Rohit Vashishtha
Employers on the program
- 2024–2026Amazon Web Services3 talks
The year around now
Talks in the past 12 months and announced talks ahead, one row per conference, January to December. Hover a mark for the talk.
Appearances by year
- AWS re:Invent
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| Nov 30, 2026 | AWS re:Invent 2026 | AWS re:Invent | breakout | Cut your data lake and lakehouse bills: Cost and performance tuning best practices as Amazon Web Services Open data lakehouses and data lakes, built on open table formats such as Apache Iceberg, can quietly accumulate cost through uncompacted small files,…Show lessOpen data lakehouses and data lakes, built on open table formats such as Apache Iceberg, can quietly accumulate cost through uncompacted small files, over-partitioned tables, and inefficient scan patterns. | |
| Dec 1, 2025 | AWS re:Invent 2025 | AWS re:Invent | chalk talk | Bring unified analytics to your data warehouse with the lakehouse architecture as Amazon Web Services Join this interactive session to explore how to unify your data warehouse analytics with modern lakehouse capabilities, to accelerate your analytics and AI…Show lessJoin this interactive session to explore how to unify your data warehouse analytics with modern lakehouse capabilities, to accelerate your analytics and AI initiatives. | |
| Dec 2, 2024 | AWS re:Invent 2024 | AWS re:Invent | code talk | Working with UDFs in Amazon Redshift and Amazon Athena as Amazon Web Services User-defined functions (UDFs) allow you to create custom functions to process records and apply unique operations to your data. Customers frequently require…Show lessUser-defined functions (UDFs) allow you to create custom functions to process records and apply unique operations to your data. Customers frequently require extending built-in functions to add capabilities for solving complex business needs. | |
| Nov 27, 2023 | AWS re:Invent 2023 | AWS re:Invent | workshop | Connect and analyze all your data with zero-ETL approachesUnifying your data is a key first step to get to analytics and machine learning insights. But, it can be challenging to build custom data management pipelines…Show lessUnifying your data is a key first step to get to analytics and machine learning insights. But, it can be challenging to build custom data management pipelines and code to prepare your data for analytics. |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Aaron Chen | 4 | — | 2026 |
| Aaron Sempf | 4 | — | 2026 |
| Abbas Mooraj | 4 | — | 2026 |
| Abhishek Pandey | 4 | — | 2026 |
| Abhishek Sharma | 4 | — | 2026 |
| Abhishek Srivastav | 4 | — | 2026 |
| Adam Hill | 4 | — | 2026 |
| Addy Upreti | 4 | — | 2026 |
| Aditi Garg | 4 | — | 2026 |
| Aditya Challa | 4 | — | 2026 |
| Aditya Samant | 4 | — | 2026 |
| Adnan Bilwani | 4 | — | 2026 |
| Ahuva Hazan-Fuchs | 4 | — | 2026 |
| Alak Eswaradass | 4 | — | 2026 |
| Alex Goff | 4 | — | 2026 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.