Architecting Data and Machine Learning Platforms : Enable Analytics and AI-Driven Innovation in the Cloud - Marco  Tranquillin

Architecting Data and Machine Learning Platforms

Enable Analytics and AI-Driven Innovation in the Cloud

By: Marco Tranquillin, Valliappa Lakshmanan, Firat Tekiner

eText | 12 October 2023 | Edition Number 1

At a Glance

eText


$71.49

or 4 interest-free payments of $17.87 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Read online on
Desktop
Tablet
Mobile

Not downloadable to your eReader or an app

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

All cloud architects need to know how to build data platforms that enable businesses to make data-driven decisions and deliver enterprise-wide intelligence in a fast and efficient way. This handbook shows you how to design, build, and modernize cloud native data and machine learning platforms using AWS, Azure, Google Cloud, and multicloud tools like Snowflake and Databricks.

Authors Marco Tranquillin, Valliappa Lakshmanan, and Firat Tekiner cover the entire data lifecycle from ingestion to activation in a cloud environment using real-world enterprise architectures. You'll learn how to transform, secure, and modernize familiar solutions like data warehouses and data lakes, and you'll be able to leverage recent AI/ML patterns to get accurate and quicker insights to drive competitive advantage.

You'll learn how to:

  • Design a modern and secure cloud native or hybrid data analytics and machine learning platform
  • Accelerate data-led innovation by consolidating enterprise data in a governed, scalable, and resilient data platform
  • Democratize access to enterprise data and govern how business teams extract insights and build AI/ML capabilities
  • Enable your business to make decisions in real time using streaming pipelines
  • Build an MLOps platform to move to a predictive and prescriptive analytics approach
Read online on
Desktop
Tablet
Mobile

More in Artificial Intelligence

AI-Powered Search - Trey Grainger

eBOOK

HBR Guide to Generative AI for Managers : HBR Guide - Elisa Farri

eBOOK

AI : The End of Human Race - Alex Wood

eBOOK