Featured Posts
Introducing Census SaaS Datasets: Connect, Transform, and Activate Your SaaS Data
Get quality data faster by connecting any SaaS app to your modeling and enrichment tools
Why we chose Iceberg as the foundation for Census Store
Why Iceberg makes object storage work, and how we're making Census more efficient with Census store
Two Ways to Enrich Directly in the Warehouse
Copy our SQL to enrich data directly in your warehouse, or try it via our HTTP enrichment protocol.
4 factors that make up the best reverse ETL tool | Census
Here are the 4 key considerations for finding the best reverse ETL tool for your use case.
Marketing teams: You don't need a CDP. The future is the data warehouse. | Census
Five years ago, CDPs seemed like the best solution for marketing teams to collect customer data. Now, data-forward companies are shifting toward an alternative: Activating their data warehouse.
Analytics engineer or data engineer: Who's right for the job? | Census
Analytics engineer, data engineer... What's the difference? More importantly, who's best equipped to solve your pain points? Here's your helpful guide to hiring for each of these roles.
Build or Buy? 4 Reasons NOT to Build Your Own Reverse ETL | Census
It's not the initial development cost, but rather the ongoing time and resources maintaining the tool that will cost you. Let’s take a look at some numbers.
Why marketers should care about the data warehouse | Census
The tide is shifting away from CDPs and towards the data warehouse. And if you can’t access it, or don’t know about it, you’re missing out. Here's why.
Why you need reverse ETL right now | Census
Part 1 of our series on evaluating reverse ETL tools: Why you should invest in reverse ETL in the first place (& why you should do it right now).
Lessons from the trenches: Advice for women early in their analytics career | Census
Career paths in data are still pretty undefined, especially if you're you're one of the first data hires at your company. Check out this SCD session recap to learn some firsthand tips.
Streamline Data Processes with the Data Engineering Lifecycle | Census
Understanding the data engineering lifecycle helps every role on the team perform better and get the results they're after. Check out this SCD session recap to learn how.
Tipping points: How individual decisions make big impacts in data careers & data teams | Census
All of our careers (and the collective careers of our data teams) are the sum of critical decisions made at the right or wrong time. Drizly's data team grew 7x in just 3 years. Here's how.
Diversity in data: Modeling a better future for data teams | Census
When it comes to data, as with all other industries, diversity is crucial. Check out this SCD keynote recap to hear some steps you can take to make your data team more diverse.