In the era of high-volume and high-velocity data, the faster you can process information and make decisions from it, the better. Accelerating data feedback loops gives you the agility to test many ideas, sort the good from the bad, and react to changes faster than the competition.
Getting to Real-Time
Building faster feedback loops requires ingesting large volumes of streaming data and also having tools to explore that data as it is captured. This is easier said than done, as legacy RDBMSs rely on high-latency batch loading, and NoSQL stores limit analytic functionality.
Transitioning to simultaneous data processing and analysis calls for adoption of a hybrid database model, where transactions and analytics converge in a single system. This means embracing evolving technologies like in-memory computing and distributed architectures that are optimized for rapid ingestion and exploration across large, changing datasets.
Free O’Reilly Ebook: Building Real-Time Data Pipelines
We teamed up with O’Reilly Media to bring you a complimentary ebook: Building Real-Time Data Pipelines – Unifying Applications and Analytics with In-Memory Architectures. This ebook will serve as your guide to achieving real-time business operations, providing examples of proven models, real-world use cases, and recommendations for implementation along the way.
