a few years of experience, salaries can rise to
₹12,00,000 to ₹18,00,000 per year. Senior professionals, such as Big Data Architects or Hadoop
Administrators with expertise in Hive, can earn upwards of ₹20,00,000 annually. The growing
reliance on big data technologies in sectors like e-commerce, finance, healthcare, and
telecommunications makes Apache Hive expertise highly sought after.

Placement Assistance & Certification
ENCODE-IT offers certification upon course completion, making you stand out to potential
employers. Our Comprehensive Hive Certification not only validates your expertise in Apache Hive
but also boosts your career prospects in the big data space. Additionally, ENCODE-IT provides
placement assistance, connecting you with top companies looking for skilled professionals in big
data and Hadoop ecosystems.

Course Curriculum

1. Introduction to Apache Hive and Big Data Ecosystem
 Understanding the Big Data Landscape and Apache Hadoop
 Overview of Apache Hive and Its Role in the Hadoop Ecosystem
 Hive’s Architecture: Components and Data Flow
 How Hive Works: From Query Execution to Data Storage
 Installing and Configuring Hive in a Hadoop Cluster
 Setting Up Hive on Local and Clustered Environments

2. Data Models and Querying with Hive
 Understanding Hive Data Types: Primitive and Complex Types

 Creating Databases, Tables, and Partitions in Hive
 HiveQL: A SQL-Like Language for Big Data Queries
 Writing Basic Queries: SELECT, WHERE, GROUP BY, and HAVING
 Loading Data into Hive: Internal vs. External Tables
 Data Types and Data Transformation in Hive Queries

3. Advanced Hive Querying
 Working with Joins: INNER, LEFT, RIGHT, and FULL OUTER
 Subqueries and Nested Queries in Hive
 Windowing Functions in HiveQL
 Aggregate Functions: COUNT, SUM, AVG, MIN, MAX
 Using HiveQL for Data Aggregation and Reporting
 Complex Query Execution and Optimizing Query Plans
 Managing Partitioned Tables for Better Data Organization

4. Partitioning, Bucketing, and Indexing in Hive
 Introduction to Partitioning: Creating and Querying Partitioned Tables
 Managing Data with Bucketing: Data Distribution in Buckets
 Creating and Using Indexes for Faster Querying
 Best Practices for Partitioning and Bucketing Large Datasets
 Optimizing Query Performance with Partitions and Buckets
 Managing Data Skew and Improving Performance with Partition Pruning

5. Hive Storage Formats and Compression
 Understanding Hive’s Storage Formats: Text, ORC, Parquet, Avro
 Choosing the Right Storage Format for Performance and Efficiency
 Working with Columnar Storage Formats: ORC and Parquet
 Compressing Data in Hive to Save Storage and Improve Performance
 Reading and Writing Data in Different Formats
 Best Practices for Managing Data in Hive

6. Hive Performance Tuning and Optimization
 Improving Hive Query Performance: Best Practices
 Cost-Based Optimizer (CBO) and Rule-Based Optimizer (RBO) in Hive
 Indexing and Partitioning Strategies for Performance Optimization

 Query Execution Plan and Query Profiling in Hive
 Caching Results for Faster Query Execution
 Managing Resource Allocation for Hive Jobs and Queries

7. Advanced Hive Features
 Understanding Hive UDF (User Defined Functions) and UDAF (User Defined Aggregate
Functions)
 Writing Custom UDFs in Java to Extend Hive Functionality
 Working with Hive’s Metastore for Metadata Management
 Using Apache Hive with Apache Spark for Real-Time Data Processing
 Integrating Hive with Other Big Data Tools (HBase, Pig, Flume)
 Real-Time Data Ingestion and Streaming Data with Hive

8. Security and Governance in Hive
 Managing Data Security in Hive: Authentication and Authorization
 Role-Based Access Control (RBAC) and User Permissions
 Auditing Data and Tracking Changes in Hive Tables
 Integrating Hive with Apache Ranger for Enhanced Security
 Managing Sensitive Data in Hive
 Implementing Data Governance Practices in Hive Environments

9. Using Hive with Data Warehousing and Reporting Tools

 Integrating Hive with Business Intelligence Tools (Tableau, Power BI, etc.)
 Data Warehousing Concepts and Hive as a Data Warehouse Solution
 Real-Time Reporting and Dashboards with Hive
 Query Optimization Techniques for Faster Reporting
 Integrating Hive with ETL Tools for Data Pipelines
 Automating Hive Queries with Apache Oozie and Airflow

10. Final Project and Certification Exam
 Real-World Project: Building a Data Warehouse Using Hive for Business Analytics
 Data Modeling, Querying, and Performance Tuning for Large Datasets
 Final Exam to Assess Your Knowledge and Skills in Hive
 Certification and Job Placement Assistance

Key Features

 Tools & Platforms: Apache Hive, Hadoop, HDFS, HiveQL, Apache Spark, Hive Metastore
 Real-World Projects: Hands-on projects in building data warehouses, querying large
datasets, and optimizing Hive queries
 Certification & Placement Support: Industry-recognized Hive certification and job
placement assistance
 Expert Instructors: Learn from experienced professionals in the field of big data and Hadoop
 Career Advancement: Build the skills necessary to become a Data Engineer, Hadoop
Developer, or Big Data Analyst

Why Choose ENCODE-IT for Comprehensive Hive?
ENCODE-IT’s Comprehensive Hive Certification Course offers in-depth training on all aspects of
Hive, from basic querying to advanced optimization techniques. With practical, real-world
applications, this course prepares you to use Hive effectively in the big data ecosystem. Whether
you're a beginner in big data or an experienced professional looking to enhance your skills, ENCODE-
IT provides the perfect platform for mastering Apache Hive. Enroll today and take your big data
career to the next level!