Architecting Data and Machine Learning Platforms: Enable Analytics and Ai-Driven Innovation in the Cloud

This handbook is for cloud architects who want to learn how to design, build, and modernize cloud-native data and machine learning platforms using AWS, Azure, Google Cloud, or multicloud tools like Fivetran, dbt, Snowflake, and Databricks. It covers the entire data lifecycle in a cloud environment, from ingestion to activation, and shows how to transform and modernize familiar solutions like data warehouses and data lakes.

Format: Paperback / softback
Length: 300 pages
Publication date: 02 January 2024
Publisher: O'Reilly Media

All cloud architects must possess the skills necessary to create data platforms, which are essential for enabling businesses to harness data and deliver enterprise-wide intelligence in a swift and efficient manner. This comprehensive handbook is designed to guide you through the process of designing, building, and modernizing cloud-native data and machine learning platforms using AWS, Azure, Google Cloud, or multicloud tools like Fivetran, dbt, Snowflake, and Databricks. Authored by Marco Tranquillin, Valliappa Lakshmanan, and Firat Tekiner, this book covers the entire data lifecycle within a cloud environment, from ingestion to activation, utilizing real-world enterprise architectures. You will gain valuable insights into how to transform and modernize familiar solutions such as data warehouses and data lakes, while also leveraging recent AI/ML patterns to obtain accurate and timely insights that can give your business a competitive edge.

This book will empower you with the knowledge and tools to:
1. Design a modern cloud-native or hybrid data analytics and machine learning platform.
2. Accelerate data-led innovation by consolidating enterprise data in a data platform.
3. Democratize access to enterprise data and empower business teams to extract insights and build AI/ML capabilities.
4. Enable your business to make real-time decisions through streaming pipelines.
5. Transition from a descriptive analytics approach to a more predictive and prescriptive one by building an MLOps platform.
6. Enhance the efficiency of your organization in working with data analytics and machine learning in a cloud environment.

By mastering the skills outlined in this handbook, you will be well-equipped to drive digital transformation and unlock the full potential of data in your organization.

Dimension: 233 x 178 (mm)
ISBN-13: 9781098151614