A Quality Assurance Guide to Salesforce Wave

February 12, 2016 Appirio

By Nitish Agarwal


Salesforce has always been ahead of the curve when it comes to customer success. Its Sales and Service Cloud offerings have been top-notch, making Salesforce the #1 CRM solution provider.

Continuing with its disruptive thinking, Salesforce introduced yet another product in October 2014 at Dreamforce. “Wave Analytics Cloud — Analytics for Everyone, Anywhere” is a must-have for every sales manager. This is because it can instantly give answers to questions like “Which sales rep in which region has not met its forecast?”

The following paragraphs describe important parts of Wave Analytics, and how Appirio’s Quality Assurance (QA) team works with it.

Key Wave Analytics features

  1. Multiple source data access: Wave allows users to view data present not only in Salesforce, but also from various other databases via connector for various ETL tools like Informatica and Mulesoft. This feature is a key differentiator from standard Salesforce reporting.
  1. Unanimous user interface: Wave is designed in such a way that any device — desktop, mobile device, or smart watch (e.g., Apple iWatch) displays the data in the same way. This allows Wave Analytics to be accessible from anywhere.
  1. Easy data drilling: Wave allows users to drill into the dashboard data with a single click.
  1. Easy sharing: Wave allows users to share the dashboard data either via a Chatter, post, the URL, or by sharing the downloadable image of the dashboard.

Wave Analytics basic vocabulary

  1. Measure: Something which can be represented as a number. For example, “number of employees.” Analytics Cloud allows users to apply aggregate functions on measures, like count or sum.
  1. Dimension: Something which has a qualitative value and no mathematics can be performed on it. For example, Region, Territory. They are the best candidate for operations, like group and filter.
  1. Dataset: The source data for Analytics Cloud. This data can be from Salesforce, or from any CSV File or ETL tool representing the data for any other database.
  1. Lens: The answer to any one question which is obtained by applying operations like group, filter, or sum on the dataset. A variety of the visual components like stacked bar or donut are available in Analytics Cloud.
  1. Dashboard: It is the canvas where the different lenses can be arranged together so that the multiple points of information can be viewed in a single place.
  1. Apps: It is the container for dashboards, lenses, and datasets. It helps to give permissions like viewer, editor, and manager to users, groups, or roles for a specific combination of dashboards, lenses, and datasets.

Wave Analytics from a QA perspective

The purpose for implementing Wave Analytics could be “to allow the user to make business decisions as quick as a lightning strike by accessing the 360-degree view of real-time data from all the data sources from anywhere at anytime across all platforms.” Therefore, QA should focus on ensuring that the integrity of the customer data is maintained along with the best user experience and usability.

Consider this scenario for Wave Analytics: A sales manager wants to inquire about the top 50 opportunities that have been closed this month, this quarter, or will be closed next quarter — along with the top 10 accounts and their revenues. Also, she wants to view the information by geography and division.

In the above scenario, QA should focus on the following checkpoints:

  1. Ensure the account and opportunity dataset is created with the fields that were consolidated in the source file that’s loaded into the Analytics Cloud.
  1. Ensure that the fields of the source file are segregated in the dataset as either a “measure,” “dimension,” or “date” (depending on the datatype of the field.) For example, the account name should be moved under “dimension,” account revenue under “measure,” and opportunity closed date under “date.”


  1. Ensure top 10 accounts and top 50 opportunities lenses of the sales manager dashboard are displaying the records for the account and opportunity dataset.
  1. Ensure that the data for the top 10 accounts and top 50 opportunities lenses is updated whenever the value of the geography and division filters is updated. For example, if geography is updated as “America,” then only America’s top 10 accounts and top 50 opportunities should be displayed.
  1. Ensure that the top 10 accounts lens displays the records with account revenue sorted descendingly.


  1. Ensure that the data of the top 50 opportunities lens is displayed depending on the toggle button selected for the closed date. For example, if the current month toggle button is selected, then the top 50 opportunities with a closed date within this month should be displayed.


  1. Ensure that the user has to select at least one toggle button for a closed date.
  1. Ensure that the account revenue data for the top 10 account lens displays only the whole numbers, since it is set to not display any decimal point.
  1. Ensure that scrolling of the data for the top 50 opportunities lens, if applicable, is working regardless of the various filters applied on the dashboard or the toggle buttons selected for the lens.
  1. Ensure that the same user interface is displayed no matter which browser or device (i.e., tablet, mobile, desktop, or iWatch) is used for viewing the dashboards.

In addition to the above, QA can also cover the following checkpoints depending on the configuration done for the lenses and dashboards:

  1. Make sure the appropriate legends are displayed for the lenses and dashboards as per the business requirements.
  1. Ensure that each lens configured to allow drilling are displaying the correct data whenever a drilling operation is performed on the lens. For example, if the “top 50 countries with accounts” lens is configured to display all the accounts for a country, then whenever a user clicks on the bar for any country all the details for that country should be displayed.
  1. Ensure that the navigation from one dashboard to another is working as expected whenever a button for the same function on the current dashboard is clicked. For example, if there are 3 dashboards (e.g., account, opportunity, and lead) and each dashboard has the button displayed on the top that allows the user to navigate to the other 2 dashboards, the buttons work as expected.

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