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Yearly Archives: 2022

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Dec 4, 2022
Importing a dataset – Blending Tableau with Traditional CRM Analytics

Importing a dataset

CRM Analytics can work with many different kinds of data, both internal to the Salesforce platform and external, such as in a Snowflake data warehouse. To keep things simple, we will simply get our data from a CSV file. Start by downloading the file: https://developer.salesforce.com/files/opportunity_history.csv. This file is used for several Salesforce tutorials, and we will make use of it as well, for instance: https://trailhead.salesforce.com/content/learn/modules/einstein-discovery-basics/build-your-crm-analytics-dataset.

Our next step is, therefore to import the data from the CSV file into a CRM Analytics dataset, which can be done using the following steps:

  1. On the Analytics Studio home tab, click Create, select Dataset, and then choose CSV File, as shown in Figure 8.5:

Figure 8.5: Dataset creation menu showing CSV file option

  1. In the file-selection window that opens, locate the CSV file you downloaded, opportunity_history.csv, select it and then click Next. You can see this in the following screenshot:

Figure 8.6: File selection dialogue

  1. In the Dataset Name field, you can change the default name (opportunity_history), as shown below. By default, Analytics Studio uses the file name as the dataset name, which cannot exceed 80 characters as shown in the following figure:

Figure 8.7: Dataset name field

  1. Choose the app where you want to create the dataset. By default, Analytics Studio selects My Test App.
  2. Click Next. The Edit Field Attributes screen appears, shown in Figure 8.8, where you can preview the data and view or edit the attributes for each field.

Figure 8.8: Edit field attributes screen

  1. For now, accept the defaults and click Upload File. Analytics Studio uploads the data, prepares, and creates the dataset while showing progress as it occurs. You can see this in the following screenshot:

Figure 8.9: File upload progress
Once finished, you will see details about the dataset you created. If you do not see the dataset details, check your Datasets or search for opportunity_history in Analytics Studio.

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Nov 8, 2022
Creating an analytics app – Blending Tableau with Traditional CRM Analytics

A CRM Analytics app is a comprehensive collection of analyses, data exploration paths, and powerful tools designed for in-depth, real-time data examination. CRM Analytics relies on apps to organize data projects, run presentations directly from dashboards, and manage asset sharing.
To get started with creating an app in your CRM Analytics-enabled Developer Edition org, follow these steps:

  1. Open your CRMA Developer Edition org.
  2. Access the App Launcher and search for Analytics Studio. Select it to open Analytics Studio in a new tab. Keep both tabs open, as you will need to work on the original tab later in the project. This is shown in the following screenshot:

Figure 8.1: App Launcher showing Analytics Studio

  1. In Analytics Studio, click the Create button and select App from the dropdown menu, as shown below:

Figure 8.2: Create menu dropdown showing App option

  1. Choose Create Blank App to start with a clean slate, as shown in the following screenshot:

Figure 8.3: Blank App creation dialogue

  1. Click Continue to proceed to the next step. Enter My Test App as the name of your new app, as shown below:

Figure 8.4: My Test App creation dialogue

  1. Click Create to finalize the app creation process.
    Congratulations! You have successfully created an app in CRM Analytics. We will now move on to importing a dataset.
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Oct 16, 2022
Creating Datasets, Lenses, and Dashboards in CRM Analytics – Blending Tableau with Traditional CRM Analytics

In CRM Analytics, the most basic concepts are app, dataset, lens, and dashboard. These are the basic building blocks to understand to be able to work in the system, although, of course, they are just the beginning.

Before we dive into the practical steps of creating a dashboard in CRM Analytics, let’s briefly familiarize ourselves with the fundamental concepts of app, dataset, lens, and dashboard. Understanding these components is crucial as they form the backbone of CRM Analytics.

  • App: In CRM Analytics, an app serves as a container for your analytical projects. It’s a workspace where you can organize your datasets, lenses, and dashboards. Think of it as a folder on your computer where you keep related files together for easy access and organization.
  • Dataset: A dataset is a collection of data that CRM Analytics can process. This data can come from various sources, including Salesforce records, external databases, or files like CSVs. Datasets are the raw materials from which you extract insights.
  • Lens: A lens is a tool for exploring a dataset. It allows you to visualize data in different formats (such as charts or tables), filter the data to focus on specific aspects, and perform basic analyses. You can think of a lens as a magnifying glass that helps you examine the details of your dataset.
  • Dashboard: A dashboard is a visual representation of your data analyses, often comprising multiple widgets (charts, tables, etc.) that display data from one or more datasets. Dashboards are designed to provide at-a-glance insights and support decision-making.

Now that we have a basic understanding of these concepts, let’s proceed to create a simple dashboard in CRM Analytics to give you a feel for what you might be able to achieve if you were to dig deeper into the topic.

We will do this in a few steps:

  1. Create an app to hold your unique analytical assets.
  2. Import a dataset into the system.
  3. Explore this dataset through a lens.
  4. Build a simple dashboard to visualize the data.

Doing this will also teach you some of the key differences between creating dashboards in Tableau and doing so in CRM Analytics and why you might prefer one over the other in particular cases.

Let us begin!

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Aug 7, 2022
Conclusion-Integration, Authentication, and Tableau Viz LWC

It is important to note that Tableau-connected apps and Salesforce-connected apps are different and offer distinct functionalities. Currently, Tableau connected apps are intended for embedding Tableau views and metrics in external applications and authorizing access to the Tableau REST API.

Generally, you should not use a Connected App with Salesforce. The one exception might be if you are planning to use the same app across several target systems that need to embed information from Tableau and should be managed in a consistent way. You would just be creating more trouble for yourself.

Finally, there is the option of embedding Tableau Dashboard as a canvas app using the Sparkler framework. This used to be the preferred way of embedding Tableau Dashboards into Salesforce, but it has now been superseded by the Tableau Viz LWC Component. The setup for this option is very complex. It involves a Java-based application, Sparkler, which can be used to embed Tableau dashboards in Salesforce using Salesforce’s canvas framework.

To set up Sparkler, you must download the adapter, create a virtual machine to run it, install Java 8, install Tomcat, enable HTTPS for Tomcat, install Sparkler, configure secure communication between Sparkler and Tableau Online, and configure a connection between Salesforce and Sparkler.

Finally, you must embed and filter the dashboard on a record in Lightning Experience by creating a new Visualforce page and customizing the record page. All in all, not something you want to do, given other options. However, you should know it as you could see it in a legacy environment.

Conclusion

In this chapter, we have provided a comprehensive guide on integrating Tableau with Salesforce using the Tableau Viz LWC component. You have learned the purpose and benefits of this integration, as well as the process of installing and configuring the Tableau Viz LWC component for seamless integration in Salesforce.

Furthermore, we have delved into advanced usage techniques, including the creation of custom visualizations and modifying the component’s settings. We have also covered the implementation of Single Sign-On (SSO) between Salesforce and Tableau to streamline the authentication process and enhance security.

Additionally, we have explored alternative methods for connecting Salesforce and Tableau dashboards, such as direct connections and third-party integration tools. With the knowledge gained from this chapter, you are now well-equipped to enhance your CRM analytics in Salesforce using the Tableau Viz LWC component and make more data-driven decisions to drive business success.

In the next chapter, we will dive deeper into how you can combine Tableau with CRM Analytics to create game-changing analytical use cases.

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May 15, 2022
Introducing CRM Analytics – Blending Tableau with Traditional CRM Analytics

CRM Analytics, formerly known as Tableau CRM and Einstein Analytics, is a powerful data analysis and business insights platform that provides users with a comprehensive way to analyze customer data and derive actionable insights. Integrated seamlessly with Salesforce CRM, CRM Analytics leverages the power of machine learning from Einstein Discovery to deliver intelligent analytics for businesses.

One of the key features of CRM Analytics is its native two-way integration with the rest of the Salesforce platform. This integration allows users to easily access and analyze data from their CRM system, creating a unified platform for managing customer relationships and analyzing customer data. Additionally, CRM Analytics offers on-platform data extraction and transformation, enabling businesses to process and prepare their data for further analysis.

CRM Analytics also provides external connectivity to various platforms and cloud storage providers, facilitating data ingestion from multiple sources. The platform enables users to visualize and explore their data through interactive dashboards, enhancing their ability to identify trends and patterns. Moreover, the data action framework allows users to make data-driven decisions based on the insights generated.

Embedded intelligence from Salesforce Einstein further enriches the analytical capabilities of CRM Analytics. This integration allows businesses to benefit from features such as Einstein Sentiment Analysis, providing deeper insights into customer data.

Another notable aspect of CRM Analytics is its integration with Tableau. By connecting CRM Analytics to Tableau, users can create interactive visualizations and insights using data from their CRM system. This enhances their ability to analyze and understand customer data, ultimately leading to improved customer relationships, increased sales, and enhanced overall business performance.

CRM Analytics offers businesses a powerful and comprehensive tool for analyzing customer data and making data-driven decisions. Through the creation of custom datasets and lenses, CRM Analytics empowers businesses to gain a deeper understanding of their customers and improve their relationships, all while leveraging the capabilities of Salesforce CRM.

The addition of CRM Analytics, therefore, adds another puzzle piece in the larger analytics picture for organizations that are invested in the Salesforce platform. We cannot cover this tool in detail in this book, but we will touch on some of the key places where it intersects with Tableau to give additional capabilities. First, however, we will look at how to do some basic analysis in CRM Analytics.

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Mar 14, 2022
Objectives – Blending Tableau with Traditional CRM Analytics

Introduction

This chapter will introduce CRM Analytics and its importance in understanding and improving customer relationships. It will begin by providing an overview of CRM analytics and its key features, including creating datasets and lenses to analyze customer data. Additionally, the chapter will explain how to create an Einstein Discovery model within Salesforce and use it from within the CRM Analytics platform. Lastly, the chapter will detail the use of the CRM Analytics Tableau Output Connector, which allows for the seamless integration of Salesforce data into Tableau for further analysis. Overall, this chapter will provide a comprehensive understanding of the capabilities and benefits of CRM Analytics within Salesforce and its integration with Tableau.

Structure

The chapter covers the following topics:

  • Introducing CRM Analytics
  • Creating Datasets, Lenses, and Dashboards in CRM Analytics
  • Building a lens
  • Creating an Einstein Discovery Model and using it from CRM Analytics
  • Using the Tableau Online Output Connection

Objectives

In this chapter, learners will develop a thorough understanding of CRM Analytics and its crucial role in managing and enhancing customer relationships. They will delve into the key features of CRM analytics, including how to create datasets and lenses for effective customer data analysis.

The chapter guides learners through creating an Einstein Discovery model within Salesforce and demonstrates how to utilize it within the CRM Analytics platform. A significant focus is placed on employing the CRM Analytics Tableau Output Connector, which facilitates the seamless integration of Salesforce data into Tableau. This includes learning how to export Salesforce data for use in Tableau and maximizing the capabilities of the CRM Analytics Tableau Output Connector.

Learners will gain a comprehensive understanding of the functionalities and benefits of CRM Analytics within Salesforce, particularly in its integration with Tableau. By the end of the chapter, they will be equipped to apply their knowledge of CRM Analytics and Tableau in a way that significantly improves the quality of customer relationships and enhances business decision-making.

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Feb 9, 2022
Alternative methods to connect Salesforce and Tableau Dashboards – Integration, Authentication, and Tableau Viz LWC

While the Tableau Viz LWC component is the most common way to link Salesforce and Tableau, there are alternatives that you may want to consider in certain cases. First among these is the humble hyperlink or, alternately, a Salesforce Web Tab, linking to the relevant Tableau destination.

The main reason you would consider using a hyperlink instead of an embedded dashboard is that it is easy to implement and provides a level of control to the user. With a hyperlink, the user can decide when and where to access the Tableau dashboard. They can open it in a separate tab, window, or device and customize the view settings to their liking. Moreover, hyperlinks are easy to create and manage, and they do not require any special integration or maintenance efforts from either the Salesforce or Tableau side.

However, there are many drawbacks to using hyperlinks as well. First, you have to break the context and go to a different interface. It is also more difficult to pass parameters that are specific to the user context, as these will need to be set up in the visualization. Also, the security setup can become more complex by going down this route.

Using a hyperlink to link Salesforce and Tableau can be a viable option in certain cases. Still, it is important to weigh the pros and cons and consider the specific needs and preferences of your users before making a decision.

A second alternate option is to use a Tableau Connected App. Tableau-connected apps are a great way to securely and seamlessly authenticate external applications that embed Tableau content with your Tableau Cloud site. There are two types of connected apps: direct trust and OAuth 2.0 trust.

  • Direct trust allows you to restrict access to content that can be embedded and where it can be embedded. With direct trust, users can access embedded content using SSO without having to integrate with an IdP. You can also programmatically authorize access to the Tableau REST API and manage the Tableau REST API capabilities that users or applications can perform.
  • OAuth 2.0 trust also allows you to control access to embedded content and enable users to access it through SSO via your IdP. You can provide access using the standard OAuth 2.0 protocol, programmatically authorize access to the Tableau REST API, and manage Tableau REST API capabilities that users or applications can perform.

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