| Registration & Networking | Name Tag collection |
| The Business Impact of Data & Analytics: Harnessing Intelligence in the Age of Generative AI by Saket Chaturvedi, Senior Manager at Spaulding Ridge | In today’s data-driven economy, organizations are increasingly leveraging analytics to drive strategic decisions, optimize operations, and unlock new sources of value. Understand the transformative role of data and analytics across industries, highlighting real-world applications, measurable benefits, and the challenges businesses face in implementation. and how GenAI influences the way insights are generated, consumed, and acted upon.
Key Learning:
1. Strategic Value: Data and analytics are no longer support functions—they are central to innovation, agility, and competitive differentiation.
2. Cross-Industry Impact: From healthcare to finance, analytics is reshaping how industries operate and deliver value.
3. Generative AI Integration: GenAI is accelerating insight generation, enabling natural language interfaces, and democratizing access to data.
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| Bring Your Own Lake: Unlocking the Power of Salesforce + Snowflake by Gaurav Kheterpal, CEO at Vanshiv Technologies | In this session, we’ll explore the emerging BYOL (Bring Your Own Lake) pattern: a modern data strategy where you keep your data in Snowflake, and still power CRM, analytics, and AI workflows directly from Salesforce.
Key Learning:
1) Why separating storage and compute is reshaping enterprise architecture
2) How to connect Salesforce Data Cloud with your Snowflake lakehouse
3) Real-world use cases: marketing personalization, sales insights, and GenAI
4) Tips, patterns, and gotchas for syncing, querying, and governing data across platforms |
| Enterprise Data Strategies for Analytics & Business Impact by Akshat Nag, Senior Solution Architect at Kipi.ai | Present day Challenges and complexity across cloud platforms, thinking with business and product POV for data analytics and drive business outcomes, Key pillars of data systems, some of the key modern design patterns to overcome the challenges and related industry best practices, one example Snowflake platform architecture (evangelistic) of how an end to end system may look like.
Key Learning:
1) Understand the key challenges and considerations around building modern day enterprise data systems and understand an overview of the state of the art. |
| Decoding the Data Jungle: Using AI to Build Dynamic Data Dictionaries from Complex Models by Rishabh Garg, Lead Data Engineer + Akshay Singh Thakur, AI Architect at Hakkoda | This session explores how AI can revolutionize the often-overlooked process of data dictionary creation—automating the extraction, interpretation, and presentation of metadata across complex data models. Through real-world use cases, we’ll demonstrate how AI-driven approaches can generate dynamic, consumable, and business-friendly data dictionaries that not only improve data understanding but also bridge the gap between technical teams and business users.
Key Learning:
1) Understand the Real-World Complexity
2) AI-Powered Metadata Extraction
3) From Technical to Business-Friendly
4) Impact on Collaboration and Decision Making |
| Navigating Data Careers: A Fresher's Introduction to Data Engineering & Analytics by Divyansh Saxena, Assistant Manager at KPMG | Exploring how industry freshers can get started with Data engineering and Data Analytics as Career Path.
Key Learning:
Freshers will gain clarity on the distinct yet interconnected roles of Data Engineering and Data Analytics, understanding the fundamental technical skills (Python, SQL, Cloud basics) essential for entry-level positions. |
| Networking over light lunch | |
