Indexing with Apache Pinot

In today's world of real-time analytics, optimizing data retrieval at scale is crucial. Apache Pinot, a powerful distributed OLAP data store, offers robust indexing mechanisms that significantly enhance query performance for high-throughput, low-latency use cases. In this talk, we will explore the various indexing strategies available in Apache Pinot, understand how they impact performance, and discuss best practices for selecting and implementing the right index types. Whether you're working with time-series data, real-time analytics, or high-volume workloads, mastering indexing in Apache Pinot is key to unlocking faster, more efficient data insights.
This session is perfect for data engineers, architects, and developers looking to optimize their big data systems.

About the speaker:
Barkha Herman is a technologist, experienced developer advocate, and the founder of WiTVoices and South Florida Women in Tech. With a deep understanding of technology and a love for fostering inclusive and diverse tech communities, Barkha is dedicated to empowering individuals and organizations to thrive in the rapidly evolving digital landscape.
Currently, Barkha is thriving as a Developer Advocate at [StarTree.ai](http://www.startree.ai/), where she collaborates with developers, engineers, and product teams to create innovative solutions that streamline development processes and enhance user experiences.
In addition to her work at StarTree.ai, she takes great pride in founding and leading WiTVoices and South Florida Women in Tech. These organizations are committed to empowering women in technology and creating a supportive environment for their professional growth. Through mentorship programs, networking events, and educational initiatives, they strive to break barriers and foster inclusivity in the tech industry.
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