The data platform reading list, autumn 2026
Snowflake and Databricks shipped six long guides between them this quarter. Here is who should read which.
TechPulse Insider Newsroom
eBook · from Databricks
As data volume and complexity increase, engineers are left figuring out how to manage, monitor and maintain fragile pipelines while also handling fragmented tools.

As data volume and complexity increase, engineers are left figuring out how to manage, monitor and maintain fragile pipelines while also handling fragmented tools.
The Big Book of Data Engineering—4th Edition equips you with cutting-edge methods for building pipelines faster and leveraging an intelligent data platform to deliver high-quality data for your AI, BI and analytics workloads.
This practical guide provides an overview of data engineering and the challenges faced today, as well as expert deep dives into:
Plus, you’ll discover how companies in Healthcare, Financial Services, Retail and Entertainment are building intelligent batch and streaming data pipelines.
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Our take
Snowflake and Databricks shipped six long guides between them this quarter. Here is who should read which.
TechPulse Insider Newsroom

The ability to share data quickly and securely, both inside and outside an organization, is mission-critical to success in the age of AI. However, traditional methods for data sharing can be cumbersome, resulting in stale, out-of-date data and delayed time to insights.

Stung by organizational bottlenecks and data governance shortfalls, companies in all industries are choosing data mesh to decentralize data management and improve data agility.

Data application developers need a data stack architecture with built-in scalability and connectivity. A cloud data platform delivers the performance and nearly infinite autoscaling needed to launch and scale applications quickly and cost-effectively.