Dinesh Chandrasekhar

As AI continues to transform capital markets, the importance of multimodal data integration will only increase. The competitive advantage will increasingly shift to firms that can not only integrate diverse signals but do so with minimal latency and maximum accuracy.

Tomer Shiran, Co-Founder of Dremio, provides an insider’s perspective about Apache Iceberg, its emergence as a standard table format, and how AI is optimizing query performance.

Today’s data lakehouse requirements can include real-time data sources and high-performance queries to provide almost real-time insights. Learn how Kafka streams and powerful query engines can extend a lakehouse’s capabilities.

As the pace of business continues to accelerate, the need for real-time data insights has never been more pressing. Here’s why.

Cardinality, control, and costs are the three Cs of understanding and managing observability data as Krishna Yadappanavar, CEO of Kloudfuse explains with Smart Talk’s host, Dinesh Chandrasekhar, founder and principal analyst of Stratola.

Observability tools watch millions of real-time data points. Thanks to AIOps these can be turned into actionable information or real-time automation.

Observability adoption is growing fast–and the tech stacks running observability are becoming bloated. Watch our experts talk about why and what to do about it.

General-purpose databases are changing to adapt to the new AI and GenAI workloads. Take Postgres which recently gained vector database extensions.

GenAI will help organizations to finally harness their unstructured data if they redesign their data pipelines with different transformations and built-in governance.

Discover the role data-in-motion plays in enterprise GenAI and how to augment LLMs trained on historical data with fresh or even real-time data.

Watch Manish, Product Executive, and Dinesh, Industry Analyst, talk about how enterprises create value from their data-in-motion by using the power of fresh, real-time data.

The Data-in-Motion Ecosystem Map shows the various moving parts of your data architecture and how they are all connected with each other.