Learn challenges of financial transaction systems and implement robust mechanisms to handle concurrency effectively to ensure system integrity and reliability.
See an example of an antipattern that can lead to difficulties in maintaining and testing code and approaches that allow you to structure your work in a preventative way.
Following our look into the enhancement of data in an org, explore Data Subject Access Rights (DSAR) and their correlation to individual rights in real-time.
Install and configure the latest version of Apache Kafka on a single-node cluster running on Ubuntu-22.04, and subsequently integrate it with RisingWave.
Take a deep dive into the architectural concepts of data pipelines along with a hands-on tutorial for implementation, demonstrating the concepts in action.
The techniques we use for dealing with bad data in event streams differ from those in the batch world. Here, learn more about overcoming bad data in streaming.
Explore the differences and strengths of PolyBase and Snowflake external tables to optimize data querying strategies and achieve efficient data integration.
Cover specific characteristics related to DynamoDB migrations and strategies employed to integrate with and migrate data seamlessly to other databases.
Learn the differences between batch and real-time data processing, and explore the decision-making factors for choosing the right approach to optimize data pipelines.
Learn more about Apache Flink, a powerful stream processing tool, for building streaming data pipelines, real-time analytics, and event-driven applications.
Retrieval augmented generation (RAG) needs the right data architecture to scale efficiently. Learn how data streaming helps data and application teams innovate.
AI and LLMs streamline user story creation, optimize backlog, and predict trends, improving agile product development speed, relevance, and user engagement.