2022 Data Stack Summit Speakers
Mark Kidwell
Chief Data Architect
Bob Muglia
Former CEO
Vikas Ranjan
Senior Leader, Data Intelligence & Innovation
Emilie Schario
Data Strategist-in-Residence
Gokul Prabagaren
Master Software Engineer
Jessica Larson
Data Engineer
Tim Meehan
Software Engineer
Nikhil Simha
Staff Software Engineer
Sunny Zhu
Director of Data & Analytics
Ali LeClerc
Community Outreach Committee Chair
Girish Baliga
Senior Engineering Manager
Sanjeev Mohan
Principal
Ash Munshi
Chairman of the Board
Arun Maniyan
Senior Solution Architect
Chad Sanderson
Head of Data
Jeffrey Tseng
Head of Autonomous Vehicles & AI Infrastructure
Andrew Machen
Senior Manager of IT Analytics
Dave Kellogg
Angel Investor & Advisor
Zarreen Naowal Reza
AI Research Scientist
Mike Mooney
Co-Founder
Brian Lu
Director of Product
Manu Bansal
Co-Founder & CEO
Esaú Reyes
Sr. Data Engineer
Vivek Joshi
Co-Founder
Margie Roginski
Head of Product
Chaitanya Patel
Software Engineer
Shekhar Gupta
Software Engineer
Claus Moldt
Former CIO
Andrew Gelinas
Co-Founder
Data Stack Summit 2022 Sessions | On-Demand
Keynote panel discussion: The building blocks of a modern data platform
Sanjeev Mohan, Data Industry Thought Leader & Principal @ SanjMo
Ash Munshi, Chairman of the Board @ Pepperdata
Claus Moldt, Former CIO @ FICO
The modern data platform is a collection of tools and capabilities that, when brought together, allow organizations to achieve the gold standard — a fundamentally data-driven organization. Join us for this panel of thought leaders for an overview of the technology, data leaders are using today, the strengths and weaknesses, and the implementation challenges in cloud and on-premises.
Morning Keynote: Data is nothing if not reliable
Manu Bansal, Co-Founder & CEO @ Lightup
From data silos to DataOps: our journey to efficiency so far
Andrew Machen, Senior Manager of IT Analytics @ American Airlines
Take a journey with Andrew Machen, Senior Manager of IT Analytics at American Airlines, as he discusses his team's journey from data silos to DataOps. He'll cover things they've done well, like talking to companies ahead of them on the curve, and things they could have done better, like knowing when to take a break from disruptors. Andrew will also share what's on the horizon for his team - leveraging self-service, API tie-ins, and enabling better notifications.
Peer-to-peer conversation: Building a modern data architecture: Presto for the open data lakehouse
Ali LeClerk, Community Outreach Committee Chair @ Presto
Tim Meehan, Software Engineer @ Meta
Girish Baliga, Senior Engineering Manager @ Uber
Today’s digital-native companies need a modern data infra that can handle data wrangling and data-driven analytics for the ever-increasing amount of data needed to drive business. Specifically, they need to address challenges like complexity, cost, and lock-in. An Open Data Lakehouse approach enables flexibility and better cost performance by leveraging open technologies and formats.
Presto is the open source SQL query engine for the Data Lakehouse, providing ad hoc and interactive queries on large amounts of data.
Join us for this fireside chat where Girish and Tim will share how Uber and Meta are leveraging Presto at scale to underpin their modern data infrastructures and why you should be using open source technologies like Presto for your Open Data Lakehouse architecture.
Trends shaping the next decade in data
Dave Kellogg, Angel Investor & Advisor @ Alation
The latest concepts in the world of data seem to arrive as quickly as the actual data we accumulate and consume — and can be just as hard to sift through, understand, and manage.
The modern data stack (MDS), data fabric, and data mesh are top of (data) mind, and this webinar will tell the tale of this trendy trio within a larger story: decentralization. How do you retain control, security, and governance — and how do people find useful, trustworthy data and information — in a decentralized utopia?
Join Dave as he explores these topics.
Peer-to-peer panel: Migrations to modern data platforms
Moderator: Sanjeev Mohan, Principal @ SanjMo
Mark Kidwell, Chief Data Architect @ Autodesk
Nikhil Simha, Staff Software Engineer @ Airbnb
Jessica Larson, Data Engineer @ Pinterest
A modern platform helps you deliver actionable insights to your business - insights that were previously unavailable or weren’t delivered in a timely manner. It can also help you to realize cost and resource efficiencies by reducing data complexity and enabling powerful self-service capabilities. A modern platform can help you go beyond reporting what happened to predict what will happen - accelerating your analytics maturity to become more forward-looking and purpose-driven. Join this panel session of experts to discuss best practices for migration to a modern data platform.
Peer-to-peer panel: Optimizing high-performance data at scale for future-forward enterprises
Moderator: Mike Mooney, Co-Founder @ Solution Monday
Esaú Reyes, Sr. Data Engineer @ Arcus Financial
Gokul Prabagaren, Master Software Engineer @ Capital One
Vikas Ranjan, Senior Leader, Data Intelligence & Innovation @ T-Mobile
How do major organizations use data and analytics to inform strategic and operational decisions? Organizations have more data than ever at their disposal. But optimizing and deriving meaningful insights from that data - converting that knowledge into action - is easier said than done.
Join us for a panel discussion with leaders from major organizations discussing the challenges and opportunities involved in adopting advanced strategies.
Fireside chat: The future of the modern data stack: Incorporating AI and SQL
Bob Muglia, Former CEO @ Snowflake
Ash Munshi, Chairman of the Board @ Pepperdata
A modern platform delivers actionable insights to the organization - insights that were previously unavailable or weren’t delivered in a timely manner.
It can also help organizations and teams realize cost and resource efficiencies by reducing data complexity and enabling powerful self-service capabilities.
These modern data platforms go beyond reporting what happened to predict what will happen — accelerating your analytics maturity to become more forward-looking and purpose-driven. Ash and Bob will discuss best practices for migration to and beyond the modern data platform.
Extending the platform to include ML and MLOps
Chad Sanderson, Head of Data @ Convoy
Mark Kidwell, Chief Data Architect @ Autodesk
Join Chad and Mark for a 1:1 peer discussion on how to extend the platform and include best practices for accelerating and scaling the deployment and management of ML and MLOps.
Architecting teams and tools for data governance
Brian Lu, Director of Product @ Rudderstack
- Organizational trust in the data
- Consistency of data across different business functions
- Discoverability and curation of relevant information
- The engineering systems to support all of those components
The path to data and analytics modernization
Vikas Ranjan, Senior Leader, Data Intelligence & Innovation @ T-Mobile
Jeffrey Tseng, Head of Autonomous Vehicles & AI Infrastructure @ NVIDIA
To really take advantage of your data, you need a modern data and analytics ecosystem that is scalable, agile, and future-ready.
Most organizations aim to be one step ahead of the competition—able to make more informed decisions about their business as well as their customers—so that they not only succeed but thrive in an everchanging business landscape. However, although many organizations have the data to do so, they often lack the technology, processes, and people to fully optimize their worth.
Join Vikas Ranjan, Data Analytics and AI Leader as he discusses the business demands and industry shifts that impact the need to modernize, as well as the benefits of and the approach to data and analytics modernization.
Optimizing data stack performance at Maisonette
Sunny Zhu, Director of Data & Analytics @ Maisonette
Sit down with Sunny as she walks through Maisonette's purpose-built
Jobs to be done by modern data teams
Emilie Schario, Data Scientist-in-Residence @ Amplify Partners
In a previous time, BI was the only interface to data and the data warehouse. Today, that's no longer true. It's allowing data teams to be more impactful to organizations than ever before. In this session, Emilie talks about the five workflows data teams are tackling and the new technology that is enabling them, as well as what this means for "self-serve analytics" in a new metric-first world.
Data warehouse or data lake, which do I choose?
Ali LeClerc, Head of Community @ Ahana
Today’s data-driven companies have a choice to make – where do we store our data? As the move to the cloud continues to be a driving factor, the choice becomes either the data warehouse (Snowflake et al) or the data lake (AWS S3 et al). There are pros and cons to each approach. While the data warehouse will give you strong data management with analytics, they don’t do well with semi-structured and unstructured data with tightly coupled storage and compute, not to mention expensive vendor lock-in. On the other hand, data lakes allow you to store all kinds of data and are extremely affordable, but they’re only meant for storage and by themselves provide no direct value to an organization.
Enter the Open Data Lakehouse, the next evolution of the data stack that gives you the openness and flexibility of the data lake with the key aspects of the data warehouse like management and transaction support.
In this talk, you’ll hear from Ali LeClerc who will discuss the data landscape and why many companies are moving to an open data lakehouse. Ali will share more perspective on how you should think about what fits best based on your use case and workloads, and how real-world teams are using Presto, a SQL query engine, to bring analytics to the data lakehouse.
Building blocks of modern data architecture
Arun Maniyan, Senior Solution Architect @ AWS
The demand for data and data-driven decision-making has picked up its pace as predicted by many. The ecosystem to generate, capture and harness the value of the data for this decision-making is also maturing at a rapid pace. Organizations are reimagining and modernizing their data landscape to meet the growing demands from different user personas. Adding to this, the variety, volume, and complexity of these data are constantly changing, making the experience of consumers say – “challenging” more frequently.
In this session, we will talk about how modern data architectures are helping organizations democratize their data. What are the driving factors that data organizations should consider when it comes to adopting or modernizing their current technology stacks? We will talk about how an eco-system of BI, data lake, purpose-built data stores, and centralized governance can help organizations navigate through the complexity of deriving insights from data.
End-to-end orchestration of machine learning models from POC to deployment
Zarreen Naowal Reza, AI Research Scientist @ Volta
Zarreen will share how she and her team have learned to overcome these challenges by adopting MLOps orchestration pipelines from the beginning and show attendees how an entire end-to-end ML orchestration pipeline can be built with minimal effort using existing open-source frameworks.
Modern strategies for data cost optimization
Chaitanya Patel, Software Engineer @ Pepperdata
Shekhar Gupta, Software Engineer @ Pepperdata
Join Pepperdata engineers Shekhar Gupta and Chai Patel for a discussion on reducing your overall cloud spend. Learn how to achieve automatic cost savings through real-world examples and best practices.
Lessons learned from solving data quality at-scale for Fortune 500 enterprises
Manu Bansal, Co-Founder & CEO @ Lightup
Vivek Joshi, Co-Founder & CEO @ Lightup
Margie Roginski, Head of Product @ Lightup
When we started Lightup 3 years ago, we had our own ideas on what we thought is required to solve data quality. Along the way, we have learned a lot in the field about the current state of data quality and bottlenecks that need to be solved. For instance, we never imagined data quality set up to be the biggest hurdle for our customers. As it turns out, friction in the end-to-end implementation of data quality checks is the number one reason why data quality initiatives fail. In this introspective session, we discuss such learnings that have significantly shaped our product to meet the needs of our enterprise customers.
Migrating to the Modern Data Stack
Joel Stewart, VP of Customer Success @ Pepperdata
A modern platform helps you deliver actionable insights to your organization — insights that were previously unavailable or weren’t delivered in a timely manner. These insights help you to overcome cost and resource inefficiencies by reducing data complexity and enabling powerful self-service capabilities.
Moving to a modern platform can also provide observability and autonomous optimization, and helps your organization move from reactive to proactive.
Join Joel Stewart, VP of Customer Success at Pepperdata for this session as he uses real-world use cases and learn the following:
- Key success factors to ensure a successful migration
- The key players in data stack modernization
- Thinking beyond traditional needs to consider architecture trends like self-service analytics that empower line-of-business professionals to perform queries and generate reports on their own
- Automation, optimization, new techniques, and tools
Where & when?
Data Stack Summit 2023 was held virtually on April 19, 2023.
What is the cost to attend the virtual sessions?
Data Stack Summit is always free and open for all to attend
What is Data Stack Summit?
Finding ways to efficiently conquer the modern data stack can become infinitely more possible when we’re able to gather together collaboratively as a community and discuss the tools and capabilities desired by future-forward organizations.
Hear real-world perspectives from long-time data visionaries, data engineers, data and cloud architects, DataOps and DevOps practitioners as they talk through topics like the building blocks of the modern data platform, open source considerations, best practices for impactful data operations, migrations, data observability, and tuning data pipelines for performance at scale.
Who comes to Data Stack Summit?
Data and cloud architects, data engineers, DevOps practitioners and managers, data and ITOps leaders
Join us for talks around things like:
- Building blocks of the modern data platform
- Implementing the modern data platform using open source
- Deploying the modern data platform using K8s
- Best practices for data team operations
- Migrations to modern data platforms
- Optimizing high-performance big data for future-forward organizations
Interested in speaking or sponsoring the next Data Stack Summit?
Please reach out to astronaut@solutionmonday.com.
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