ABOUT THE TALK: In this talk, Dan Selans shows you how we developed a schema discovery process that is able to automatically evolve schemas in a complex distributed system that is processing upwards of a 100,000 messages per second.

He dives deep into the details of schema versioning, detecting schema conflicts, compatibility and normalization, all without the use of any batching processes.

He shows how they developed a schema discovery process that is able to automatically evolve schemas in a complex distributed system that is processing upwards of a 100,000 messages per second. He also details how to detect schema drift, determine compatibility and ultimately how to do all of this, without having to involve batching.

ABOUT THE SPEAKER: Daniel Selans is the co-founder and CTO of Streamdal.com, a streaming data performance monitoring company. Dan previously wrote software at companies such as InVisionApp, New Relic and DigitalOcean and before that, spent over 10 years doing integration and R&D work at data centers.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

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ABOUT THE TALK: What are the latest trends and buzzwords in Data?

Barry McCordel welcomes panelists from Hex, DBT Labs and West Marin Data to discuss their thoughts on the latest trends and buzzwords in Data.

Learn about the latest in the world of streaming, data teams doing more with less, data meshes, innovations in different kids of SQL plus more!

ABOUT THE SPEAKERS: Julia Schottenstein is the Product Manager at dbt labs. Prior to this, she worked in Venture Capital as a Principal at NEA.

Drew Banin is the co-founder of dbt labs. He has built event collection systems that scaled to billions of events per month, implemented Markov-based marketing attribution models on millions of dollars of marketing spend, and dreams in NetworkX graphs.

Barry McCardel is the CEO and co-founder of Hex. He previously worked at TrialSpark leading operation and Palantir Technologies where he led teams at the intersection of product development and real-world impact.

Pedram Navid is the Founder of West Marin Data. In his role he helps startups implement their data stack. He also supports them with product, marketing and community-building.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: In this lightning talk, Emma Tang shares learnings from Stripe’s early efforts to tackle data correctness. As a financial technology company, data correctness is paramount to the operation of the company. This low tolerance for data inaccuracy poses unique constraints to how infrastructure is designed. Emma shares strategies as well as the trade-offs made in order to achieve this high level of correctness.

ABOUT THE SPEAKER: Emma Tang led Big Data Infrastructure at Stripe helping the company build and scale data infrastructure systems to support the 14x revenue growth and 6x headcount growth during her time there.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: Modern data stacks focus on the most common use-cases and dashboards, but what about all the ad-hoc requests that come? The current tool set fails to allow data analysts to iterate easily with stakeholders. In this talk, we will discuss that without an ad-hoc layer, data analysts are left to answer questions with hacky live SQL or have every request go through the resource-intensive and expensive production processes and workflows.

An ad-hoc layer solves this by allowing data analysts to answer data questions, change their mind, and deliver data dumps or simple analyses incredibly fast and reliably. Allowing them to prioritize putting it into production only if it needs to be reused.

ABOUT THE SPEAKER: Ahmed Elsamadisi is the founder and CEO of Narrator. Narrator enables companies to make better decisions by providing them with the ability to answer any question in under 10 minutes. Ahmed started his career building algorithms for self-driving cars and human-robot interaction. He then joined Raytheon to develop AI algorithms for missile defense, focusing on tracking and discrimination. In 2015, Ahmed joined WeWork as the first hire on their data team. He built their data engineering infrastructure and grew the team of data engineers and analysts.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/

ABOUT THE TALK: Whether consulting or working as an employee there are certain tools, patterns and practices many of us would like to disappear in the next few years. Many of them delay projects, frustrate data engineers and yet we continue to rely on them. Whether it be transferring data via SFTP or joining teams without coding standards, some companies, even those that may be considered cutting edge, still have these patterns.

In this talk Ben Rogojan explores some of these tools, patterns and practices as well as why he hopes he doesn’t see them around in a few years.

ABOUT THE SPEAKER: Ben Rogojan has spent his career focused on helping companies develop end-to-end data solutions that are simple and maintainable. He has worked in various industries such as healthcare, finance, and e-commerce. In addition, he has worked for companies including Facebook as a data engineer. Using his broad experiences he has helped companies develop, improve, modernize, and migrate their data infrastructure.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/

ABOUT THE TALK: After two years, three rounds of funding, and hundreds of new employees — Whatnot’s modern data stack has come from not existing to processing tens of millions of events across hundreds of different event types each day.

How does their small (but mighty!) team keep up? This talk explores data contracts — it covers the use of Interface Definition Language (Protobuf) to serve as the source of truth for event definitions, govern event construction in production, automatically generate DBT models in the data warehouse.

ABOUT THE SPEAKER: Zack Klein is a software engineer at Whatnot, where he thoroughly enjoys building data products and narrowly avoiding breaking production each day. Previously, he worked on big data platforms at Blackstone and HBO.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: Incident management is a key practice used by DevOps and SRE teams to keep software reliable—but it's still uncommon among data teams! Datadog says incident management can "streamline their response procedures, reducing mean time to repair (MTTR) and minimizing any impact on end users."

In this talk, Kyle Kirwan, co-founder of data observability company Bigeye, will explain the basics of incident management and how data teams can use it to reduce disruptions to analytics and machine learning applications.

ABOUT THE SPEAKER: Kyle Kirwan is the co-founder and CEO of Bigeye. He began his career as a data scientist, went on to lead the development of Uber's internal data catalog/lineage/quality tools, and now helps data teams use data observability to improve pipeline reliability and data quality.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: In this talk, we discuss cleanlab open-source (github.com/cleanlab/cleanlab) and Cleanlab Studio (https://cleanlab.ai/studio). Cleanlab open-source is a fast-growing python framework for data-centric AI that automatically detects issues in ML datasets. Cleanlab Studio is a no-code web interface used by universities and fortune 500 companies for dataset issue detection and fixing. Cleanlab algorithms have theoretical support for improved accuracy on real-world, messy data.

ABOUT THE SPEAKER: Curtis Northcutt is an American computer scientist and entrepreneur focusing on machine learning and AI to empower people. He is the CEO and co-founder of Cleanlab, an AI software company that improves machine learning model performance by automatically fixing data and label issues in real-world, messy datasets. Curtis completed his PhD at MIT where he invented Cleanlab’s algorithms for automatically finding and fixing label issues in any dataset.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: Building and curating representative datasets is crucial for accurate ML systems. Monitoring metrics post-deployment helps improve the model. Unstructured language models may face data shifts, leading to unpredictable inferences. Open-source APIs and annotation tools streamline annotation and reduce analyst workload.

This talk discusses generating datasets and real-time precision/recall splits to detect data shifts, prioritize data collection, and retrain models.

ABOUT THE SPEAKER: Ivan Aguilar is a data scientist at Teleskope focused on building scalable models for detecting PII/PHI/Secrets and other compliance related entities within customers' clouds. Prior to joining Teleskope, Ivan was a ML Engineer at Forge.AI, a Boston based shop working on information extraction, content extraction, and other NLP related tasks.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: During this talk, we'll make the argument that by aligning your product with data's core purpose, you increase adoption of your product and accelerate growth.

We'll propose a framework for Data Product Management that ensures this vital alignment is consistently held while catalyzing development and shortening time-to-outcome.

Along the way, we will show how to best structure your company's data org based on your current stage of growth in pursuit of improving the delivery of data products and enhancing outcomes for customers/end-users.

ABOUT THE SPEAKER: Ricky Saporta is passionate how people learn to make great decisions. A builder of data teams, Ricky is currently serving as SVP of Data at Entera. He spent the prior four years at The Farmer's Dog as Head of Data Strategy.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/

ABOUT THE TALK: While giving a talk to a group of up-and-coming data scientists, a question that surprised Dean Pleban was: "When you say “production”, what exactly do you mean?"

In this talk, Dean defines what production actually means. I’ll present a first-principles, step-by-step approach to thinking about deploying a model to production. He will talk about challenges you might face in each step, and provides further reading if you want to dive deeper into each one.

ABOUT THE SPEAKER: Dean Pleban has a background combining physics and computer science. He’s worked on quantum optics and communication, computer vision, software development and design. He’s currently CEO at DagsHub, where he builds products that enable data scientists to work together and get their models to production, using popular open source tools. He’s also the host of the MLOps Podcast, where he speaks with industry experts about ML in production.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: Building data tools requires us to not only think about the data team, but also about the people that the data team is serving: business users, or "non-data team people".

This talk will go over how it's super important to consider these two personas when building data tools, but it can also be a bit complicated. We will talk through a few principles we can use to build data products that are great for everyone (not just the data team!)

ABOUT THE SPEAKER: As a product manager with a background in data science, Katie Hindson loves building data products. Currently, she's working at Lightdash, an open-source BI tool that instantly turns your dbt project into a full-stack BI platform. Katie is really interested in the interaction between data teams, their tools, and the rest of the company - because the best data teams are the ones that can help everyone at the company make better decisions, faster.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/

ABOUT THE TALK: In this talk, Hamel Hussain discusses innovative approaches and tools for software development, their history, and future directions. He dives into the historical threads upon which these new approaches are built, talks about nbev, a popular open-source project that implements many of these ideas. He also shares learnings from building nbdev, along with challenges and future directions.

ABOUT THE SPEAKER: Hamel Hussain is an entreprenuer-in-residence at fast.ai, where he is building new software development tools like nbdev. Prior to fast.ai, Hamel was a machine learning engineer at companies like Airbnb, GitHub, and DataRobot, and other related roles in management consulting.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK As machine learning models are becoming more common in production, organizations are recognizing the significance of continuous validation, and are integrating automated testing into their CI/CD pipelines to ensure that their models remain relevant and are trustworthy. However, with constantly changing data and black-box logic, testing these models can be a daunting task.

In this talk, we explore the common pitfalls of ML models and best practices for testing them. We demonstrate how to use the deepchecks open source package to validate models and data during the research and CI/CD phases.

ABOUT THE SPEAKER Shir Chorev is the co-founder and CTO of Deepchecks, an MLOps startup for continuous validation of ML models and data. Previously, Shir worked at the Prime Minister’s Office and at Unit 8200, conducting and leading research in various Machine Learning and Cybersecurity related challenges.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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A vast amount of time series datasets are organized into structures with different levels or hierarchies of aggregation.

In this talk, we introduce the open-source Hierarchical Forecast library, which contains different reconciliation algorithms, preprocessed datasets, evaluation metrics, and a compiled set of statistical baseline models. This Python-based framework aims to bridge the gap between statistical modeling and Machine Learning in the time series field.

ABOUT THE SPEAKER: Max Mergenthaler is the CEO and Co-Founder of Nixtla, a time-series research and deployment startup. He is also a seasoned entrepreneur with a proven track record as the founder of multiple technology startups. With a decade of experience in the ML industry, he has extensive expertise in building and leading international data teams. Max has also made notable contributions to the Data Science field through his co-authorship of papers on forecasting algorithms and decision theory.

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ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/

ABOUT THE TALK: Data scientists build models of the real world using 1s and 0s. Model Railroaders build models of the real world using plastic and metal. In the end, they’re both models and Model Railroaders have been at it way longer than we DS have. Let’s look at parallel concepts like overfitting versus the 10 foot rule, synthetic data versus prototype freelancing, or assumptions versus modeler’s license and see what lessons from other realms of model building we can bring home to DS.

ABOUT THE SPEAKER Peter Lenz (he, him) is a Geographer and Data Scientist who combines a deep domain expertise in geoinformatics and economic geography with technical skills in programming, machine learning, NLP, among others. Peter is working to create 'Big Social Science'.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/

ABOUT THE TALK: A thoughtful discussion between AI heavyweights on what to expect in this present age of AI. The moderator will draw on their own personal experience and insight to serve up some awesome queries (#wired).

ABOUT THE SPEAKERS: Gregory Larson is the VP of Engineering at Jasper. He joined the company to build out the organization and invest in making AI a part of every creative's workflow.

In past positions Greg was the head of engineering at Divvy Pay and ObservePoint, and he led development and AI projects at Adobe, Jive/LogMeIn, and Microsoft.

Idan Gazit is a Senior Director of Research at GitHub Next, leading the Developer Experiences team. He is a hybrid designer-developer, and can usually be found geeking out about the Web, data visualization, typography, and color

Barry McCardel is the CEO and co-founder of Hex. In past positions Barry has worked at TrialSpark and Palantir Technologies.

George Mathew is the Managing Director at Insight Partners focused on venture stage investments in AI, ML, Analytics, and Data companies as they are establishing product/market Fit.

He brings 20+ years of experience developing high-growth technology startups including most recently being CEO of Kespry.

Sean Owen is the Principal Specialist for Data Science and ML at Databricks.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: The emergence of generative AI models such as GTP-3, DALL•E, and Stable Diffusion has the potential to fundamentally change knowledge and creative work. This talk highlight the ways generative AI can enhance products, accelerating workflows and unlocking creativity. It also discusses some of the technical challenges involved in building generative AI products, including prompt chaining, data privacy, learning from human and AI feedback, and AI-human interaction.

ABOUT THE SPEAKER: Tristan Zajonc is the co-founder and CEO of Continual, an ML delivery platform that provides lifecycle management for production machine learning. He was previously CTO for Machine Learning at Cloudera and co-founder of Sense, a data science platform acquired by Cloudera in 2016. He has spent over 10 years in the trenches of machine learning infrastructure and operations.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: Shiny object syndrome draws us from technology to technology, technique to technique, and we forget that analytics is fundamentally not a technical profession. It is a domain in which excellence is predicated on one's ability to translate, consult, advise the business with data-driven intelligence. The engineering world has gone too far, and lost the spirit of business intelligence.

In this talk, we talk about how we can get it back.We define what a 10x analyst looks like, and spoiler alert: your query optimization ninjitsu doesn't make the cut.

ABOUT THE SPEAKER: Robert Yi is a Co-founder and Chief Product Officer at Hyperquery, a new kind of data notebook for teams. Previously, he spent time at Airbnb and Wayfair, working across a wide range of projects in data science, product analytics, and open-source.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

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ABOUT THE TALK: In this talk, Felipe Hoffa and Daniel Myers present an honest take of their wildly different approaches to Developer Relations and how both have been critical in building Snowflake's world-class developer community and ecosystem from the ground up. Learn how they define DevRel KPIs & metrics and daily challenges they face and lessons learned along the way. You might even get inspired to become a Developer Advocate after understanding the different ways to engage with the Snowflake community and what's next for Snowflake Developer Relations.

ABOUT THE SPEAKERS: Felipe Hoffa is the Data Cloud Advocate at Snowflake. Previously he worked at Google, as a Developer Advocate on Data Analytics for BigQuery, after joining as a Software Engineer. He moved from Chile to San Francisco in 2011. His goal is to inspire developers and data scientists around the world to analyze and understand their data in ways they never could before.

Daniel Myers is in Developer Relations and previously held roles at different companies, including Google, Cisco, and Fujitsu. In addition, he led and founded multiple startups.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/