Rudderstack blog

Delivering ML capabilities doesn’t have to be out of reach or wildly inefficient. In this piece, we explore how RudderStack makes rapid experimentation possible for every data science team.

Data modeling for customer 360 involves unique complexities that make a SQL based approach particularly painful. A declarative approach handles these complexities for you so you can focus on using your data to drive better outcomes.

RudderStack Predictions makes it easy for you to build predictive features in Snowflake without additional MLOps and infrastructure, read our blog to learn more about the new product.

Now, you can easily send data from your Databricks lakehouse to all of your marketing and product tools with our Databricks reverse ETL source. Read the blog for more details.

The Activation API extends the customer 360 to every corner of the enterprise through the power of a real-time, RudderStack-managed API.

Braze’s data point based pricing model can cause a major pain point. Our Braze Deduplication feature solves this problem. Prevent sending duplicate data to Braze with one click and eliminate accidental overages.

With a customer 360, you can deliver every bit of relevant customer data to the right people, in the right places, at the right time to craft the connected end-to-end customer experiences that cultivate strong customer relationships.

With our Kafka Source integration, you can easily get your customer data out of Kafka, solve data quality issues, and distribute it throughout your stack to drive better business outcomes.

Creating a customer 360 doesn’t have to be a Sisyphean task. Here’s how you can use RudderStack to solve the major technical challenges at every step of the process.