“How much is Yardi Data Connect?” is one of the most-searched Yardi questions, and for good reason — Yardi doesn’t publish list prices. This guide is the independent buyer’s view: what Data Connect is, what it actually costs, the failure modes nobody will tell you about, and when you should (and shouldn’t) license it.
What Data Connect actually is
Data Connect is Yardi’s supported pipeline from Voyager into Microsoft Power BI. Under the hood it is a Snowflake replica of your Voyager database, refreshed on a vendor-controlled cadence, with a Power BI gateway that exposes a set of curated views to your BI environment.
Three things to understand:
- It is not a warehouse you control. You get query access, not cloud-account ownership. The Snowflake instance lives in Yardi’s tenancy, not yours.
- The refresh cadence is daily for most customers. Sub-daily refresh is available at the enterprise tier with additional cost.
- The view layer is opinionated. Yardi has already made dozens of join / flatten choices for you. Most of them are reasonable; a few will frustrate your analytics team (more on that below).
What it actually costs — the ranges we’ve seen
Yardi’s commercial team does not publish Data Connect pricing, and will typically route a direct question to a named rep. In our engagements over the last 18 months, the all-in annual Data Connect spend has landed in the following bands:
| Portfolio size | Annual Data Connect spend | Notes | |---|---|---| | 500–1,000 units | $14K–$22K | Usually 3–5 seats; one database | | 1,000–5,000 units | $20K–$35K | 5–10 seats; one or two databases | | 5,000–15,000 units | $30K–$55K | Multi-DB; more seats; occasionally sub-daily refresh | | 15,000+ units | $50K–$85K+ | Enterprise; sub-daily refresh; Qlik add-ons common |
These bands are directional, not a rate card. Every customer negotiates. Two identical portfolios can come out 30% apart depending on which rep, which renewal cycle, and what else is in the contract.
What’s stable is the cost-per-user, cost-per-database, cost-per-refresh-tier structure. Your total Data Connect bill is some multiplicative combination of those three.
When Data Connect is the right choice
Data Connect is the right pipeline when:
- You’re Power BI-standardized. Your finance team lives in Power BI. Your reports are native .pbix files. You have no intention of adopting Looker or Tableau.
- You want Yardi to own the pipeline. Your IT team is lean. You don’t want to maintain a Replicate-Qlik deployment. Daily refresh is fine.
- You’re at or above 1,500 units. Below that threshold, the all-in cost tends to exceed what scheduled YSR exports would cost you, and the operational marginal benefit becomes hard to justify.
- You need audited, vendor-sanctioned extraction for HUD / LIHTC compliance or similar regulatory reasons.
When Data Connect is the wrong choice
Data Connect is the wrong pipeline when:
- You want sub-hourly freshness. Yardi will quote you sub-daily refresh, but the full pipeline has lag points (Snowflake refresh cadence, Power BI dataset refresh cadence) that make true real-time elusive.
- You want to join Voyager with non-Yardi sources at the warehouse layer. Data Connect exposes a view layer in Yardi’s Snowflake, not a raw warehouse in yours. Joining with your HR system, your leasing platform, or your banking data happens upstream of Power BI — and that architecture is awkward with Data Connect.
- You want Looker, Tableau, Sigma, or a non-Power-BI BI layer. There are workarounds (export to Excel, Power BI REST API, third-party Snowflake bridges), but none of them are what you thought you were buying.
- You’re under 1,000 units and budget-constrained. Scheduled YSR exports into your own warehouse will do what Data Connect does for 10% of the cost, with more lag.
The six gotchas Yardi sales may not mention
These are the patterns we see show up in Data Connect deployments at month 3, month 6, and renewal.
1. The Power BI seat multiplier
Data Connect is priced per user connecting through Power BI. Many operators assume the Power BI Pro license (~$10/user/month) is the relevant per-user cost. It isn’t — it’s on top of Data Connect’s own per-seat charge. When you model ROI, you’re paying Microsoft and Yardi for the user.
2. The refresh cadence renegotiation
Sub-daily refresh is available but is almost always a renegotiation event, not a self-service setting. Factor a 20–40% price premium for moving from daily to sub-daily.
3. The curated view layer is fixed
Data Connect exposes a predetermined set of views. If you need a column that isn’t in that view layer (a custom field, a join across tables not exposed together), you’re looking at a Yardi Professional Services engagement — billable at ~$150/hour — to get it added. This is one reason operators often layer their own dbt models on top of a raw YSR export in addition to Data Connect.
4. Concession accounting is already decided for you
Data Connect’s views apply a specific concession-accrual convention. If your finance team books concessions differently, your dashboards will reconcile oddly against your GL. This is solvable, but it requires a conversation with your Data Connect rep that most customers don’t know to have until they’ve already gone live.
5. Multi-entity rollups don’t always line up
If you operate multiple Voyager databases (e.g., a fund 1 / fund 2 / JV structure), each database is licensed separately in Data Connect. Rollups across databases happen in Power BI, not in Data Connect — which means you’re either building the cross-entity join in Power BI (slow, awkward) or standing up a third warehouse layer to do it (at which point the value of Data Connect diminishes).
6. Custom fields need propagation time
Custom Voyager fields (user-defined, often used for fund-level tagging or unit amenities) do not automatically appear in Data Connect views. Adding them requires a ticket, a cycle, and sometimes an additional SKU. If your portfolio uses a lot of custom fields, scope that work explicitly during your Data Connect negotiation.
Data Connect vs. Replicate vs. scheduled YSR
| | Data Connect | Replicate | Scheduled YSR | |---|---|---|---| | Warehouse location | Yardi’s Snowflake | Your cloud account | Your cloud account | | Freshness | Daily (sub-daily extra) | Near-real-time CDC | Nightly | | BI tool | Power BI (primarily) | Any | Any | | Price, 5K units | ~$30K/yr | ~$40–55K/yr | ~$2K/yr all-in | | Setup effort | Low (Yardi does it) | Medium (Qlik + cloud) | Medium (export job + loader) | | Audit posture | Strongest | Strong | Weakest | | TOS risk | None | None | Low (YSR is licensed) | | Best for | Power BI-only shops | Enterprise, multi-source | Small/mid-market, budget-constrained |
Questions to ask before signing
If you’re in an active Data Connect conversation, here are the questions that will save you an unpleasant month-6 surprise:
- What is the per-seat price at daily refresh vs. sub-daily? Which tier is in this proposal?
- Are all of our Voyager databases covered, or is this a per-database license?
- Does the current view layer expose the custom fields our asset management team uses? If not, what is the cost and timeline to add them?
- What is the annual price escalator after year one?
- If we terminate, what happens to our historical replicated data? Is there an export window?
- What is the procedure and cost for adding a non-Power-BI connector (Tableau, Sigma, Looker) if we change BI platforms in the future?
These are reasonable to ask and you should have the answers in writing before signing.
The Memowright view
We build on all three paths — Data Connect, Replicate, and YSR. Our strong recommendation for the 2,000–20,000-unit operator segment:
- Under 2,000 units: Scheduled YSR export + Snowflake / BigQuery in your cloud account. Add Data Connect only if Power BI native is a hard requirement.
- 2,000–10,000 units: Whichever of Data Connect or YSR you already have. If neither, YSR first (lower commitment), and revisit at renewal.
- 10,000+ units: Replicate into your own warehouse. You’ve outgrown Data Connect’s view-layer limitations and you want the CDC freshness and architectural flexibility.
Whatever pipeline you pick, the warehouse should live in your cloud account, the dbt models should be in your source control, and the analyst / vendor layer (us or anyone else) should be replaceable without a data migration.
Related reading