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In this recipe, you learn how to use Twilio Segment and AWS Redshift ML together to generate predictive analytics without writing any code, spinning up any data pipelines, or requiring significant ML experience.

In this recipe, you’ll set up rETL to automatically pull in both backfill customer data and events from your warehouse to help complete your identity graph and provide a holistic view of your customer’s journey over an extended period of time.

Are you tired of slow and impersonal customer experiences? Our recipe has the solution, showing you how to seamlessly connect customer data from Twilio Segment with Uniform’s integration mesh. Our technique allows you to create visually stunning and high-performing customer experiences across all platforms in under 200ms. Don't let slow load times and generic experiences negatively impact your business - try our recipe today and see the difference for yourself.

The nature of iterative development cycles is that you find yourself at some point with multiple systems that need to be integrated. Maybe you built your customer database in Snowflake and your frontend applications are integrated with it, but now that your organization has grown, you’re investing in a CRM like Salesforce. You could eliminate the database and try to sync everything directly to Salesforce, but that’s probably a huge lift. You can’t just leave the systems separate, because having two sources of truth is not a good idea; you’ll introduce endless bugs and mismatches that affect your organization’s reputation and effectiveness. If your data warehouse could sync with your Salesforce, though… you’d be able to run both without the worry about divergent databases! In this recipe we’ll explore how to set up this synchronization so that your systems don’t diverge, and you don’t have extra work to keep them that way.