Product News

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

Katy Yuan
Katy Yuan April 07, 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.

👋 Hey ops folks, good news!

By using Looker Looks as models in Census, you can take business logic out of dashboards and sync directly into downstream apps to drive action.

Looker, Google Cloud’s data analytics platform, enables thousands of companies to collaborate on BI dashboards, explore their organizational data, and share insights. Analytical teams use LookML, Looker’s modeling language that generates SQL for your business users, to query and model data. With a centralized data model written in LookML, operations teams can create and edit their own reports, called Looks.

All you need to do is connect Census to an existing Looker environment. You can immediately leverage business logic built in Looker and extend those trusted models to any business tool with ease. Build once, reuse everywhere.

❤️ Customer story: Spreedly iterates faster with Looker + Census

Spreedly, a Payments Orchestration Platform, helps digital businesses build best-in-market payment systems by connecting to multiple payment services.

Michael's team uses Census to sync their data warehouse to their CRM. The Looker integration makes it easy for the marketing ops team to create and edit Looks and send modeled data directly to downstream tools – without leaving Looker or relying on data team assistance.

✨ With Census and Looker, business teams can self-serve with data in the warehouse, and power operational workflows such as:

  • Hyper-personalizing sales outreach and marketing email campaigns targeted toward every stage of the customer journey, using all the data context in your warehouse
  • Using Looker’s powerful visual explorer to build audiences and sync them to all your Ad destinations (Facebook, Google, LinkedIn, TikTok, etc.) from a single place
  • Segmenting marketing audiences without SQL using Census Segments on top of approved Looker models, based on product usage or billing data

⚡️ Census + Looker: Operational Analytics for all

For BI or ops teams using Looker, Operational Analytics helps you achieve outcomes like:

  • No more wasted effort: Before, when you created business logic in Looker, your logic wasn’t used again beyond dashboards. Now, when you expose Looks to Census as models, data from the warehouse will automatically sync everywhere.
  • Inspire action, not reaction: Dashboards don’t help business users with day-to-day work like segmenting audiences or upselling customers. With Census, sync lead scores or custom audience models directly to tools like Salesforce, Braze, and Intercom.
  • Better workflow efficiency: You might send scheduled deliveries from Looker. Instead of emailing Looks to ops stakeholders or exporting and importing CSVs, skip that manual work and send data directly to the ops tool.

🪄 Build once, reuse everywhere

Census helps you get more mileage out of the modeling and analysis you already do in Looker by making it simple to sync data back into business apps for action. We compile your models on the fly whenever you schedule a sync, to keep your data and models always up to date.

You can even use Looker Blocks, out-of-the-box dashboards and insights, to speed up your modeling alongside Census. For example, pair a HubSpot marketing block with sales and product data and direct that model back into HubSpot.Business teams and data teams work better together when they can iterate quickly, and trust that their data will always be reliable. Census’s syncs keep Looker and the destination app in lockstep.

🔗 How to connect your Looker environment to Census

Requirements:

  • A connection to the same data source that powers Looker (for example, your data warehouse)
  • API Keys from your Looker account
  • Go to Models > Looker Looks > Connect Looker.
  • Enter your Looker subdomain plus API Client ID and secret key.

When you connect a Looker Look, Census uses the underlying SQL from the Look as a model.

See the Census + Looker documentation for more details.

🤝 Census + Google Cloud: Better Together

Census and Google work closely together to help mutual customers accelerate action from data with reverse ETL and Operational Analytics.

In addition to Looker, Census integrates with multiple Google products that power your business. Supercharge your entire Google stack with Census:

Check out all of our other connectors.

Try Census for free today or join our Slack community for data practitioners!

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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, 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: