Cloud Data Architectures Demystified: Gain the expertise to build Cloud data solutions as per the organization’s needs

Learn using Cloud data technologies for improving data analytics and decision-making capabilities for your organization

Key Features

• Get familiar with the fundamentals of data architecture and Cloud computing.
• Design and deploy enterprise data architectures on the Cloud.
• Learn how to leverage AI/ML to gain insights from data.

Description

Cloud data architectures are a valuable tool for organizations that want to use data to make better decisions. By understanding the different components of Cloud data architectures and the benefits they offer, organizations can select the right architecture for their needs.

This book is a holistic guide for using Cloud data technologies to ingest, transform, and analyze data. It covers the entire data lifecycle, from collecting data to transforming it into actionable insights. The readers will get a comprehensive overview of Cloud data technologies and AI/ML algorithms. The readers will learn how to use these technologies and algorithms to improve decision-making, optimize operations, and identify new opportunities.

By the end of the book, you will have a comprehensive understanding of loud data architectures and the confidence to implement effective solutions that drive business success.

What you will learn

• Learn the fundamental principles of data architecture.
• Understand the working of different cloud ecosystems such as AWS, Azure & GCP.
• Explore different Snowflake data services.
• Learn how to implement data governance policies and procedures.
• Use artificial intelligence (AI) and machine learning (ML) to gain insights from data.

Who this book is for

This book is for executives, IT professionals, and data enthusiasts who want to learn more about Cloud data architectures. It does not require any prior experience, but a basic understanding of data concepts and technology landscapes will be helpful.

Table of Contents

1. Data Architectures and Patterns

2. Enterprise Data Architectures

3. Cloud Fundamentals

4. Azure Data Eco-system

5. AWS Data Services

6. Google Data Services

7. Snowflake Data Eco-system

8. Data Governance

9. Data Intelligence: AI-ML Modeling and Services