Product News

New in April: Looker, Postgres, Google Analytics, Mixpanel’s PLG strategy, and G2 rewards!

Katy Yuan
Katy Yuan April 29, 2022

Katy is a Product Marketing Manager at Census who loves diving into startups, SaaS technology, and modern data platforms. When she's not working, you can find her playing pickleball or Ultimate Frisbee.

Why do eggs like April Fools’ Day?

They love practical yolks. 🍳

Dad jokes aside, we had some exciting announcements in April like using Looker Looks as models, new integrations with Google Analytics and Postgres (as a destination), and Mixpanel’s product-led growth story. Read on!

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🎉 Product Updates

👀 Census + Looker: Sync business logic in Looker to all your tools

Take business logic out of dashboards and sync directly into downstream tools to drive action with Looker Looks as models in Census. Build once, reuse everywhere!

👉 Read the blog announcement

Census + Google Analytics: Sync first-party data to custom dimensions for trustworthy revenue attribution

  • Keep marketing metrics consistent across all your tools to evaluate marketing channel effectiveness, attribute user properties to revenue, and iterate faster and run big experiments with ads.

Census + Postgres: Enrich application data with insights from the warehouse

  • Drive more relevant product interactions by syncing modeled data from the warehouse back into app databases for action and automation.

🔗 Connectors

New

Enhancements

See the changelog for improvements to Zendesk, Mailchimp, Shopify, S3 authentication alternatives, and Braze.

✨ OA in Action: How Mixpanel’s data team enabled Product-led Growth

Adam Kinney, VP of Analytics at Mixpanel, shares his team’s goals when setting up their product-led growth data strategy. His advice: Plan for a long term investment in data quality, but don’t let it prevent you from getting started. Learn more about their stack

🗓 Events

Upcoming - Register Now!

Meet our team in-person at the Snowflake Summit (Las Vegas, June 13-16) or Databricks Data & AI Summit (San Francisco, June 27-30) 🥳

See more: Census Events

Past Sessions - Click to watch on-demand

How to make the shift from DIY solutions to dedicated toolingwith Census, Brooklyn Data & Snowplow

Donny Flynn from Census, Jordan Peck from Snowplow, and Scott Breitenother from Brooklyn Data Co. discuss how to make the switch from DIY in-house tools to modern data stack solutions.

Questions, concerns, feedback?

Join us on Slack in the OA Club or reach out through email. We’d love to hear from you!P.S. We’re hiring! Join us 🥳

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Sync data 100x faster on Snowflake with Census Live Syncs
Sync data 100x faster on Snowflake with Census Live Syncs

For years, working with high-quality data in real time was an elusive goal for data teams. Two hurdles blocked real-time data activation on Snowflake from becoming a reality: Lack of low-latency data flows and transformation pipelines The compute cost of running queries at high frequency in order to provide real-time insights Today, we’re solving both of those challenges by partnering with Snowflake to support our real-time Live Syncs, which can be 100 times faster and 100 times cheaper to operate than traditional Reverse ETL. You can create a Live Sync using any Snowflake table (including Dynamic Tables) as a source, and sync data to over 200 business tools within seconds. We’re proud to offer the fastest Reverse ETL platform on the planet, and the only one capable of real-time activation with Snowflake. 👉 Luke Ambrosetti discusses Live Sync architecture in-depth on Snowflake’s Medium blog here. Real-Time Composable CDP with Snowflake Developed alongside Snowflake’s product team, we’re excited to enable the fastest-ever data activation on Snowflake. Today marks a massive paradigm shift in how quickly companies can leverage their first-party data to stay ahead of their competition. In the past, businesses had to implement their real-time use cases outside their Data Cloud by building a separate fast path, through hosted custom infrastructure and event buses, or piles of if-this-then-that no-code hacks — all with painful limitations such as lack of scalability, data silos, and low adaptability. Census Live Syncs were born to tear down the latency barrier that previously prevented companies from centralizing these integrations with all of their others. Census Live Syncs and Snowflake now combine to offer real-time CDP capabilities without having to abandon the Data Cloud. This Composable CDP approach transforms the Data Cloud infrastructure that companies already have into an engine that drives business growth and revenue, delivering huge cost savings and data-driven decisions without complex engineering. Together we’re enabling marketing and business teams to interact with customers at the moment of intent, deliver the most personalized recommendations, and update AI models with the freshest insights. Doing the Math: 100x Faster and 100x Cheaper There are two primary ways to use Census Live Syncs — through Snowflake Dynamic Tables, or directly through Snowflake Streams. Near real time: Dynamic Tables have a target lag of minimum 1 minute (as of March 2024). Real time: Live Syncs can operate off a Snowflake Stream directly to achieve true real-time activation in single-digit seconds. Using a real-world example, one of our customers was looking for real-time activation to personalize in-app content immediately. They replaced their previous hourly process with Census Live Syncs, achieving an end-to-end latency of <1 minute. They observed that Live Syncs are 144 times cheaper and 150 times faster than their previous Reverse ETL process. It’s rare to offer customers multiple orders of magnitude of improvement as part of a product release, but we did the math. Continuous Syncs (traditional Reverse ETL) Census Live Syncs Improvement Cost 24 hours = 24 Snowflake credits. 24 * $2 * 30 = $1440/month ⅙ of a credit per day. ⅙ * $2 * 30 = $10/month 144x Speed Transformation hourly job + 15 minutes for ETL = 75 minutes on average 30 seconds on average 150x Cost The previous method of lowest latency Reverse ETL, called Continuous Syncs, required a Snowflake compute platform to be live 24/7 in order to continuously detect changes. This was expensive and also wasteful for datasets that don’t change often. Assuming that one Snowflake credit is on average $2, traditional Reverse ETL costs 24 credits * $2 * 30 days = $1440 per month. Using Snowflake’s Streams to detect changes offers a huge saving in credits to detect changes, just 1/6th of a single credit in equivalent cost, lowering the cost to $10 per month. Speed Real-time activation also requires ETL and transformation workflows to be low latency. In this example, our customer needed real-time activation of an event that occurs 10 times per day. First, we reduced their ETL processing time to 1 second with our HTTP Request source. On the activation side, Live Syncs activate data with subsecond latency. 1 second HTTP Live Sync + 1 minute Dynamic Table refresh + 1 second Census Snowflake Live Sync = 1 minute end-to-end latency. This process can be even faster when using Live Syncs with a Snowflake Stream. For this customer, using Census Live Syncs on Snowflake was 144x cheaper and 150x faster than their previous Reverse ETL process How Live Syncs work It’s easy to set up a real-time workflow with Snowflake as a source in three steps: