Shaurya Agrawal
Start-up CTO; Board Advisor at Hoonartek
Austin, Texas, United States
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Shaurya Agrawal is a Data & Analytics leader with 25+ years of experience driving transformative initiatives across Tech/SaaS, E-commerce, and FinTech. With expertise in AI/ML, Enterprise Data Architecture, and BI, he's led impactful projects, creating customer-centric solutions and modernizing data platforms. As a CTO of YourNxt Technologies, a mobile tech start-up and Board Advisor to Hoonartek, Shaurya shapes global data strategies.
Holding an MBA and pursuing an MS in Data Science from UT Austin, Shaurya leverages data to unlock business value, specializing in unified customer views and personalized experiences.
Area of Expertise
Topics
Integrating Microsoft Fabric and Databricks for Modern Data Analytics
This session will explore the strategic integration of Microsoft Fabric and Databricks to build a robust Cloud centric modern data analytics ecosystem. We will delve into how these powerful platforms complement each other, leveraging Microsoft Fabric's comprehensive suite for data integration, governance, and business intelligence with Databricks' advanced capabilities for data engineering, AI/ML, and complex analytics at scale.
Attendees will learn best practices for seamless data flow, optimizing performance, and unlocking deeper insights by combining the strengths of both environments. We will be drawing on real-world examples from FinTech and E-commerce to illustrate practical implementation strategies and benefits for enterprise data architecture.
Getting Started with Vector Search on Databricks: Building Intelligent Search Applications
Vector search is a hot topic in the AI/ML and data engineering space, especially with the rise of generative AI and semantic search. Databricks recently introduced native vector search capabilities, making it a timely for discussion
End-to-End Machine Learning Pipelines on Databricks: From Data Ingestion to Model Deployment
See the full lifecycle of ML on Databricks, including data engineering, feature engineering, model training, and deployment.
Disrupting Defaults: Smarter Credit Risk w/ Neo4j Graphs
In this lightning talk, Shaurya Agrawal will demonstrate how Neo4j’s graph database technology can revolutionize credit risk management for Financial and FinTech firms by uncovering hidden relationships between entities. Using a real-world scenario where Company A, Company B, and Company C, are subsidiaries, with varying ownership, under a common parent, you will see how traditional systems often miss these indirect connections—potentially underestimating aggregate exposure and risk. With Neo4j, you will learn how to model and visualize complex corporate hierarchies, instantly revealing cross-entity dependencies and shared liabilities.
Attendees will discover how graph queries can surface risk concentrations, identify circular ownership, and support more informed credit decisions. This session will show you how leveraging Neo4j’s relationship-first approach enables smarter, faster risk assessment—empowering you to move beyond the limitations of legacy, table-based systems.
Revolutionizing Data Governance with Databricks Lakehouse Architecture
"The Databricks lakehouse architecture represents a transformative approach to data management by seamlessly unifying the flexibility of data lakes with the reliability and performance of data warehouses. This convergence simplifies data governance by providing a single platform that supports both traditional OLAP workloads and modern AI/ML applications. Attendees will gain insights into how this architecture enables consistent data quality, robust security controls, and streamlined compliance processes, addressing the complex challenges organizations face in managing diverse data environments.
This session will also delve into best practices for implementing effective governance across the entire data lifecycle, including DataOps, MLOps, and ModelOps. By integrating governance into these operational workflows, organizations can ensure that data and models remain trustworthy, auditable, and compliant with regulatory requirements. Participants will leave equipped with practical strategies to leverage the lakehouse paradigm to drive innovation while maintaining control and transparency over their data assets."
Disrupting CDPs: Neo4j vs. the Status Quo
In this session, Shaurya Agrawal will guide you through the architecture and implementation of a modern Customer Data Platform (CDP) powered by Neo4j, the industry-leading graph DB. As organizations strive to unify and activate customer data from disparate sources, traditional relational models often fall short in capturing the complex, interconnected relationships that drive true customer understanding. This session will demonstrate how Neo4j’s flexible schema enables seamless integration of multi-channel customer data, and showcase how graph algorithms can uncover hidden patterns in customer journeys, preferences, and behaviors.
You will explore techniques for ingesting, linking, and querying customer data using Cypher, Neo4j’s powerful query language. Shaurya Agrawal will walk you through real-world use cases such as identity resolution, personalized recommendations, and advanced segmentation, illustrating how a graph-based CDP can deliver actionable insights and drive business value. By the end of the session, you will understand how to design and build a scalable CDP on Neo4j, leverage graph analytics for deeper customer intelligence. Whether you are a developer, architect, or data professional, you will leave equipped with the knowledge and resources to start your own graph-powered customer data journey.
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