Businesses often need to aggregate topics because it is essential for organizing, simplifying, and optimizing the processing of streaming data. It enables efficient analysis, facilitates modular development, and enhances the overall effectiveness of streaming applications. For example, if there are separate clusters, and there are topics with the same purpose in the different clusters, then it is useful to aggregate the content into one topic.

Automating data extraction from patient registration forms in healthcare is crucial to enhancing patient care efficiency, accuracy, and overall quality. Over 71% of surveyed clinicians in the USA agreed that the volume of patient data available to them is overwhelming. This abundance of data highlights the importance of streamlining the extraction process. Manual extraction is time-consuming and prone to errors, hindering patient safety.

Discover the role of Release Management in the DevOps landscape, a key to unlocking faster, more reliable software releases. Explore essential release practices, challenges, and the impact of DevOps on release cycles through this blog post.

Today marks a monumental milestone: Autoscaling is now in public preview and available to all our users. Don't like to wake up in the middle of the night to scale up? Do you still have nightmares of the time you forgot to scale down your cloud infrastructure? Autoscaling is the answer: we adjust infrastructure to demand dynamically. We built our autoscaling feature to be: Autoscaling is powerful and raises some questions: It was the most requested feature on our feedback platform with new regions.

When it comes to cloud data warehousing, the choice between Snowflake vs BigQuery is crucial for businesses that rely on big data analytics for decision-making. Snowflake, known for its flexibility and ease of use, contrasts with BigQuery, Google’s fully-managed, serverless data warehouse that excels in speed and scalability. Understanding the main differences between these two platforms is essential for selecting the right solution that aligns with your data strategy and operational needs.

Prior to 2022, a lot of the AI news centered on use cases like self-driving cars. Of course, use cases like these didn’t exactly apply to enterprise software. In 2023 ChatGPT showed the abilities of AI to mimic human language, but still, this only scratched the surface of AI applications for the modern enterprise. If you’ve ever asked yourself, “What is AI capable of?” then consider the following examples: How many emails do you get per day?

The class of 2027 saw a massive influx of applications at top universities across the United States. Harvard received close to 57,000 applications for the class of 2027, while MIT received almost 27,000. UC Berkeley and UCLA, meanwhile, received 125,874 and 145,882 respectively. Manual transcript processing is an uphill battle for educational institutions at every level.

This blog explores the strategies and tools provided by App Store Connect and Google Play for managing mobile app releases, focusing on minimizing the impact of faulty releases through phased rollouts and staged releases.

Introduced in 2023, SwiftData is the latest addition to the range of database framework options in Swift, Apple’s primary programming language for iOS. Built on top of Core Data, two levels above SQLite, it’s great for simplifying our persistent stores and it allows us to use declarative code, which is a really useful time-saver.