Raghav Matta | Vivek Singh
Senior Solutions Architect | Senior Cloud Engineer
About
Raghav Matta is a Senior Specialist Solutions Architect at Databricks, where he helps organizations tackle complex big data challenges. With over ten years of experience across cloud data platforms, he has assisted numerous clients in deploying scalable analytics solutions. His expertise spans Azure, big data, and Apache Spark.As a Microsoft Certified Trainer for eight consecutive years, Raghav has delivered sessions at multiple conferences and meetups, sharing insights on the Azure Data Platform and artificial intelligence (AI) services.Vivek Singh is a Senior Cloud Engineer specializing in cloud architecture, platform engineering, and data solutions using Microsoft Azure and modern cloud-native technologies. He has extensive experience designing and delivering secure, scalable cloud platforms, infrastructure as code (IaC) using Terraform, Azure Kubernetes Service (AKS), GitOps, CI/CD automation, cloud governance, and AI-enabled developer platforms.A Microsoft Certified Trainer (MCT) since 2017, Vivek has delivered numerous technical workshops and conference sessions at national and international events, helping engineers and organizations adopt Azure, cloud-native architectures, DevOps, and modern data engineering practices. His work focuses on building enterprise-scale cloud platforms, enabling AI-driven developer productivity, and implementing real-time analytics and data solutions using Azure and Databricks.He is passionate about sharing practical knowledge with the community and enjoys speaking about cloud infrastructure, platform engineering, AI, and data technologies.
Talk
Raghav Matta | Vivek Singh | Sentiment Analysis using Databricks AI Functions
Sentiment Analysis, Databricks, SQL, Natural Language Processing
<p>In this talk, Raghav Matta and Vivek Singh explore a real-world scenario involving real-time social media analysis using Databricks AI Functions in SQL for enrichment powered by large language models (LLMs).</p>
<p>They begin by outlining the business problem, focusing on how organizations monitor sentiment, trends, and reactions on social media platforms.</p>
<p>Next, they walk through the solution architecture, including Azure Event Hubs, Unity Catalog, and Azure Databricks, with a focus on Databricks AI Functions in SQL, such as ai<em>analyze</em>sentiment(), ai<em>extract(), and ai</em>classify().</p>
<p>They then ingest live or simulated social media content into Databricks, apply Databricks AI Functions to analyze sentiment and topics, store the results in Delta Lake, and create visualizations using Databricks AI/BI.</p>
<p>Finally, they use a Databricks Genie Agent to ask questions about the analyzed data in natural language and derive further insights.</p>
2026-11-25
12:15
13:00