At Airbnb, we’ve always had a data-driven culture. We’ve assembled top-notch data science and engineering teams, built industry-leading data infrastructure, and launched numerous successful open source projects, including Apache Airflow and Apache Superset. Meanwhile, Airbnb has transitioned from a startup moving at light speed to a mature organization with thousands of employees. During this transformation, Airbnb experienced the typical growth challenges that most companies do, including those that affect the data warehouse. While we’ve shared parts (I and II) of our journey towards high quality data on our Tech Blog, this event will expand on how we’ve evolved our teams and tools to ensure trustworthy data wherever, and whenever needed at Airbnb.Â
Join us on Wednesday, July 28th at 12pm to learn more about how we’re achieving end-to-end quality data at scale.Â
As Airbnb grew from a small start-up to the company it is today, many things have changed. The company ventured into new business areas, acquired numerous companies, and significantly evolved product strategy. Meanwhile, the requirements on data have also changed.
Expectations for timeliness and correctness have increased, and focus on cost and compliance have become more central. To keep up with these new demands, Airbnb took action to retain trust in data and build an enduring culture of excellence around data quality. This talk explores this journey, highlighting the challenges the company has faced and the specific steps taken to address both technical and organization challenges.
 Two of the most critical changes that have allowed Airbnb to achieve our data strategy goals in the last two years were 1) defining a formal process for achieving end-to-end data quality, and 2) defining and establishing the Analytics Engineering (AE) role at Airbnb.
In this talk, we’ll provide a brief primer on the key steps of our data modeling and data re-architecture process (Midas). Then, we’ll cover how this process helped us recognize the need for the AE role at Airbnb, how Analytics Engineers (AEs) have enabled the full-scale re-architecture of Airbnb’s data ecosystem, and how AEs serve as force multipliers for data consumers at scale.
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At Airbnb, we lean on data to inform our critical decisions. We validate product ideas through randomized controlled experiments, and we track our business performance rigorously to ensure that we maximize values for our stakeholders. To achieve these goals, we needed to build a robust data platform that serves the internal users’ end-to-end needs.
In our recent blog posts, we have shared why we built Minerva - Airbnb's single source of truth for analytics, reporting and experimentation. In this talk we will discuss more about Minerva’s unique features which help maintain data quality across datasets and use-cases.
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The journey to high-quality data doesn’t end at the creation of high-quality data; it begins. Once high-quality data has been created, how do you get people to use it? How do you enable people to discover the new datasets and adopt them? How do you ensure that outdated datasets go away, without disrupting the business?
In this talk, we’ll dive into what happens once a high-quality dataset is born. We’ll share how we took a platform approach to driving the consumption of high-quality data at Airbnb, and describe the uniquely well-integrated platform we’ve built that facilitates the discovery of high-quality data and the shift away from outdated data. Â
Jonathan is a leader in Airbnb’s Data Engineering community and member of Airbnb’s Central Data team. In this role, Jonathan is the Tech Lead for the Midas initiative, a multi-year effort to rebuild Airbnb’s foundational data used for reporting and analytics. Jonathan is also the chair of the Data Warehouse Architecture Working Group. The group is composed of senior data engineers and is tasked with establishing Airbnb’s standards and best practices for Data Engineering.
Clark is working on establishing and growing the Analytics Engineering function within Data Science at Airbnb. He designs and implements data assets leveraged by data consumers across the company. Passionate about data democratization, Clark also collaborates with our data tooling teams to improve internal tools such as our Metrics Framework, BI / Data Viz, and Data Exploration products.
Amit is the tech lead for Minerva, Airbnb’s single source of truth metric platform. During his tenure, he led initial design and development of Minerva as it was quickly integrated with internally tooling and adopted across the company. Minerva is now a critical component of Airbnb’s next generation data warehouse serving hundreds of users and covering use-cases from ad-hoc analytics to critical financial reporting.
Sylvia has spent most of her last 10 years building and evolving data platforms, with the goal of enabling anyone to be able to harness the power of data. At Airbnb, she is the product manager for Airbnb’s Analytics Platform, where she brings her passion for design and data together to build seamless experiences for discovering and analyzing data.