Product News

Census partners with Google Cloud BigQuery to make data more actionable

Katy Yuan
Katy Yuan October 11, 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.

Your data warehouse is the most complete, accurate, and trustworthy view of customer data. Unfortunately, this 360º view of your customers doesn’t extend to the operational tools that are used to engage with customers every day.

When companies centralize customer information in data warehouses like Google BigQuery, the logical next step is to make that data actionable in business tools like CRMs, marketing automation platforms, and customer success platforms.

At Census, we’ve been helping customers seamlessly connect any software or business tool to BigQuery for several years. Instead of migrating data between applications, customers access data from a single source of truth, ensuring that insights are always current, consistent, and complete. 

Census Reverse ETL makes BigQuery data actionable in downstream business tools

Reverse ETL is the last mile of the data stack

Census makes it easier than ever to scale the impact of data and analytics. Data teams can deliver trustworthy first-party data or fine-grained metrics for personalization and scoring to their stakeholders in minutes, not weeks. With reverse ETL, every team has the data they need to act and automate with confidence.

Reverse ETL is the missing piece of the data stack. It was designed to help companies leverage all the customer data in their source of truth and empower teams with real-time analytics in the tools they already use. Now, salespeople and customer success managers don’t have to look at 10 different tools to understand what their users are doing.

For more, read our blog What is reverse ETL? Here's everything you need to know.

Census achieves Google Cloud Ready – BigQuery Designation

Today, we’re excited to announce that Census has achieved Google Cloud Ready – BigQuery designation, proving that we meet a core set of functionality and interoperability requirements when integrating with BigQuery.

Operationalizing data is a priority for BigQuery users. Our mutual customers like Fivetran, Bitly, Mixpanel, Clearbit, and more use Census to sync data from BigQuery into the business tools that marketing, sales, and customer success teams use every day. 

Connecting Census to BigQuery only takes minutes, and customers benefit from automated logging, error monitoring, and alerting natively integrated with the warehouse. Also, our native integration with BI platform Looker (acquired by Google in 2019) helps users sync business logic directly into downstream apps to drive action.

Census also integrates with other tools in the Google ecosystem, such as Google Analytics, Google Sheets, Google Ads, Google Offline Conversions, and Google Cloud Storage. 

What BigQuery customers achieve with Census

Census and Salesforce

Fivetran takes Salesforce data to the next level for both sales ops and data teams

Census and Mixpanel

Mixpanel enables product-led growth with data in Mixpanel and Salesforce

Census and Facebook ads

Bleach London reduces Cost Per Acquisition by 20% by improving Facebook Ads targeting

Census and Intercom

UpKeep reduces customer churn with real-time data in Intercom

Why BigQuery customers love Census

Census is the top rated reverse ETL platform, loved by customers for top-tier support, transparent pricing, and connector reliability. Adding reverse ETL to your BigQuery stack helps you:

Empower business teams to self-serve

  • Operationalize your data and insights by getting data out of the warehouse, and into the apps your business users use daily.

Scale the impact of the data team

  • Drive more business value by powering your business workflows with BigQuery data. Spend more time modeling, and less time building and managing custom integrations. 

Multiply the ROI from your existing stack

  • Maximize the value of existing tools like dbt, Airflow and Looker. Census seamlessly plugs into your existing stack to operationalize BigQuery data at scale.

Google Cloud and Census: Better together

Together, Census and BigQuery enable data and operations teams to get every user the data they need to act and automate with confidence. Customers can keep operational metrics in sync with the central hub, quickly build scalable data pipelines without code, and bridge the gap between analysis and action.

Interested in learning more about how your team can benefit from Census and Google Cloud’s partnership to drive more actionable data? Talk to 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: