Book Image

Creating Actionable Insights Using CRM Analytics

By : Mark Tossell
Book Image

Creating Actionable Insights Using CRM Analytics

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)
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

Occasions of ambiguity

The more familiar you become with building lenses and dashboards using the CRMA GUI, the more you will understand where code is required. A best practice is to use the GUI whenever possible, and only resort to code where it cannot be avoided. Also, be sure to stay up to date with the new CRMA releases since the GUI becomes more capable with every release.

I want to share one final example of where I used code – in this case, customizing the JSON data flow to reset and refresh dates every time the data flow was run:

"relativeDates2": {
    "action": "computeExpression",
    "parameters": {
      "source": "substituteNewDate",
      "mergeWithSource": true,
      "computedFields": [
        {
  ...