Thinking
beyond the
data stack
4.19.2023
Data Stack Summit 2023 Speakers
Jennifer Romero-Higgins
Principal Data Architect
Dr. Rajkumar J. Bhojan
AI Researcher
Vikas Ranjan
Senior Leader, Data Intelligence & Innovation
Mark Kidwell
Chief Data Architect
Bill Inmon
Founder, Chairman, CEO and Author
Sandeep Mehta
Engineering Lead, Data Platforms
Raj Joseph
Founder & CEO
Monica Kay Royal
Founder & Chief Data Enthusiast
Dr. Alexander Mikhalev
Director
Manimuthu Aayyannan
Senior Manager II, Feature Engineering
Subramanya Mulgund
Sr. Software Engineer, Feature Engineering
Sunny Zhu
ESG Data Analytics & Operations
Sangeeta Krishnan
Sr. Analytics Lead
Mike Fuller
CTO
Matthew Norton
Product Owner
Joel Hernandez
CTO
Carlos Rodríguez
Data and Analytics Manager
Carlos Costa
Data & Analytics Hub Lead & Engineering Director
Joseph Machado
Senior Data Engineer
Jess Ramos
Senior Data Analyst
Nicole Radziwill
SVP & Chief Data Scientist
Mark Mullins
Chief Data Officer
Olga Maydanchik
Head of Enterprise Data
Recent Session Announcements | Data Stack Summit 2023
From Complex to Simplicity: Our DataOps Journey
Jennifer Romero Higgins, Principal Data Architect @ American Airlines
In this presentation, Jennifer Romero-Higgins, Principal Data Architect will take a deep dive into American Airlines' DataOps journey, from the challenges we faced to the solutions we implemented.
She’ll cover how they created the “Easy” button for data and how it has helped reduce the time and effort required to onboard into the cloud and ingest data.
Jennifer will also share insight into how they have created a culture of continuous improvement and collaboration.
Modernizing the data stack - keeping it real!
Mark Mullins, Chief Data Officer @ United Community Bank
Raj Joseph, Founder & CEO @ DQLabs.ai
In a world of active metadata, semantic layer, data contracts, and modernization of data quality, sometimes it’s easy to overlook the challenges of delivering business value and jump upstream towards a vision of a modern stack.
Hear from a true data leader currently transforming his entire banking data stack and team with careful planning and making progress. This session is about keeping it real and for other leaders who want to learn how to swim in a world of hypes and buzzwords.
Turning your data lake into an asset
Bill Inmon, Founder, Chairman, CEO and Author @ Forest Rim Technology
Data architecture is constantly evolving. First there were applications. Then data warehouses. Today we have the data lake. People are discovering that the data lake quickly turns in a data swamp or data sewer. What do you need to do to turn your data lake into a productive, vibrant data lakehouse.
Maintaining price and performance SLAs across engineering teams
Mark Kidwell, Chief Data Architect @ Autodesk
Getting a data stack up and running is just one step—making sure it’s optimized is the true challenge. This session will cover how Mark and his team have developed their strategy and built a self-service analytics platform.
Ranging from the common pitfalls and approaches to how they worked with cross-functional teams, Mark will take you through the journey of truly optimizing the modern data stack for price and performance.
Building a business-critical data platform to process over £34bn in card transactions
Sandeep Mehta, Engineering Lead, Data Platforms @ Dojo
The UK payments infrastructure has remained unchanged for 20 years, resulting in a fragile and unpredictable system for processing card transactions. Sandeep will discuss their journey in building a PCI DSS compliant data platform on Kubernetes, using cloud-native technologies to address the challenges of scaling one of Europe's largest fintechs in a highly regulated industry.
His talk will cover security, auto-scaling, data observability, data transformation, schema evolution, and data governance considerations. He aims to inspire the community to build a data stack that can handle millions of transactions per day with four-nines availability, referring to it as "building a nuclear power station - it cannot fail."
NLP & ML data-driven decision making: Taming the curriculum beast
Joel Hernandez, CTO @ eLumen
Carlos Rodriguez, Data and Analytics Manager @ MentorMate
Recent advances in Natural Language Processing (NLP) and Machine Learning (ML) created unprecedented opportunities for organizations to leverage heterogeneous data scenarios. We can now draw insights from not only structured data but unstructured ones (text) as well.
eLumen partnered with MentorMate to deliver Data Engineering, NLP, and ML tools that harvest and curate course data and learning outcomes in higher education curriculum improvement. Formerly unstructured data tracked by the eLumen Insights platform now has key metadata and graph relations and can be stored in institutional data lakes that drive insights.
Joel and Carlos will share how eLumen Insights leverages graph DBs, data lake, and ML/NLP technologies to drive data curation and insights in heterogeneous unstructured data scenarios.
An ever-increasing need for data quality
Dr. Rajkumar J. Bhojan, AI Researcher @ Fidelity Investments
As the big data explosion matures even further, we're seeing how data quality is so closely linked to information quality, decision quality, and outcome quality. So, good data is more important than big data but how fast can we make good data?
Rajkumar will walk through the new, different challenges teams are facing and explore a real-time use case for data quality.
Panel: Managing cloud costs right now
Mike Fuller, CTO @ FinOps Foundation
Joseph Machado, Senior Data. Engineer @ LinkedIn
Carlos Costa, Data & Analytics Hub Lead & Engineering Director @ Adidas
Vikas Ranjan, Senior Leader, Data Intelligence & Innovation @ T-Mobile
Mike, Carlos, Vikas and Joseph join us to address cloud cost management. Together they’ll walk through:
- Challenges when it comes to controlling costs associated with managing data in the cloud
- Who on the team should be responsible for cost management
- Tools and processes they’ve implemented to ensure cost management coordination among those responsible for managing data
Out of all the ways to control costs, this panel will discuss the most valuable ways to identify cost-saving opportunities and see successful outcomes.
Self service metadata driven data loader framework
Manimuthu Aayyannan, Senior Manager II, Feature Engineering @ Walmart
Subramanya Mulgund, Sr. Software Engineer, Feature Engineering @ Walmart
Join Manimuthu and Subramanya as they share insights around personalization at Walmart via thousands of data apps that generate personalized recommendations to customers.
They'll walk through relevant challenges and approaches for solutions, high-level system architecture, metadata design connectors, orchestration, schedule optimization and telemetry.
Is synthetic data useful for data engineers?
Dr. Alexander Mikhalev, Director @ Applied Knowledge Systems
Matthew Norton, Product Owner @ Nationwide Building Society
There is a recent buzz around synthetic data but is it useful for data engineers?
In this talk, we will cover synthetic data and how it's different from anonymized (masked) data and fuzzing and give a short overview of current synthetic data vendors.
The benefits vendor's tooling brings into generating synthetic data. We will conclude the session with a demo of using open-source synthetic data generation to validate real-time streaming pipeline.
DataOps teams: Stop sprinting!
Monica Kay Royal, Founder & Chief Data Enthusiast @ Nerd Nourishment
DevOps and DataOps have a few similarities in the processes and tooling required to achieve the goals of each. So why are data teams struggling with the implementation of DataOps?
Attendees will learn what it takes for data professionals to get things done, what done really means, and why it’s not a good idea to sprint through the data lifecycle.
YARN to Kubernetes: Modernizing big data workloads on a massive scale
Vikas Ranjan, Senior Leader, Data Intelligence & Innovation @ T-Mobile
Watch this session to gain perspectives on how to optimize costs and meet cross-department SLAs by transforming a high scale, high volume distributed system, from YARN to Kubernetes.
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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