Advanced Analytics with PySpark: Patterns for Learning from Data at Scale Using Python and Spark

Spark: The Definitive Guide: Big Data Processing Made Simple

High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Dataclysm: Love, Sex, Race, and Identity--What Our Online Lives Tell Us about Our Offline Selves

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

Practical Lakehouse Architecture: Designing and Implementing Modern Data Platforms at Scale

Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh

Driving Data Quality with Data Contracts: A comprehensive guide to building reliable, trusted, and effective data platforms

What Is Data Science?

Google Cloud for DevOps Engineers: A practical guide to SRE and achieving Google's Professional Cloud DevOps Engineer certification

IoT and Edge Computing for Architects: Implementing edge and IoT systems from sensors to clouds with communication systems, analytics, and security, Edition 2

SQL Procedures, Triggers, and Functions on IBM DB2 for i

Platform Engineering for Architects: Crafting modern platforms as a product

Solutions Architect's Handbook: Kick-start your career with architecture design principles, strategies, and generative AI techniques, Edition 3

IBM PowerVM Virtualization Active Memory Sharing

Site Reliability Engineering: How Google Runs Production Systems

Python: Master the Art of Design Patterns

Managing Data as a Product: Design and build data-product-centered socio-technical architectures