Not many years ago, the role of the data steward was the domain of the world’s largest organizations. When I was in college, the only person I heard of with this job title worked for one of Detroit’s Big Three automakers. Even as mainframes were supplanted by other computing paradigms, only sprawling corporations with intensive electronic data processing needs could possibly have enough information to justify a full-time staff member charged with overseeing it all.

Speed is the key to the success of our products. Instead of guessing your next step, data can navigate your path faster to complex business decisions.

Magnite, the biggest independent sell-side advertising solution, empowers publishers with their innovative monetization technology. Trusted by the world’s foremost agencies and brands, Magnite’s advertising technology provides publishers access to brand-safe, high-quality ad inventory, powering billions of advertising transactions every month. In 2021, Magnite’s revenue exceeded $416.5 million.

If you’re a 1.x user of InfluxDB, you might be a Kapacitor user as well. If so, you’re also familiar with TICKscripts, the data processing and transformation language for Kapacitor, the batch and stream processor for InfluxDB. Kapacitor is a great tool, but it’s largely a black box, so using and implementing TICKscripts to execute data processing tasks, checks, and notifications can be a challenging developer experience.

As the adtech industry continues to expand and the volume of ads sold and served grows exponentially, the only way to manage the business is through programmatic advertising. This approach utilizes data insights and algorithms to automatically serve ads to the right user, at the right time, on the right platform, and at the right price. The speed and scale of online advertising means that adtech companies need to collect, analyze, and act upon immense datasets instantaneously, 24 hours a day.

In Part 1 of this series, we started to compare the uses of Kafka and MQTT within an IoT infrastructure. It was concluded that in a basic publish-and-subscribe model of an IoT device, Kafka might simply be overkill.