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  • Book Overview & Buying Creating Actionable Insights Using CRM Analytics
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Creating Actionable Insights Using CRM Analytics

Creating Actionable Insights Using CRM Analytics

By : Mark Tossell
4.3 (8)
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Creating Actionable Insights Using CRM Analytics

Creating Actionable Insights Using CRM Analytics

4.3 (8)
By: Mark Tossell

Overview of this book

CRM Analytics, formerly known as Tableau CRM and Einstein Analytics, is a powerful and versatile data analytics platform that enables organizations to extract, combine, transform, and visualize their data to create valuable business insights. Creating Actionable Insights Using CRM Analytics provides a hands-on approach to CRM Analytics implementation and associated methodologies that will have you up and running and productive in no time. The book provides you with detailed explanations of essential concepts to help you to gain confidence and become competent in using the CRM Analytics platform for data extraction, combination, transformation, visualization, and action. As you make progress, you'll understand what CRM Analytics is and where it provides business value. You'll also learn how to bring your data together in CRM Analytics, build datasets and lenses for data analysis, create effective analytics dashboards for visualization and consumption by end users, and build dashboard actions that take the user from data to insight to action with ease. By the end of this book, you'll be able to solve business problems using CRM Analytics and design, build, test, and deploy analytics dashboards efficiently.
Table of Contents (19 chapters)
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1
Section 1: Getting Started with CRM Analytics
4
Section 2: Building Datasets in CRMA
10
Section 3: How to Build Awesome Analytics Dashboards in CRMA
15
Section 4: From Data To Insight To Action

Chapter 5

  • What is the difference between a lookup join, an inner join, and a full join?

The following list highlights the key differences between these joins:

  • The lookup source on the right is the User object, and the left data stream is the recipe dataset. Any user record that matches the user ID in the recipe dataset will return information relating to the user and augment it to the recipe dataset without adding any rows.
  • The inner join is used to create the intersection, or overlap, of two data sources, where only rows that match both data streams are included.
  • A full join is used when you want to include a record for every combination.
  • Give one real-world example of how to use a full join.

You want to combine products and product families and cater to every viable combination.

  • Why would you need to connect data from external sources with Salesforce objects? Give one practical example.

You want to connect order data...

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