Every business that analyzes their operational (or transactional) data needs to build a custom data pipeline involving several batch or streaming jobs to extract transactional data from relational databases, transform it, and load it into the data warehouse. In this post, we show how you can leverage Amazon Aurora zero-ETL integration with Amazon Redshift and ThoughtSpot for GenAI driven near real-time operational analytics.
Countly has many powerful features, and one of them is Hooks. You can set up custom triggers and actions, and we want to expand it even further. But for now, let’s check some simple but powerful use cases you can implement. Notifying you in Slack about new crashes happening in your app.
The Apache Flink PMC is pleased to announce the release of Apache Flink 1.18.0. As usual, we are looking at a packed release with a wide variety of improvements and new features. Overall, 174 people contributed to this release completing 18 FLIPS and 700+ issues. Thank you! Let's dive into the highlights.
We’ve all heard that data helps businesses make better decisions. The good news? This isn’t just speculation: research shows that companies who use data to drive decision making increase revenues by an average of more than 8%, are 23 times more likely to attract new customers, and are 19 times more likely to be profitable as a result.
A patient interaction turned into clinician notes in seconds, increasing patient engagement and clinical efficiency. Novel compounds designed with desired properties, accelerating drug discovery. Realistic synthetic data created at scale, expediting research in rare under-addressed disease areas.
