Your board wants yield, burn, and pipeline on one screen and Tableau needs four data engineers to do it: cost breakdown
Custom BI dashboards for a Sunnyvale deep-tech company, joining yield, ops, and financial data into one trustworthy view, run $45k to $120k over 3 to 6 months. Tableau, Power BI, and Looker are powerful but need a clean data layer underneath. The hard part for a hardware or biotech team is the pipeline that joins wafer yield, ERP (Enterprise Resource Planning) revenue, and ops data, not the chart.
If you are budgeting a build in Sunnyvale, this is what actually moves the number, where software and technology, semiconductors, hardware engineering teams overspend, and how to scope so the quote matches the outcome.
Every Sunnyvale exec wants the same thing: one screen with yield, revenue, burn, and pipeline, refreshed and trustworthy. The reason they don't have it isn't Tableau; it's that the data lives in five places that don't speak to each other. Wafer yield is in a test-data system, revenue is in NetSuite, pipeline is in a custom CRM (Customer Relationship Management), ops is in a spreadsheet, and biotech assay data is in a lab system. Tableau will happily chart any one of them and just as happily show four numbers that disagree.
So someone on the finance or data team spends two days a month hand-assembling the board deck, and by the time it's done, half the numbers are stale. The dashboard tool was never the bottleneck. The missing piece is the data pipeline and modeling layer that makes the join trustworthy, and that's the part Tableau, Power BI, and Looker assume you already have.
- Your key metrics live in five systems that don't join
- Tableau shows contradictory numbers because the data isn't modeled
- Someone burns two days a month assembling a stale board deck
- Hardware test or biotech assay data can't reach your BI tool
- Your data already lives clean in one warehouse
- A single source (say, your CRM) covers the metrics you need
- Off-the-shelf BI on your existing warehouse already works
- You lack anyone to maintain a data pipeline
- One trustworthy view joining yield, revenue, pipeline, and burn, refreshed automatically
- A modeled data layer so numbers reconcile instead of contradicting across tools
- The two-day monthly board-deck assembly replaced by an always-current dashboard
- Hardware test data and biotech assay data brought into the same analytics layer
- Self-serve metrics so execs stop pinging the data team for every question
- Most of the cost is the data pipeline, which is invisible work compared to charts
- It depends on the quality of your source data, which often needs cleanup first
- The pipeline needs maintenance as source systems change their schemas
- If your data is already clean and in one place, off-the-shelf BI may be enough
The honest cost picture for Sunnyvale
| Project scope | Typical cost | Timeline |
|---|---|---|
| Data pipeline + executive dashboards | $45k to $80k | 3 to 4 months |
| Full BI platform with modeling layer + self-serve | $80k to $120k | 5 to 6 months |
| Single-domain dashboard (yield or revenue) | $25k to $45k | 2 to 3 months |
Feature priorities for Sunnyvale teams
Business Intelligence Dashboards services we deliver in Sunnyvale
Digital Heroes builds the full business intelligence dashboards stack for Sunnyvale teams. Typical engagements cover Tableau alternative, Power BI, Looker, real-time analytics and KPI dashboards.
Exactly what you get
You get the part that actually makes BI work: a data pipeline and modeling layer that joins yield, revenue, pipeline, and ops into one reconciled model, with board-ready dashboards on top. The two-day deck assembly disappears. It pulls from your ERP, custom CRM, accounting software, and hardware test or biotech assay systems so a single view reflects the whole company, and it can surface those metrics back into your internal tools and project management software where teams already work.
How to choose a developer in Sunnyvale
Watch where the agency spends the conversation. A BI vendor who talks mostly about chart aesthetics is selling you the easy 20 percent. The right partner spends the time on the data pipeline, the modeling layer, and how to make numbers reconcile across sources, because that's where the value and the difficulty are. Scope the work alongside your ERP, accounting software, and custom CRM so the dashboards draw from real, reconciled data.
Timeline: what happens, and when
- !They focus on chart design; ask how they build the data pipeline underneath
- !No modeling layer; ask how metrics stay consistent across dashboards
- !They ignore source data quality; ask how they handle a messy ERP export
- !No pipeline maintenance plan; ask what happens when a source schema changes
- !They've only done dashboards on clean data; ask for a multi-source reference
Most Sunnyvale teams pricing business intelligence dashboards end up comparing notes on helpdesk & ticketing, erp, custom software too; the systems share one data spine.
Rohan advises mid-market and enterprise teams on ERP, CRM and custom software, and has led delivery on dozens of business-software builds.
Writes for Digital Heroes, shipping business software for 2,000+ brands across 55+ countries since 2017.
Frequently asked questions
Why can't Tableau give us a single board view in Sunnyvale?
Because Tableau charts whatever data you feed it, and your metrics live in five disconnected systems, yield in a test system, revenue in NetSuite, pipeline in a CRM. Without a data pipeline and modeling layer to join and reconcile them, Tableau shows contradictory numbers. The dashboard tool was never the bottleneck; the missing data layer is.
What's the hard part of BI for a hardware or biotech team?
The data pipeline and semantic layer, not the charts. Joining wafer yield, ERP revenue, CRM pipeline, and lab assay data into one reconciled model is where the real engineering lives. Off-the-shelf BI tools assume you already have that clean, modeled data, which most deep-tech companies don't, so that's exactly what a custom build provides.
What do custom BI dashboards cost in Sunnyvale?
Between $45k and $120k. A data pipeline with executive dashboards runs $45k to $80k; a full platform with a modeling layer and self-serve runs $80k to $120k. The data pipeline and integration is the biggest cost driver, followed by the modeling layer and any source-data cleanup.
Can we keep Tableau or Looker as the front end?
Yes, often you should. The custom work is the pipeline and modeling layer underneath; the front end can be Tableau, Looker, Power BI, or a custom UI. Building the reconciled data layer first means whichever tool you use finally shows numbers that agree, which is the entire point.
How do we stop hand-assembling the board deck?
By building an always-current executive dashboard on top of a modeled data layer that refreshes automatically. Once yield, revenue, pipeline, and burn flow into one reconciled model, the deck assembles itself and the numbers are live, replacing the two-day monthly scramble that produces a stale deck.