AI & Big Data Expo: Maximizando o valor de fluxos de dados em tempo real

As digital transformation accelerates across industries, more and more companies are recognising the untapped value in their real-time data streams. Enterprise streaming analytics firm Streambased aims to help organisations extract impactful business insights from these continuous flows of operational event data.

In an interview at the recent AI & Big Data Expo, Streambased founder and CEO Tom Scott outlined the company’s approach to enabling advanced analytics on streaming data. At the foundation of Streambased’s offering is Apache Kafka, an open-source event streaming platform that has been widely adopted by Fortune 500 companies.

“Where [Kafka] falls down is in large-scale analytics,” explained Scott. While Kafka reliably transports high-volume data streams between applications and microservices, conducting complex analytical workloads directly on streaming data has historically been challenging. 

Streambased adds a proprietary acceleration technology layer on top of Kafka that makes the platform suitable for the type of demanding analytics use cases data scientists and other analysts want to perform.

Because these continuously flowing event streams power critical operational systems and core business functions, data quality must alr