Do you want to add more capabilities to your analytics platform? Maybe you’re a SaaS company and want to augment your offering with robust self-serve analytics to generate more customer value and revenue? Or, maybe you’re a SaaS start-up and want to build your solution with Snowflake? No matter the task, hear from developers who have achieved these goals, and more. By attending this track, you’ll also learn about the Snowflake features that enable modern SaaS analytics, and integrations with other tools and frameworks to help you innovate faster.
Enabling Developers Sessions
conDati: How I Built [and Sold] A Web-Performance Analytics-as-a-Service Company
This session is for application and company builders. Ken will share his experience developing analytics applications on Snowflake. He is currently the CEO of conDati, a marketing analytics solution using real-time ML on Snowflake. Before conDati, Ken was CEO of SOASTA (acquired by Akamai) and one of Snowflake’s early alpha customers, recognizing the unique capabilities to power the analytics stack.
Cross Screen Media: Snowflake as the Foundation for Media Planning
When you’re still finding product and market fit, you can’t afford to build infrastructure or spend time on features that don’t directly lead to discovering what customers will pay for. Learn how Cross Screen Media uses Snowflake to iterate quickly on ScreenSolve, a data-intensive media planning product for local video advertising, with a small development team and no operations support. You’ll also hear the tips and tricks learned along the way.
CTO. Cross Screen Media
GitLab: Doing DataOps the Right Way
Are you struggling to bring proper DevOps practices to your data systems? At GitLab, we’re working to bring the best of the DevOps revolution to our data team, pioneering a “DataOps” way of working. In this session, we’ll discuss how to use version control, open-source software, and Snowflake as the cornerstones of a world-class DataOps practice. By properly leveraging our DataOps processes, we have increased both the quantity and the quality of analytics at GitLab.
Senior Data Engineer, GitLab
Lacework: Building a Cloud Security and Compliance App at Scale on Snowflake
Lacework delivers a cloud security and compliance application at scale for its customers’ critical security needs. In this session, you’ll learn about how Lacework evaluated SQL vs NoSQL for its application and why it chose SQL with Snowflake. Lacework representatives will talk about why Snowflake was the right choice because of its need to deliver both speed and scale in its application. Lacework will also talk about various unique Snowflake features that made it easier to develop its platform on top of Snowflake and deliver better value to its customers.
Co-founder and CTO, Lacework
Sendgrid: Migrating to Snowflake to Free Resources and Enable Nontraditional Use CasesChoosing Snowflake for Twilio SendGrid Applications
More than 15,000 paying marketers use Sendgrid’s marketing applications to send more than 2.5 billion emails a month. Being a customer-facing application with a massive underlying data set introduces challenges and requirements that many data warehouses can’t accommodate. Sendgrid has moved from a limiting and inefficient on-premises solution to being completely cloud native with Snowflake. Find out how Sendgrid’s migration has freed teams to focus on building features, not provisioning more hardware and configuring clusters. Sendgrid achieved faster developer velocity and increased performance and capacity on a much simpler design. In this session, you’ll also learn some nontraditional use cases for Snowflake and some challenges for building a customer-facing application on a data warehouse.
Senior Principal Engineer, Sendgrid
Square: Delivering a Self-Service Data Engineering Platform on Snowflake
With Square’s acquisition of Weebly’s web hosting service, Weebly’s data engineering team migrated to Square’s data warehouse. Along the way, the Weebly team built a platform on top of Square’s warehouse to give data consumers self-service data engineering capabilities, thereby mitigating manual labor. Attend this session to hear the process and tools used—change data capture, pipeline management, and pipeline acceptance tests—to build this platform and how Snowflake’s features made the dream a reality.
Senior Data Engineer, Square
Enable modern Test/Dev with Snowflake
We know that creating and maintaining test/dev environments has many challenges: test/dev typically has a smaller subset of production databecause creating complete copies is time consuming and costly; on top of that, maintaining multiple environments is administratively challenging.
In this session, you’ll learn new ways of enabling your teams to
instantly create and manage their own test /dev environments whenever they want with no impact to other users. We will also show how your team can run identical test/dev and product environments and seamlessly switch back & forth like never before.
Sales Engineer, Snowflake
Snowflake as an Analytics Backend for Your SaaS Applications
Field CTO, Snowflake
Salesforce = Snowforce ... Cleaned Salesforce Data with Stitch and Snowflake
Brought to you by Trianz
Doing sales forecasting out of Salesforce was problematic due to manually entered data. Learn how Salesforce used a combination of Stitch, Looker, and Snowflake as its data provider to fix data inconsistencies, incorporate other data, and increase the accuracy of its sales forecasts.
Director of Analytics, Trianz
Snowflake API for Developing Analytics Applications
Are you building a SaaS app or adding analytics to an existing one? In this lab, you’ll compare various API design patterns to determine if one is better suited for analytics. You’ll develop a serverless API that leverages Snowflake as an engine for an analytics application. You’ll also learn how advanced Snowflake features such as multi-cluster warehouses and multiple caching layers enable you to build a truly scalable and performant analytics API at a fraction of the cost of legacy systems.
Senior Sales Engineer, Snowflake