Behind the scenes building McLaren’s F1 stream processing system, and why the world needed a new stream processing client library.

Behind the scenes building McLaren’s F1 stream processing system, and why the world needed a new stream processing client library.
Data’s value depends on how you use it. We’ll look at three ways to increase the value you get from the data you’re already collecting.
“Dark data” is the data being collected and stored without a plan for future use. It’s often dumped into data lakes with little to no thought for how it could actually be used in the future — that’s someone else’s problem.
Twelve questions with Quix’s lead product designer and visual designer on integrating brand and product design.
The data maturity model starts with data silos and ends with automation and machine learning. Here’s how to move through the journey and overcome the challenges of each.
Our CEO summarizes Gartner’s “Market Guide for Event Stream Processing” and offers guidance to business leaders navigating the market of data tools.
Last decade, companies wrestled with big data. The new challenge is how to handle data fast. Here’s how market leaders generate more value by processing and acting on data immediately.
How to make data processing more resilient for mission-critical applications: it starts with better (and easier to manage) data pipelines.
Move over, subscription pricing. Usage-based pricing maximizes the value of a service for product-led growth, building trust and transparency in the process.
Five industry experts forecast how our approach to data will be transformed. Batch vs. stream processing? On-prem vs. cloud? Data lake or data mesh?