Data plays a key role in any business, but it’s often messy, incomplete, or not optimized for analytics. Use connectors and recipes to carry out all your Salesforce data tasks.
Note: We are still tagging older content and there might be sections that are empty. In the meantime check out the Browse All page.
Connecting & integrating data
To work with data we need data available. Find and connect different data sources.
How to setup the Google Analytics legacy connector in the data manager.
Walkthrough of how to use OAuth for the Snowflake connector.
Join, enrich and enhance your data with recipes or dataflow and ready for exploration.
As we move from dataflow to recipes here's a guide on how to get used to the new tool.
Tips and tricks to working with dates in recipes including examples of most common challenges.
All you need to know about migrating dataflows to recipes using the migration tool.
Jumpstart your dataset building with templated apps build with recipes.
The transition plan of moving from dataflow to recipes.
How do you use the different sampling options when preparing your data.
Make data smarter with ML
Leverage out-of-the-box smart transformations to get even more value out of your data.
Understand in detail how Detect Sentiment works.
Create clusters with the cluster smart transform. Explore and compare key difference plus do white space analysis based on opportunities and products.
Managing data assets
Understand how to best orchestrate your flow of data, keep data performance-optimized, and maintain a clean data manager.
How best to approach the end to end data orchestration in Tableau CRM.
Taking a closer look at data sources and the landscape of data you are creating.
Taking a closer look at data sync and its importance in regards to data orchestration.
Understanding the basic concepts of working with data in Tableau CRM this part explains how an analytics developer needs to consider governance limits when designing the flow of data.
Taking a look at considerations you should have when bringing in external data followed by considerations when you are dealing with large data volume.
Exploring how to maintain data sync and taking a closer look at data prep tools (dataflow and recipe), their limits, and scheduling of data prep.
Carrying out data tasks with Data Pipelines
Use Salesforce Data Pipelines to manage different data tasks at scale natively in Salesforce.
Examples of different custom formulas used to flag if a contact record should be flagged to be looked over manually.
Want to be notified when new blogs are published? Sign up below.