(final Release)

The cloud promises cost savings, agility, and more. But the increasing complexity of modern IT systems often prevents businesses from realizing the outcomes they sought by moving to the cloud in the first place. At the core of this complexity is technical debt. Ad hoc decisions, traditional approaches, and "quick and dirty" solutions add up to fragile, more complex systems (and organizations)–reducing the pace of change, driving up costs, and degrading security. To succeed in the cloud, you first have to manage the problems IT complexity creates. This practical guide will help.

More organizations than ever understand the importance of data lake architectures for deriving value from their data. Building a robust, scalable, and performant data lake remains a complex proposition, however, with a buffet of tools and options that need to work together to provide a seamless end-to-end pipeline from data to insights.

Docker and Linux containers have fundamentally changed the way that organizations develop, deliver, and run software at scale. But understanding why these tools are important and how they can be successfully integrated into your organization's ecosystem can be challenging. This fully updated guide provides developers, operators, architects, and technical managers with a thorough understanding of the Docker tool set and how containers can improve almost every aspect of modern software delivery and management.

This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems all the way from loading data to training models and leveraging neural networks.

Citizen data analysts are emerging to fill in the gaps left by traditional and slow business intelligence processes. Business functions such as finance, supply chain, and sales are now leading new data/analytics initiatives rather than partnering with centralized IT or analytics teams. But there is a knowledge gap—these new "citizen data analysts" understand their area of business, but unlike their IT counterparts, they do not have a background in data processing technology.

Lead your demand planning process to excellence and deliver real value to your supply chain.

Guide machine learning projects from design to production with the techniques in this one-of-a-kind project management guide. No ML skills required

This international bestseller has been revised with new exercises, annotations, and full coverage of Scala 3.

Java developers usually tackle the complexity of software development through object-oriented programming (OOP). But not every problem is a good match for OOP. The functional programming (FP) paradigm offers you another approach to solving problems, and Java provides easy-to-grasp FP tools such as lambdas and streams. If you're interested in applying FP concepts to your Java code, this book is for you.