Real-time data insights help identify performance bottlenecks, manage data efficiently, and drive innovation. Despite the growing need for these capabilities, organisations often face challenges in implementing effective real-time analytics.
Achieving high-concurrency data processing is crucial for overcoming performance bottlenecks in real-time analytics. Embracing real-time analytics is not just a necessity, but a way to transform your data into actionable insights, optimise performance, and fuel business growth.
Yellowbrick is a modern data platform built on Kubernetes for enterprise data warehousing, ad-hoc and streaming analytics, AI and BI workloads that ensures comprehensive data security, unparalleled flexibility, and high performance.
In this podcast, Doug Laney, a Data Strategy Innovation Fellow with West Monroe, speaks to Mark Cusack, the CTO of Yellowbrick, about the power of real-time analytics.
Key Takeaways:
- Real-time analytics enables faster business decisions based on up-to-date data and focuses on enabling actions.
- Using a SQL data platform like Yellowbrick, designed for high-concurrency data processing, can address performance bottlenecks in real-time analytics.
Chapters:
00:00 - Introduction and Overview
01:07 - The Benefits of Real-Time Analytics
06:23 - Overcoming Challenges in Implementing Real-Time Analytics
06:51 - High Concurrency Data Processing for Real-Time Analytics
13:59 - Yellowbrick: A Secure and Efficient SQL Data Platform
