move(data)2023

The data practitioner conference.

December 6th & 7th
by
DECEMBER 6 - 7
ONLINE & FREE
Thank you to everyone who attended move(data) 2023! All  records are posted under talks, click on the speaker image to watch the session

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40+
Featured speakers
5,000+
Attendees to move(data)
6hrs
Lighting talks only
CELEBRATING THE HARD WORK AND DEDICATION OF DATA ENGINEERS AND PRACTITIONERS WORLDWIDE.

Why attend move(data)?

Discover the latest tools

Learn from data experts about the tools that have transformed their work and made their teams more efficient.

Connect with fellow data engineers

Engage with 5.000+ data professionals and learn topics like delivering dashboards as code, building end-to-end data pipelines, orchestration in GCP, and more.

Enhance your data movement knowledge

Walk away with actionable insights that you can execute on to improve the way your team builds, manages and extends your existing data workflows.

Join Airbyte Slack
MOVE(DATA) 2023

Talks by industry experts

Chase Zieman

Chase Zieman

Cart.com, Chief Data Officer and Co-founder
Ken Wong

Ken Wong

Databricks, Sr. Director, Product Management
Tanya Bragin

Tanya Bragin

ClickHouse, VP of Product
Lior Gavish

Lior Gavish

Monte Carlo, Co-founder & CTO
Anna Geller

Anna Geller

Kestra, Product Lead
Sigal Shaharabani

Sigal Shaharabani

Tikal, Technical and Group Leader
Michel Tricot

Michel Tricot

Airbyte, Co-Founder & CEO
Benn Stancil

Benn Stancil

ThoughtSpot, Field CTO
Laurie Voss

Laurie Voss

LlamaIndex, VP of Developer Relations
Mehdi Ouazza

Mehdi Ouazza

MotherDuck, Developer Advocate
Pete Hunt

Pete Hunt

Dagster Labs, CEO
Bobur Umurzokov

Bobur Umurzokov

Pathway, Developer Advocate
Tejas Manohar

Tejas Manohar

Hightouch, Co-Founder & Co-CEO
Sitki Timucin

Sitki Timucin

Tydo, Head of Data and Strategy
Rick Radewagen

Rick Radewagen

Data for All. Co-creator of Dot, the data bot
All speakers
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Conference talks

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AI

Data Engineering in the AI Era

With the rapid democratization of LLMs, organizations are discovering novel applications of gen AI that data engineers need to learn to support.
AI

Pioneering the Future of Reliable Data & AI

What it takes to build more reliable data and AI systems - and give LLMs the diligence they deserve.
AI

From Unstructured to Understood: ELTP as the Foundation for Language Model Applications

The ELTP framework highlights how integrating updated, specific company data with language models like ChatGPT can overcome their limitations.
Data Engineering

Joe’s pet peeve - the knowledge and skills gap

There’s no shortage of tools in the data space, but why do we keep making the same mistakes?
Data Engineering

Data Visibility, Stability, and Control

Shares insights on enhancing e-commerce analytics through integrated yet agile data systems.
Data Engineering

One Size Can't Fit All: The Case for a Real-Time Data Warehouse

We will introduce the concept of a real-time data warehouse by describing how it addresses challenges as seen in the market today.
Data Engineering

Convert batch code into streaming with Python

You will see with examples how simple it is to make your batch code run in streaming.
Data Engineering

Less Is More: Simplifying Your Data Architecture

This talk will emphasize the importance of aligning data infrastructure with actual business needs.
Data Engineering

Standardization of Data Pipelines

There are better abstractions than black-box tasks for modeling data pipelines. In this talk, we'll explore a new paradigm: Software-Defined Assets.
AI

Semantic Layers & LLMs

He discusses the integration of semantic layers with Large Language Models, envisioning AI's enhanced understanding and interaction with organizational data.
Data Engineering

The Streaming Plane

Empowering organizations to access and analyze a broader spectrum of data types, enabling better-informed decisions in real-time and over time.
Data Engineering

You've Got (More) Mail: Making the Airbyte Weekly Digest a meaningful read in a flood of emails

In an endless sea of weekly recap emails, how can you make sure yours is worth reading?
Data Engineering

Data Silos, Be Gone!

How centralizing the data warehouse as the operational hub for companies can effectively address the challenge of data silos.
Data Engineering

Data as Code: Project Nessie brings a Git-like experience for Apache Iceberg Tables

Data-as-code paradigm, what is the open-source Project Nessie and the new patterns in data engineering it enables.
Data Engineering

PRQL: A Modern Language for Data Transformation

Highlights PRQL’s expressivity with complex analytical queries, demonstrated through interactive examples in Python.
Data Engineering

Fixing the Data Engineering Lifecycle

How emerging tools and data engineering testing capabilities can refine the transition from local development to production workflows.
Data Engineering

Keynote: Founders talk startups, data trends, what’s next in 2024

Michel and Benn offers insights into the journey of entrepreneurship, the current state and future of data strategy in businesses, and the crucial balance between innovative data solutions and practical business applications in a startup environment.
Data Engineering

Cart.com and Airbyte - A Tale of Two Hyper-growth Unicorns

Chase discusses the longstanding partnership between Cart.com and Airbyte, including being Airbyte’s Customer #1,
Data Engineering

How to Build a Database

Data warehouses are at the center of our data universes, but what’s at the center of a data warehouse?
Data Engineering

Design Principles for ELT Database Destinations

Attendees will learn about Airbyte's innovative approach to ensuring easy-to-query tables, decoupling sync errors from data errors, and enhancing overall data observability.
Data Engineering

Streaming your database - Easier said then done?

I share my experience and tips from building a system to help developers and architects prepare for the journey, surprises, and challenges along the way.
Data Engineering

Attention Is All You Need: Fine-Tune Your Way to the CEO

Boris explores the transformative role of data teams in business growth, emphasizing strategic involvement in decision-making and concise data insights to executives for impactful, growth-driven outcomes.
AI

LLMs for data engineers : Cutting Through the Hype

Recognize the vital role data engineering plays in AI.
AI

DataPilot - AI Teammate for Data Teams is Here! Accelerate dbt Development and Automate Snowflake Cost Savings!

AI tool revolutionizing data team workflows by accelerating dbt development and optimizing Snowflake costs.
AI

Use AI to Unlock Your Data with Retrieval Augmented Generation and LlamaIndex

LLMs are trained on huge volumes of data, they're not trained on *your* data and they can't answer questions about your company.
AI

Evolution of Data Lake and impact of GenAI in data industry

Starburst's data access layer and strategic approach to data management significantly enhance the performance and applicability of Generative AI and LLMs in various organizational contexts.
AI

Applying LLMs to Data Modeling

Going from synthesis in LLM-based data modeling to a deterministic system with reliable verification and repair.
AI

Text to SQL is solved. What's next?

GPT-4 is powerful enough to write correct SQL in almost any dialect, but what is missing?
AI

How organizations can harness their data in conjunction with GenAI

Brian will explore the transformation of diverse data forms into AI-ready formats, enhancing generative AI's efficacy in organizational contexts, with a focus on clean JSON data and overcoming LLM limitations.
Data Engineering

Breaking Orchestration Silos

In this talk, you’ll enter the labyrinth of orchestration silos and the speaker will show you a way out.
Data Engineering

Database Sources: Now Ready for Terabyte Data Movement

Our DB source connectors now handle massive datasets with unmatched speed and reliability
Data Engineering

Customer-Facing Analytics: Why They're More Challenging Than They Seem

What will it take to expose data in my customer-facing products?
move(data)

Keynote: Making data available and actionable to everyone, everywhere.

Airbyte's critical role in evolving data infrastructure, focusing on enhanced data movement, community-driven development, and future strategies to make every company proficient in handling and leveraging data.

Frequently Asked Questions

What is move(data) for?

Walk away with actionable insights that you can execute on to improve the way your team builds, manages and extends your existing data workflows.

How much does it cost?

Free for everyone to attend.

How do I join the slack channel?

To join the Slack channel click the link and then follow the instructions to join. Once you have joined Slack, search #movedata-conference-general-2023 to join the conversation.

Can I join as a sponsor?

We are not accepting sponsors this year. To get on the list for next year please reach out to chris.rose@airbyte.io.

Who should I contact for questions?

If you have any questions, please feel free to reach out to chris.rose@airbyte.io

Where is move(data) located?

move(data) is an online conference only...join from where you are.

Will talks be recorded?

Yes, the talks will be recorded and published on the Content Hub after each day has concluded.

Is there a code of conduct ?

The code of conduct is located here

What is the hosting platform?

Hopin will be the hosting platfrom.

Who is hosting move(data)?

move(data) is hosted by the Airbyte Community team.