Mastering Data Engineering and Analytics with Databricks : A Hands-On Guide to Build Scalable Pipelines Using Databricks, Delta Lake, and MLflow (English Edition).

Format:

Book

Author/Creator:

Kumar, Manoj.

Language:

English

Subjects (All):

Big data.

Data mining.

Physical Description:

1 online resource (331 pages)

Edition:

1st ed.

Place of Publication:

Delhi : Orange Education PVT Ltd, 2024.

Summary:

In today's data-driven world, mastering data engineering is crucial for driving innovation and delivering real business impact. Databricks is one of the most powerful platforms which unifies data, analytics and AI requirements of numerous organizations worldwide. Mastering Data Engineering and Analytics with Databricks goes beyond the basics, offering a hands-on, practical approach tailored for professionals eager to excel in the evolving landscape of data engineering and analytics. This book uniquely blends foundational knowledge with advanced applications, equipping readers with the expertise to build, optimize, and scale data pipelines that meet real-world business needs. With a focus on actionable learning, it delves into complex workflows, including real-time data processing, advanced optimization with Delta Lake, and seamless ML integration with MLflow--skills critical for today's data professionals. Drawing from real-world case studies in FMCG and CPG industries, this book not only teaches you how to implement Databricks solutions but also provides strategic insights into tackling industry-specific challenges. From setting up your environment to deploying CI/CD pipelines, you'll gain a competitive edge by mastering techniques that are directly applicable to your organization's data strategy. By the end, you'll not just understand Databricks--you'll command it, positioning yourself as a leader in the data engineering space.

Contents:

Cover Page

Title Page

Copyright Page

Dedication Page

About the Author

About the Technical Reviewers

Acknowledgements

Preface

Errata

Table of Contents

SECTION 1 Getting Started with Data Engineering and Databricks

1. Introducing Data Engineering with Databricks

Introduction

Structure

The Basics of Data Engineering

Data

Data Layers

Raw Data

Enriched Data

Curated Data

Big Data

Data Quality

Master Data/Dimensions

Transactions/Facts

Times Series Data

Data Serialization

Parquet

JavaScript Object Notation (JSON)

Comma Separated Values (CSV)

Schema Generated by AI.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

9788196862046

8196862040

OCLC:

1492932263