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Speaker
Shirshanka Das
5
talks
My career in software engineering has led me to some incredible companies, including PayPal, Yahoo, and LinkedIn. I spent 10 years navigating the complex data challenges that came up as LinkedIn grew to become one of the most influential platforms in the world. I developed DataHub, an open-source metadata platform that helps address issues that arise when managing and leveraging data at scale. In 2021, I co-founded Acryl Data to help enterprises adopt DataHub and scale the open-source community.
Bio from: dbt Coalesce 2023
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Data contracts have been much discussed in the community of late, with a lot of curiosity around how to approach this concept in practice and how it might enable shift-left developer-first governance and data quality. For organizations adopting dbt while also dealing with non-dbt data that is upstream of the warehouse, it can be challenging to understand how to apply data contracts uniformly across a fragmented stack. We are calling this harmonizing layer the Control Plane for Data - powered by the common thread across these systems: metadata.
In this talk, Shirshanka Das, CTO of Acryl Data and founder of the DataHub Project describes how you can use data contracts and DataHub to make your dbt centered stack more reliable - as well as other use cases that can help build a simpler, more flexible data stack.
Speaker: Shirshanka Das, CTO, Acryl Data
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Data contracts have been much discussed in the community of late, with a lot of curiosity around how to approach this concept in practice. We believe data contracts need a harmonizing layer to manage data quality in a uniform manner across a fragmented stack. We are calling this harmonizing layer the Control Plane for Data - powered by the common thread across these systems: metadata. For teams already orchestrating pipelines with Airflow, data contacts can be an effective way to process data that meets preset quality standards. With a control plane as a connecting layer, producers can build data contracts that consumers can rely on, ensuring DAGs only run when a contract is valid. Producers can govern how workflows should behave, and consumers receive the tooling they need to only opt into high quality data. Learn how to use data contracts and DataHub to make your Airflow pipelines more reliable - as well as other use cases that can help build a simpler, more flexible data stack.
ABOUT THE TALK: This talk explains what the control plane of data looks like and how it fits into the reference architecture for the deconstructed data stack: a data stack that includes operational data stores, streaming systems, transformation engines, BI tools, warehouses, ML tools and orchestrators.
It dives into the fundamental characteristics for a control plane:
Breadth (completeness) Latency (freshness) Scale Source of Truth Auditability
ABOUT THE SPEAKER: Shirshanka Das is the Co-founder and CEO of Acryl Data, the company which is commercializing the open source DataHub project, a real-time metadata platform used by LinkedIn, Stripe, Pinterest, Optum, Expedia and many others. Prior to founding Acryl, he was the overall architect for Big Data at LinkedIn from 2010 to 2020, and responsible for creating the metadata and data management strategy at the company.
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Summary The binding element of all data work is the metadata graph that is generated by all of the workflows that produce the assets used by teams across the organization. The DataHub project was created as a way to bring order to the scale of LinkedIn’s data needs. It was also designed to be able to work for small scale systems that are just starting to develop in complexity. In order to support the project and make it even easier to use for organizations of every size Shirshanka Das and Swaroop Jagadish founded Acryl Data. In this episode they discuss the recent work that has been done by the community, how their work is building on top of that foundation, and how you can get started with DataHub for your own work to manage data discovery today. They also share their ambitions for the near future of adding data observability and data quality management features.
Announcements
Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. The data you’re looking for is already in your data warehouse and BI tools. Connect your warehouse to Hightouch, paste a SQL query, and use their visual mapper to specify how data should appear in your SaaS systems. No more scripts, just SQL. Supercharge your business teams with customer data using Hightouch for Reverse ETL today. Get started for free at dataengineeringpodcast.com/hightouch. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days. Datafold helps Data teams gain visibility and confidence in the quality of their analytical data through data profiling, column-level lineage and intelligent anomaly detection. Datafold also helps automate regression testing of ETL code with its Data Diff feature that instantly shows how a change in ETL or BI code affects the produced data, both on a statistical level and down to individual rows and values. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Go to dataengineeringpodcast.com/datafold today to start a 30-day trial of Datafold. Once you sign up and create an alert in Datafold for your company data, they will send you a cool water flask. Your host is Tobias Macey and today I’m interviewing Shirshanka Das and Swaroop Jagadish about Acryl Data, the company driving the open source metadata project DataHub for powering data discovery, data observability and federated data governance.
Interview
Introduction How did you get involved in the area of data management? Can you describe what Acryl Data is and the story behind it? How has your experience of building and running DataHub at LinkedIn informed your product direction for Acryl?
What are some lessons that your co-founder Swaroop has contributed from his experience at AirBnB?
The data catalog/discovery/quality market has become very active over the past year. What is your perspective on the market, and what are the gaps that are not yet bei