Maximizing the value of real-time data streams

Are you ready to dive into the world of enterprise streaming analytics? In today’s fast-paced digital landscape, the value of real-time data streams is becoming increasingly evident, and companies are seeking innovative ways to extract impactful business insights from these continuous flows of operational event data. In this blog post, we’ll explore how Streambased, a leading enterprise streaming analytics firm, is revolutionizing the world of advanced analytics on streaming data. Get ready to uncover the secrets behind the “streaming data lake” movement and learn how Streambased is empowering organizations to harness the power of real-time data for actionable intelligence.

Unlocking the Potential of Streaming Data with Streambased

Streambased founder and CEO, Tom Scott, is at the forefront of the enterprise streaming analytics revolution. In a recent interview at the AI & Big Data Expo, Scott shed light on how Streambased is leveraging Apache Kafka, an open-source event streaming platform, to enable advanced analytics on streaming data. While Kafka excels at transporting high-volume data streams, Streambased has addressed the need for large-scale analytics by enhancing Kafka with a proprietary acceleration technology layer. This enhancement makes the platform suitable for demanding analytics use cases, empowering data scientists and analysts to extract valuable insights from real-time data.

Empowering Business Analysts Through Frictionless Access to Real-Time Data

One of the standout features of Streambased’s approach is its focus on empowering business analysts through self-service access to granular real-time data. By leveraging existing Kafka data pipelines, Streambased ensures that its analytical capabilities have access to up-to-date, clean, and well-organized data. This level of data quality is crucial for powering critical operational systems and core business functions. The result is a seamless analytical experience that enables users to rapidly gather contextual insights without disrupting their workflow.

The Rise of the “Streaming Data Lake” Movement

Scott identified a significant trend in the industry, which Streambased refers to as the “streaming data lake” movement. This movement represents a complete convergence between data systems used for analytical purposes and those used for operational purposes. Recent enhancements such as infinite data retention in Kafka and native streaming analytics services are laying the foundation for this new paradigm. For now, Streambased remains focused on empowering business analysts through frictionless self-service access to granular real-time data, without requiring changes to existing tools and processes.


In conclusion, Streambased is leading the charge in revolutionizing enterprise streaming analytics, empowering organizations to extract actionable insights from real-time data streams. The convergence of operational and analytical data platforms is creating new opportunities for businesses to harness the power of real-time data for informed decision-making. With Streambased’s innovative approach and focus on self-service access to real-time data, the possibilities for leveraging real-time data are endless. Watch this space as Streambased continues to shape the future of enterprise streaming analytics.

Categorized as AI

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