Today, organizations must do more with less. The pace of innovation has increased exponentially, yet resources remain the same (or are dwindling). Between talent shortages, long development cycles that rely on traditional programming languages, and technology teams that are already stretched perilously thin, many businesses have glaring operational problems they simply can’t solve with their current resources.
Since the introduction of stream processing, there have been three certainties in life: death, taxes, and out-of-order data. As a stream processing library built for Apache Kafka, Kafka Streams processes data in offset order. When out-of-order data is present, offset order differs from timestamp order and care must be taken to ensure that processing results respect timestamp order where appropriate.
Ever since the release of ChatGPT, which showed the potential of generative artificial intelligence (AI), enterprises have raced to operationalize generative AI within their organizations. In fact, AI represents the primary challenge for nearly every organization today. You will either be good at AI or bad at business. Appian was quick on the AI draw.
Learn the optimizations for a dbt deployment that are essential for a dependable data stack.
Atlas AI‘s geospatial artificial intelligence platform that helps organizations anticipate changing societal conditions to help them make investment decisions.
Secret management in shared environments like Continuous Integration and Delivery services is challenging. It’s essential to keep secrets secure and ensure they don’t end up in the wrong place, like logs or code repositories. Integrating solutions like 1Password into CI/CD workflows offer the advantage of centralising secret management, and it also allows you to encrypt every secret, providing controlled programmatic access to applications.
