Apache Hive for Data Engineers (Hands On) with 2 Projects

The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command-line tool and JDBC driver are provided to connect users to Hive.

Do you want to unlock the full potential of big data and gain a competitive edge in today’s data-driven world? With Apache Hive, you can seamlessly turn massive datasets into actionable business insights using simple SQL-like queries—no advanced coding required. As one of the most powerful tools in the Hadoop ecosystem, Hive is the key to efficiently managing, analyzing, and optimizing large-scale data warehouses.

This course is designed to take you from a beginner to an Apache Hive expert, equipping you with the skills to harness big data for better decision-making and strategic growth. Through hands-on, real-world projects, you’ll master everything from setting up Hive environments to writing high-performance queries, building data warehouses, and generating insightful reports that can supercharge your business strategy.

One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Hive! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Apache Hive!

Built on top of Apache Hadoop, Hive provides the following features:

Tools to enable easy access to data via SQL, thus enabling data warehousing tasks such as extract/transform/load (ETL), reporting, and data analysis.
A mechanism to impose structure on a variety of data formats
Access to files stored either directly in Apache HDFS™ or in other data storage systems such as Apache HBase™
Query execution via Apache Tez™, Apache Spark™, or MapReduce
Procedural language with HPL-SQL
Sub-second query retrieval via Hive LLAP, Apache YARN and Apache Slider.

Hive provides standard SQL functionality, including many of the later SQL:2003, SQL:2011, and SQL:2016 features for analytics.
Hive's SQL can also be extended with user code via user defined functions (UDFs), user defined aggregates (UDAFs), and user defined table functions (UDTFs).

There is not a single "Hive format" in which data must be stored. Hive comes with built in connectors for comma and tab-separated values (CSV/TSV) text files, Apache Parquet™, Apache ORC™, and other formats. Users can extend Hive with connectors for other formats. Please see File Formats and Hive SerDe in the Developer Guide for details.

Hive is not designed for online transaction processing (OLTP) workloads. It is best used for traditional data warehousing tasks.

Hive is designed to maximize scalability (scale out with more machines added dynamically to the Hadoop cluster), performance, extensibility, fault-tolerance, and loose-coupling with its input formats.

We will learn

1) Apache Hive Overview

2) Apache Hive Architecture

3) Installation and Configuration

4) How a Hive query flows through the system.

5) Hive Features, Limitation and Data Model

6) Data Type, Data Definition Language, and Data Manipulation Language

7) Hive View, Partition, and Bucketing

8) Built-in Functions and Operators

9) Join in Apache Hive

10) Frequently Asked Interview Question and Answers

11) 2 Realtime Projects

My goal is to provide you with practical tools that will be beneficial for you in the future. While doing that, with a real use opportunity.

I am really excited you are here, I hope you are going to follow all the way to the end of the course. It is fairly straight forward fairly easy to follow through the course I will show you step by step each line of code & I will explain what it does and why we are doing it. So please I invite you to follow up on it to go through all the lectures. All right I will see you soon in the course.

What You'll Gain:

Data Warehousing Mastery: Learn how to use Hive to store, manage, and analyze large datasets effortlessly, transforming your business intelligence capabilities.
Scalable Data Analytics: Discover how to optimize queries and boost performance, turning raw data into strategic insights quickly and efficiently.
Real-World Projects: Apply your skills to hands-on projects, mastering the techniques needed to solve complex data challenges and drive business growth.

Who Should Enroll:

This course is perfect for:

Data Analysts & Business Intelligence Professionals looking to upskill and streamline their data analytics workflows.
Data Engineers & Developers eager to enhance their big data expertise using Apache Hive.
Tech-Savvy Entrepreneurs & Startups who want to leverage big data to refine their strategies and boost profitability.

Don't miss out on this opportunity to become an Apache Hive expert and transform the way your organization uses data. Enroll now and take your big data analytics skills to new heights!