Product News

šŸ¦ƒ Whatā€™s New in November: Sync Sequences, Prefect partnership, static list sync improvements | Census Sync

Katy Yuan
Katy Yuan November 30, 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 birds fly south in the fall? šŸ¦

Because itā€™s too far to walk.

Rounding up our new releases, integrations, and events from November!

šŸŽ‰ Product News

Census and Prefect Partnership

Officially announcing our partnership with Prefect! Together, Reverse ETL and dataflow automation make data engineering more efficient and effective.

Sync Sequences: Trigger syncs based on a successful run of another sync

For anyone trying to sync data to objects with nested dependencies, you can now pick the order you want to create or update those objects.

āœļø Content

Why marketers should care about the data warehouse

Thereā€™s a huge and important shift happening in the MarTech space that will change the way marketers do their jobs, as well as the way marketing technology is built and integrated in the long term. 

The data warehouse is emerging as the single source of truth for customer data ā€“ data that can help marketing teams do their job better and faster ā€“ if only they could access it. 

šŸ”— New Connectors

See enhancements that make it easier to sync audiences (also known as static lists) to Braze, Iterable, and Pinterest in the changelog.

ā€

šŸŽ¬ Upcoming and on-demand events

Upcoming

How to Supercharge Revenue with Powerful Customer Profiles ft. Snowplow, AWS, Prolific & Census

Tuesday Dec 6th, 10 am PT

Faced with the need for high-quality, reliable data, Prolificā€™s data team built a technology stack to create complete Customer Behavioral Profiles, ensuring the rest of their org could access actionable data to best engage with their customers.

In this hour-long panel discussion, data leaders will break down how to create a data-first culture to support and drive revenue like never before. 

ā€

On-Demand

Building a Composable CDP with Google Cloud

Off-the-shelf Customer Data Platforms haven't delivered on their promises. The Composable CDP with Google BigQuery is a better, faster way to build a future-proof marketing stack centered around your data warehouse.

Questions, concerns, feedback?

Join us on Slack in the OA Club or reach out through email. Weā€™d love to hear from you!

ā€P.S. Weā€™re hiring! Join us šŸ„³

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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, weā€™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. Weā€™re proud to offer the fastest Reverse ETL platform on the planet, and the only one capable of real-time activation with Snowflake. šŸ‘‰ Luke Ambrosetti discusses Live Sync architecture in-depth on Snowflakeā€™s Medium blog here. Real-Time Composable CDP with Snowflake Developed alongside Snowflakeā€™s product team, weā€™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 ā€” 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 weā€™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 ā€” 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. Itā€™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 ā…™ of a credit per day. ā…™ * $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 donā€™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 Snowflakeā€™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 Itā€™s easy to set up a real-time workflow with Snowflake as a source in three steps: