12.2 Reports, Dashboards & Tableau Analysis on Data 360 Data

12.2 Reports, Dashboards & Tableau Analysis on Data 360 Data

Quick Answer: Data 360 data is reportable with the ordinary Lightning Experience report builder. A standard report runs against a single source — one data model object (DMO), one semantic model, or one calculated insight. A custom report type combines fields and records from multiple related DMOs, up to four. Reports roll up into dashboards the same way CRM reports do. For deeper analysis, semantic models expose a governed metric layer to Tableau and Tableau Next, and CRM Analytics can connect to Data 360 directly. Reporting is the governed analytical surface; the Query Editor and Query API are the exploratory one.

This section covers the "View and build reports and dashboards using Data 360" objective inside Data Enhancements, Sharing, and Analysis (18%).

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Why Reporting Matters to the Consultant Conversation

Every Data 360 implementation eventually meets the same question from the business sponsor: "We spent six months unifying this data. Where do I look at it?" If the only answers are "build a segment" or "ask an architect to run SQL," the platform looks like marketing infrastructure rather than an enterprise data asset.

Reports close that gap. They turn harmonized, identity-resolved data into something a marketing operations manager, a service director, or a finance analyst can open without a licence to a separate analytics tool and without knowing that UnifiedIndividual__dlm exists.

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Standard Reports vs. Custom Report Types

Salesforce documents two report shapes for Data 360, and the distinction is directly testable:

The four-object ceiling on custom report types is the kind of specific limit that shows up as a distractor. If a scenario asks for a report spanning five or six related DMOs, the correct consultant answer is to pre-join upstream — a calculated insight or a data transform that flattens the relationship — and then report on the result as a single source.

Building the Report

Once the report type is in place, the workflow is standard Lightning Experience:

1. Group to compare meaningful categories — loyalty tier, region, acquisition channel.
2. Filter to focus the record set — date ranges, consent flags, segment membership.
3. Summarize fields to surface trends — sum, average, count, min, max.
4. Add a chart so the report communicates at a glance.
5. Run it for near real-time results against Data 360.

Dashboards

Dashboards assemble multiple Data 360 reports into a single view — one component for audience growth, one for unified profile counts by region, one for consolidation health, one for activation volumes. Standard Lightning dashboard features apply: dynamic dashboards, subscriptions, and scheduled refreshes.

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Prerequisites That Trip Implementations

Reporting on Data 360 is not automatic. The recurring blockers a consultant should check before promising a dashboard:

• The object has to be exposed for reporting. A DMO that has not been enabled for reporting will not appear in the report type wizard, no matter how well mapped it is.
• Relationships must exist in the model. A custom report type can only traverse relationships that were actually defined between DMOs. If nobody created the relationship between the order DMO and the unified individual, there is nothing to join across.
• Permissions and data spaces still apply. A user who cannot see a data space cannot report on its data. An empty report is more often a scoping problem than a data problem.
• Reports read the model, not the lake. Reporting targets DMOs, semantic models, and calculated insights — not raw data lake objects. Raw DLO inspection stays in Data Explorer.

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Semantic Models, Tableau and CRM Analytics

A semantic model is a governed layer of business-friendly entities and metrics defined over Data 360 objects, so that "active customer" or "net revenue" means the same thing in every downstream tool. Salesforce supports creating a semantic model from a data kit and from a Tableau published data source (PDS), which lets an organisation that has already standardised its definitions in Tableau reuse them rather than redefine them.

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Reporting vs. Query Editor vs. Data Explorer

These three get conflated constantly. Keep the personas separate:

Remember the access constraint from Chapter 3: Salesforce documents that neither the Data Cloud Activation Manager nor the Data Cloud Activation Specialist permission set can open the Query Editor. That is precisely why reports matter — they are how an audience operator answers an analytical question without the SQL surface.

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Worked Scenario: The Audience Health Dashboard

A retail client wants a weekly executive view covering: unified profile growth, consolidation rate trend, segment population by brand, and activation success rate.

1. Unified profile growth — standard report on the unified individual DMO, grouped by created date, summarized as a record count, with a line chart.
2. Consolidation rate trend — the raw counts are on two different objects, so pre-compute the ratio in a calculated insight and build a standard report on that insight. Trying to divide across objects in the report builder is the wrong shape.
3. Segment population by brand — standard report on the segment membership DMO, grouped by the brand attribute.
4. Activation success rate — a custom report type joining the activation-related DMOs, staying within the four-object limit.
5. Assemble all four as components on one dashboard, add a subscription so the executive sponsor receives it Monday mornings.

The instructive step is the second one: the moment an analytical requirement needs a ratio, a window, or a cross-object aggregation, the work belongs in a calculated insight and the report simply displays it.

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Exam Traps & Consultant Pitfalls

Trap 1: Reporting on raw DLOs. Reports target DMOs, semantic models, and calculated insights. If a scenario wants to inspect what landed in a raw data lake object, that is Data Explorer, not a report.

Trap 2: Exceeding the custom report type join limit. Custom report types combine up to four related DMOs. A five-object requirement means flattening upstream with a calculated insight or data transform.

Trap 3: Reaching for Tableau by reflex. When a scenario describes a Salesforce-native business user wanting a recurring view with a chart and a subscription, the lowest-friction correct answer is a Data 360 report and dashboard — not a separate analytics platform.

Trap 4: Calling reports real-time. Data 360 reports return near real-time results. A requirement for sub-second, in-conversation data is a data graph, and a requirement for event-window detection is a streaming insight.