Introducing Data Cloud Reports on Tableau Semantics

If you’re a Reporting customer, you’re probably well-versed with the concept of a Report Type (if not, this post is a great introductory post). A report type is a lightweight data model that lets you define object joins and acts as a template to create Reports. You can join up to 4 objects, and the join type can be an inner or a left-outer join.

Now, with the introduction of Data Cloud and Data Cloud Reporting, we’re introducing another powerful concept called a Semantic Model. A Semantic Model is a container of the entities that define your business terms. With this new concept, Data Cloud Reports will now be able to unlock deeper insights and unparalleled flexibility in reports.

Wait, Semantic What?

Semantic Models are first-class Salesforce metadata, integrated throughout Data Cloud to power analytical and data-driven experiences. The Semantic Model is composed of a grouping of semantic definitions tailored for a specific analytical use case. Semantic Models consist of one or more data objects. With Semantic Models, you can create flexible joins across more than four objects and enrich your analysis with Calculated Dimensions and Measures.

Great, but what is the Semantic Layer?

The Semantic layer, a new layer that’s been introduced in Data Cloud, is a business representation of corporate data that helps end-users and applications access data using common business terms. This layer of abstraction provides a consistent way to map complex data into familiar business terms such as revenue, return on investment, or retention, to offer a standard and unambiguous interpretation of data across the organization.

You can think of it as a translation layer between the raw, messy data in your spreadsheet or database, where you store fields with text and numbers, and the business language we all speak, such as – Metrics and Dimensions, or Revenue and Regions. It serves as a trusted place where you can ask business questions of your data such as “what was my Revenue across Regions during the Last Year?”

Positioned above Data Cloud’s data sources, the Semantic Layer will drive all data consumption experiences that rely on Data Cloud, including Salesforce applications (such as Data Cloud Reports, Tableau Einstein, Intelligent apps, and AI). The core components of the Semantic Layer are the Semantic Models and the Semantics Query Generator.

The Semantics Query Generator allows you to make the most of your data in Data Cloud through Tableau Semantics to answer a variety of business questions.

The Semantics Query Generator is an API-based service that interacts with the Semantic Model and generates ‌optimized SQL over Data Cloud objects. This API accepts a semantic query as a parameter, a context of a tenant, and then internally fetches the needed data-model metadata and calculates and returns the query result.

You can use these components in Data Cloud Reports to elevate your reporting capabilities by building comprehensive Data Cloud Reports on these advanced models, now in Beta.

Okay, so now tell me why I should use the Semantic Layer…

The primary issue we’re hearing from our customers is that they can’t trust the data within their BI tools. They’re encountering different values for the same metrics across various apps or dashboards, and they lack visibility into how their KPIs are calculated. This lack of trust and visibility stems directly from the absence of a semantic layer. Without a semantic layer to offer context (such as timezone and business calendar), visibility, and centralized management (a single source of truth) for how business metrics are calculated, customers are compelled to rely on complex, hard-coded SQL to understand and view their data.

A Semantic Layer ensures consistent metrics across all platforms, providing every user with a unified and reliable view of data from all sources, thereby enhancing every business decision. It enables Trusted AI by supplying the necessary context for accurate data interpretation and effective utilization. Additionally, it streamlines data management and reduces complexity by managing all data through an integrated, reusable layer that spans the entire data stack.

Got it. So, now, how can I‌ use it?

Imagine you’re a marketing manager. You’ve purchased Data Cloud, and ingested your data into it. Now, you want to evaluate the success of your campaign based on factors such as unsubscribe rate, bounce rate, clickthrough rate, etc., for email templates, as well as landing pages, forms, and other assets. However, this data is spread across multiple data model objects, such as Email Engagement, Flow, Campaign, Bulk Email Messages, and more.

This goes beyond the limitations of a standard Report Type, as it involves more than five objects and requires sibling joins.

To address this, you can create a Semantic Model that links all these objects together, allowing you to define Calculated Measurements for key metrics such as clickthrough rate, bounce rate, and unsubscribe rate.

Once the model is built, you can publish it for use in your analysis.
Now, you simply need to go to your Reports tab, select Semantic Data Models as the category, and start reporting on it.

Note: Detail Rows and Row Count are currently disabled for Reports on Semantic Models.

So there you go, with reporting on Semantic Models; you can derive insights and take action based on the 360-degree view of your customers in Data Cloud.

Sounds amazing! How do I sign up for the beta?

Go to Setup → Reports and Dashboards → Enable reports on semantic models (Beta).

Please Note: Semantic Model is a beta service that is subject to the Beta Services Terms Agreements – Salesforce.com, and the Non-GA Credit Consumption terms in the Product Terms Directory. Use of this beta service consumes Customer Data Cloud Credits and is at the Customer’s sole discretion. At the conclusion of the open beta period, use of portions of the Semantic Model may be subject to additional purchase and/or additional credit consumption.

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