Panel: Shift Left Across the Data Lifecycle—Data Contracts, Transformations, Observability, and Catalogs | Prukalpa Sankar, Tristan Handy, Barr Moses, Chad Sanderson | Shift Left Data Conference 2025

Join industry-leading CEOs Chad (Data Contracts), Tristan (Data Transformations), Barr (Data Observability), and Prukalpa (Data Catalogs) who are pioneering new approaches to operationalizing data by “Shifting Left.” This engaging panel will explore how embedding rigorous data management practices early in the data lifecycle reduces issues downstream, enhances data reliability, and empowers software engineers with clear visibility into data expectations. Attendees will gain insights into how data contracts define accountability, how effective transformations ensure data usability at scale, how proactive how proactive data and AI observability drives continuous confidence in data quality, and how catalogs enable data discoverability, accelerating innovation and trust across organizations.

Generative AI's transformative power underscores the critical need for high-quality data. In this session, Barr Moses, CEO of Monte Carlo Data, Prukalpa Sankar, Cofounder at Atlan, and George Fraser, CEO at Fivetran, discuss the nuances of scaling data quality for generative AI applications, highlighting the unique challenges and considerations that come into play. Throughout the session, they share best practices for data and AI leaders to navigate these challenges, ensuring that governance remains a focal point even amid the AI hype cycle. Links Mentioned in the Show: Rewatch Session from RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile app Empower your business with world-class data and AI skills with DataCamp for business

In the fast-paced work environments we are used to, the ability to quickly find and understand data is essential. Data professionals can often spend more time searching for data than analyzing it, which can hinder business progress. Innovations like data catalogs and automated lineage systems are transforming data management, making it easier to ensure data quality, trust, and compliance. By creating a strong metadata foundation and integrating these tools into existing workflows, organizations can enhance decision-making and operational efficiency. But how did this all come to be, who is driving better access and collaboration through data? Prukalpa Sankar is the Co-founder of Atlan. Atlan is a modern data collaboration workspace (like GitHub for engineering or Figma for design). By acting as a virtual hub for data assets ranging from tables and dashboards to models & code, Atlan enables teams to create a single source of truth for all their data assets, and collaborate across the modern data stack through deep integrations with tools like Slack, BI tools, data science tools and more. A pioneer in the space, Atlan was recognized by Gartner as a Cool Vendor in DataOps, as one of the top 3 companies globally. Prukalpa previously co-founded SocialCops, world leading data for good company (New York Times Global Visionary, World Economic Forum Tech Pioneer). SocialCops is behind landmark data projects including India’s National Data Platform and SDGs global monitoring in collaboration with the United Nations. She was awarded Economic Times Emerging Entrepreneur for the Year, Forbes 30u30, Fortune 40u40, Top 10 CNBC Young Business Women 2016, and a TED Speaker. In the episode, Richie and Prukalpa explore challenges within data discoverability, the inception of Atlan, the importance of a data catalog, personalization in data catalogs, data lineage, building data lineage, implementing data governance, human collaboration in data governance, skills for effective data governance, product design for diverse audiences, regulatory compliance, the future of data management and much more.  Links Mentioned in the Show: AtlanConnect with Prukalpa[Course] Artificial Intelligence (AI) StrategyRelated Episode: Adding AI to the Data Warehouse with Sridhar Ramaswamy, CEO at SnowflakeSign up to RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile app Empower your business with world-class data and AI skills with DataCamp for business

WARNING: This episode contains detailed discussion of data contracts. The modern data stack introduces challenges in terms of collaboration between data producers and consumers. How might we solve them to ultimately build trust in data quality? Chad Sanderson leads the data platform team at Convoy, a late-stage series-E freight technology startup. He manages everything from instrumentation and data ingestion to ETL, in addition to the metrics layer, experimentation software and ML.  Prukalpa Sankar is a co-founder of Atlan, where she develops products that enable improved collaboration between diverse users like businesses, analysts, and engineers, creating higher efficiency and agility in data projects.  For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.  The Analytics Engineering Podcast is sponsored by dbt Labs.

Summary One of the biggest obstacles to success in delivering data products is cross-team collaboration. Part of the problem is the difference in the information that each role requires to do their job and where they expect to find it. This introduces a barrier to communication that is difficult to overcome, particularly in teams that have not reached a significant level of maturity in their data journey. In this episode Prukalpa Sankar shares her experiences across multiple attempts at building a system that brings everyone onto the same page, ultimately bringing her to found Atlan. She explains how the design of the platform is informed by the needs of managing data projects for large and small teams across her previous roles, how it integrates with your existing systems, and how it can work to bring everyone onto the same page.

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! 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. RudderStack’s smart customer data pipeline is warehouse-first. It builds your customer data warehouse and your identity graph on your data warehouse, with support for Snowflake, Google BigQuery, Amazon Redshift, and more. Their SDKs and plugins make event streaming easy, and their integrations with cloud applications like Salesforce and ZenDesk help you go beyond event streaming. With RudderStack you can use all of your customer data to answer more difficult questions and then send those insights to your whole customer data stack. Sign up free at dataengineeringpodcast.com/rudder today. Your host is Tobias Macey and today I’m interviewing Prukalpa Sankar about Atlan, a modern data workspace that makes collaboration among data stakeholders easier, increasing efficiency and agility in data projects

Interview

Introduction How did you get involved in the area of data management? Can you start by giving an overview of what you are building at Atlan and some of the story behind it? Who are the target users of Atlan? What portions of the data workflow is Atlan responsible for?

What components of the data stack might Atlan replace?

How would you characterize Atlan’s position in the current data ecosystem?

What makes Atlan stand out from other systems for data cataloguing, metadata management, or data governance? What types of data assets (e.g. structured vs unstructured, textual