Jean-Georges Perrin – författare

Concrete tools, techniques, and processes to align software architecture with your business domains, organizational design, team topologies, and corporate strategy.

Written for anyone who makes decisions about software architecture or organization design, including architects, CTOs, principal engineers, and tech leads.

In Architecture Modernization: Socio-technical alignment of software, strategy, and structure you'll learn how to:

About the technology

You can't safely separate an organization's software architecture from its business objectives, corporate strategy, or team structure. Architecture Modernization shows you how to turn the practice of designing software into a transformative process for your entire company. This unique guide reveals a collaborative holistic approach to software design that identifies the value modernization can bring to your business's domains. You'll quickly reduce ineffective dependencies and empower your teams to make fast decisions and even faster production deployments.

As data continues to grow and become more complex, organizations seek innovative solutions to manage their data effectively. Data mesh is one solution that provides a new approach to managing data in complex organizations. This practical guide offers step-by-step guidance on how to implement data mesh in your organization.

In this book, Jean-Georges Perrin and Eric Broda focus on the key components of data mesh and provide practical advice supported by code. Data engineers, architects, and analysts will explore a simple and intuitive process for identifying key data mesh components and data products. You''ll learn a consistent set of interfaces and access methods that make data products easy to consume.

This approach ensures that your data products are easily accessible and the data mesh ecosystem is easy to navigate. This book helps you:

About the authors:

Jean-Georges "JG" Perrin is a technology leader focusing on building innovative and modern data platforms.

Eric Broda is a technology executive, practitioner, and founder of a boutique consulting firm that helps global enterprises realize value from data.

As data continues to grow and become more complex, organizations seek innovative solutions to manage their data effectively. Data mesh is one solution that provides a new approach to managing data in complex organizations. This practical guide offers step-by-step guidance on how to implement data mesh in your organization.

In this book, Jean-Georges Perrin and Eric Broda focus on the key components of data mesh and provide practical advice supported by code. Data engineers, architects, and analysts will explore a simple and intuitive process for identifying key data mesh components and data products. You''ll learn a consistent set of interfaces and access methods that make data products easy to consume.

This approach ensures that your data products are easily accessible and the data mesh ecosystem is easy to navigate. This book helps you:

About the authors:

Jean-Georges "JG" Perrin is a technology leader focusing on building innovative and modern data platforms.

Eric Broda is a technology executive, practitioner, and founder of a boutique consulting firm that helps global enterprises realize value from data.

The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, Second Edition, you’ll learn to take advantage of Spark’s core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning.

Unlike many Spark books written for data scientists, Spark in Action, Second Edition is designed for data engineers and software engineers who want to master data processing using Spark without having to learn a complex new ecosystem of languages and tools. You’ll instead learn to apply your existing Java and SQL skills to take on practical, real-world challenges.

Key Features

·  Lots of examples based in the Spark Java APIs using real-life dataset and scenarios

·  Examples based on Spark v2.3 Ingestion through files, databases, and streaming

·  Building custom ingestion process

·  Querying distributed datasets with Spark SQL

For beginning to intermediate developers and data engineers comfortable programming in Java. No experience with functional programming, Scala, Spark, Hadoop, or big data is required.

About the technology

Spark is a powerful general-purpose analytics engine that can handle massive amounts of data distributed across clusters with thousands of servers. Optimized to run in memory, this impressive framework can process data up to 100x faster than most Hadoop-based systems.

Author Bio