Data 360 Meets Tableau and CRM Analytics: The Exec Dashboard

The scenario

Vantage Freight is a logistics company. Shipment tracking events live in a data lake; customer accounts, quotes and complaints live in Salesforce. Over the last quarter they built the Data 360 foundation from Part 1: shipment events ingested as an engagement DMO, customers resolved into unified profiles, and an on-time delivery Calculated Insight per account.

Then the COO asked the question that funds data projects: "One dashboard. On-time rate, margin per lane, and which of our top-50 accounts are getting bad service — weekly, on my screen, not in a spreadsheet."

The data is ready. The remaining decision is the tool. Vantage has Tableau licenses in operations and CRM Analytics bundled with their Salesforce licenses — and the honest answer, as usual, is "it depends on who's looking."

The metric first: one CI, every tool

Resist building metrics inside the dashboard tool. Vantage defines on-time performance once, as a Calculated Insight (the discipline from Part 2), so Tableau, CRM Analytics and any future agent all read the same number:

SELECT
    s.account_id__c AS account_id__c,
    COUNT(s.shipment_id__c) AS total_shipments__c,
    SUM(CASE
        WHEN s.delivered_on__c <= s.promised_on__c THEN 1
        ELSE 0
    END) AS on_time_shipments__c,
    AVG(s.margin_pct__c) AS avg_margin_pct__c
FROM Shipment__dlm s
WHERE s.delivered_on__c IS NOT NULL
GROUP BY s.account_id__c

If the on-time rate lived as a Tableau calculated field, the ops team's number and the exec dashboard's number would drift within a quarter. A CI is the single source of "what does on-time mean here" — the dashboards become presentation layers, which is all they should be.

Path 1 — Tableau, live on Data 360

Tableau ships a native Data 360 connector (you'll still see it labeled Salesforce Data Cloud in the connect pane). It queries the lakehouse live — no extracts to schedule, no copies to reconcile — and it's backed by accelerated queries, a Data 360 service that speeds up live connections from Tableau.

1. In Tableau, choose the connector from the connect pane and sign in with OAuth (Tableau Server needs the connected-app OAuth setup done once by an admin).
2. Pick the data space, then drag in the shipment DMO, the unified account DMO and the on-time CI object — they join on the account dimension like ordinary tables.
3. Build the three views the COO asked for: on-time trend, margin by lane, and a top-50-accounts table sorted by service score. Labels come through as object labels, not API names, so the ops analyst never sees __dlm.

Choose Tableau when the audience lives outside Salesforce (ops teams, execs who want a link or a TV screen), analysts already speak Tableau, or the visual requirements go beyond standard dashboard widgets.

Path 2 — CRM Analytics, inside the CRM

CRM Analytics reads Data 360 objects through its Salesforce-native connectors, and its dashboards embed directly on Lightning record pages. Vantage uses it for the second audience nobody mentioned in the exec meeting: account executives.

• Sync the on-time CI and shipment DMO into a CRM Analytics dataset alongside CRM opportunity data.
• Build one dashboard: this account's on-time trend, open complaints and shipment volume.
• Embed it on the Account record page — the AE opens the account before a renewal call and sees the service story without leaving Salesforce.

Choose CRM Analytics when the consumer is a CRM user in record context, you want row-level security inherited from Salesforce sharing, or actionability matters — CRM Analytics widgets can launch actions on the records they chart.

The decision table

Vantage shipped all three: Tableau for the COO's weekly view, CRM Analytics embedded for AEs, and an On_Time_Rate__c field on Account feeding list views. Same CI underneath all of them — that's the part that makes it maintainable.

Governance: who gets to see margin data?

The exec dashboard exposed a question Vantage hadn't asked while the data sat in the lake: margin per lane is commercially sensitive, and now it's one click from every viewer. The two paths govern differently, and it should influence your choice:

• CRM Analytics inherits the Salesforce security model — the embedded account dashboard shows an AE only accounts they can already see, with row-level security enforced on the dataset. If the answer to "who can see this?" is "whoever can see the record," CRM Analytics gets you there with the least custom work.
• Tableau authenticates each viewer's live connection against Data 360 permissions, and workbook-level access is managed on the Tableau side. Vantage publishes the COO workbook to a restricted project and keeps margin fields out of the ops team's data source entirely.
• Either way, scope at the source. Data spaces partition what a connection can reach at all — the cleanest control is data the connector never sees. Decide field-level sensitivity when you design the CI, not after the first screenshot circulates.

Watch the meter

Live connections are convenient and metered. Data 360 queries consume credits, and a popular Tableau dashboard on auto-refresh is a query generator. Three habits keep the bill boring:

• Aggregate in the CI, not the dashboard. The on-time CI reduces millions of shipment rows to one row per account before any dashboard touches it. Dashboards over raw engagement DMOs are the classic credit burner.
• Match refresh to reality. The CI publishes nightly — a dashboard refreshing every five minutes recomputes the same answer 288 times.
• Check consumption early. Review Data 360 usage cards in the first weeks after launch, not at renewal time.

What you learned

• Define metrics once as Calculated Insights; treat every dashboard as a presentation layer on the same number.
• Tableau's native connector queries Data 360 live with accelerated queries — best for broad, visual, outside-the-CRM audiences.
• CRM Analytics brings unified data into record context with Salesforce-native security and embedding.
• Copying a CI value onto a CRM field and using a standard report is a legitimate architecture, not a hack.
• Analytics on consumption-priced data needs the same cost discipline as API design.

That closes the series. Start from the beginning on the Data 360 track page, or jump to Part 1: fundamentals — and if your next step is putting this data in front of an agent instead of an exec, that's Part 3.

Sources: Salesforce Help — Connect Tableau in Data 360 · Tableau Help — Salesforce Data 360 connector · Activation and Activation Targets