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Data Analysis with Apache Hive

  • IntermediateLevel

  • 1014+Students Enrolled

  • 2 Hrs Duration

  • 4.7Average Rating

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About this Course

  • This course introduces Apache Hive, a data warehouse system built on Hadoop, enabling efficient querying of large datasets using a familiar SQL-like interface.
  • Learn to create and manage Hive databases, work with internal and external tables, and connect Hive to real-world data sources for seamless data handling.
  • Gain practical skills in writing HiveQL queries to perform data filtering, grouping, sorting, and analysis on distributed data systems.

Learning Outcomes

Hive Fundamentals

Understand Hive’s role, features, and use in Hadoop systems

Data Handling in Hive

Create, manage Hive tables and link to external data sources.

HiveQL Query Skills

Write effective HiveQL queries to analyze and process large datasets.

Who Should Enroll

  • Students keen to learn big data tools and build a strong base in SQL-like querying with Apache Hive.
  • Aspiring data analysts looking to handle large datasets using Hive in distributed systems like Hadoop.
  • BI professionals and engineers wanting efficient querying skills for big data in Hive-based environments.

Course Curriculum

Explore a comprehensive curriculum covering Python, machine learning models, deep learning techniques, and AI applications.

tools

  1. 1. What is Hive

  2. 2. Features of Hive

  3. 3. Working of Hive

  4. 4. Itversity Credentials

  1. 1. Module Overview

  2. 2. Connecting to Hive

  3. 3. Creating Database

  4. 4. Hive Data Types

  5. 5. File Encoding of Data Values

  6. 6. Creating Tables in Hive

  7. 7. Loading data in Hive Tables

  8. 8. Managed vs External Tables

  9. 9. Creating External Table

  10. 10. Creating Tables from existing tables

  11. 11. Dropping Tables

  12. 12. Altering Tables

  1. 1. Module Overview

  2. 2. Reading Records in Hive

  3. 3. Filtering Data in Hive

  4. 4. Grouping Data in Hive

  5. 5. Ordering Records in Hive

  6. 6. ORDER BY vs SORT BY

  7. 7. Distributing Data in Hive

  8. 8. Built-in Functions in Hive

Meet the instructor

Our instructor and mentors carry years of experience in data industry

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Kunal Jain

Founder & CEO, Analytics Vidhya

Kunal has 15+ years of experience in the field of Data Science and is the founder and CEO of Analytics Vidhya- the world's 2nd largest Data Science community.

Get this Course Now

With this course you’ll get

  • 2 Hours

    Duration

  • Kunal Jain

    Instructor

  • Intermediate

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Industry-Recognized Credential
  • Career Advancement Credential
  • Shareable Achievement
certificate

Frequently Asked Questions

Looking for answers to other questions?

Apache Hive is a data warehouse infrastructure built on top of Hadoop that allows users to query and manage large datasets using Hive, a SQL-like language​

In a managed table, Hive controls both the table metadata and the data itself. Dropping the table deletes the data. In an external table, Hive only manages metadata, and the data remains intact even after the table is dropped​

Hive stores metadata in a metastore and processes data using Hadoop MapReduce or Tez/Spark engines, converting HiveQL queries into corresponding execution plans.

Hive supports various file formats including TextFile, SequenceFile, ORC, Parquet, and Avro, allowing flexibility in storing and querying structured data efficiently.

Yes, you will receive a certificate of completion after successfully finishing the course and assessments.

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