Fishbowl to Power BI, done for you
Fishbowl tracks every part, order and build — then hands you a report window instead of a picture. A senior US-based engineer builds the connection, the model and the scheduled refresh, so stock, turns, margin by SKU and open work orders sit on pages that update themselves.
Representative dashboard — sample data
Stock data you can finally see
Small manufacturers and wholesalers add Fishbowl Inventory because QuickBooks alone could not hold parts, locations, work orders and landed cost. It does that job well. Then the reporting question arrives — what is turning, what is dead, which SKUs actually earn — and the honest answer is a report window and an exported workbook that somebody rebuilds every Monday. That is the gap a Power BI dashboard is for.
Built properly, it replaces that routine with one governed model. We connect to the records your server already holds, shape them into a star schema, write the measures, and schedule the refresh — so on-hand value, inventory turns, margin by SKU and open builds all read from the same source and agree with each other.
What we build from Fishbowl
Buy a block of prepaid Flex hours and, if you're unhappy within the first 4 hours, we refund you in full — no questions asked. We scope each task and quote the hours before work starts, hours deduct only for work you approve, and your banked hours never expire.
Why teams hand this over
Nobody stalls on picking a chart type. Inventory reporting stalls on getting clean, refreshable data out of the system without disturbing the people using it.
Power BI ships no first-party Fishbowl connector. The server keeps its records in MySQL, so we usually read them through a read-only database account — and use the Fishbowl API instead where your edition or your hosting makes that the better route.
Your parts, products, location groups, customers and vendors become proper dimensions. Quantities, costs and order lines land at the right grain, so a margin figure on the summary page drills to the SKU, the order and the transaction underneath it.
An export answers one question once, and ages the moment it is saved. We move that logic into a model that pulls only changed rows on each run and refreshes on a schedule, so the numbers are waiting rather than being rebuilt.
We land an extract rather than querying the live server all day, run refresh incrementally, and schedule it around your shifts. Where Fishbowl sits on your own network we configure and document an on-premises data gateway so refresh survives a reboot.
One engineer with 20+ years on the Microsoft platform does the extract, the model and the DAX. Prepaid Flex hours never expire, there is no project minimum, and a first inventory build is exactly what they are for.
Because a stock system is built to run transactions, not to trend them. Its reports answer one question, for one person, as of right now. Someone still has to export last quarter, join it to sales, work out what turned and what sat, and reconcile the result against the ledger. The workbook that grows out of that becomes the real reporting system — owned by one person, unversioned, and quietly wrong in ways nobody can audit.
The symptoms are consistent. On-hand value is known but turns are not, so nobody can say which SKUs are funding the business and which are storing cash on a shelf. Margin is quoted at the invoice level and never at the part level, so the loss-makers hide inside a healthy average. Builds are tracked on a whiteboard because the work-order list will not trend. A semantic model fixes this at the root: one set of facts and dimensions, one definition of turns and of margin, and visuals that recompute themselves.
The views that earn their keep for a small manufacturer or wholesaler are the ones that connect stock to money: what you hold, how fast it moves, what it earns, and what is in build. Each is a page in one model rather than a separate export. Here is the map we walk through on the demo call.
| Dashboard view | What it measures | Fishbowl records behind it |
|---|---|---|
| Stock on hand | Units and inventory value by part, location group and bin, with a committed-versus-available split | Part and product records, on-hand quantities by location |
| Inventory turns & aging | Turns, days on hand, and slow-moving or dead stock ranked by the cash sitting in it | Issue and receipt history measured against on-hand balances |
| Sales & margin by SKU | Revenue, cost and gross margin per part, customer, channel and rep, trended against prior periods | Sales orders and order lines with unit cost and price |
| Work orders & builds | Open, in-progress and finished builds, quantity completed against planned, and cycle time | Work order and manufacture order records with their statuses and dates |
| BOM cost roll-up | Component cost per finished good, and planned consumption against what the build actually used | Bills of materials plus the parts issued to each build |
| Reorder & purchasing | Parts below reorder point, open purchase orders, vendor lead time and receipt accuracy | Purchase orders, receipts, vendor records and reorder settings |
| Backorders & fill rate | Lines shipped complete against what was promised, and the age and value of what is waiting | Sales order lines compared with shipment records |
The table describes record types, not a schema. Field names and availability vary by Fishbowl edition, version and how your team has configured it, so we confirm the mapping against your own install before quoting the hours. Distributors who want the wider trading picture — fill rate, vendor scorecards and customer health across the whole book — should read our Power BI dashboards for wholesale distributors, and shops that also run a plant floor will find the production side on Power BI for manufacturing and logistics.
Through whichever supported route your install allows. The Fishbowl server stores its data in MySQL, so a read-only database account is usually the cleanest path: Power BI has a documented MySQL database connector (opens in new tab), and a scoped account keeps reporting away from anything that can write. Where your edition or your hosting makes that awkward, the Fishbowl API covers the same ground with more effort per record.
Whatever the route, we do not point a report at the production server and leave it there. We land the extract, run it incrementally so each refresh moves only changed rows, and let the report query a modeled copy — which keeps the warehouse screens responsive while a year of transactions is being read. Refresh then runs inside Power BI's documented limits; Microsoft's data refresh reference (opens in new tab) sets out the cadence available on each licence. Because Fishbowl typically runs on a server inside your own network, an on-premises data gateway (opens in new tab) carries the connection; we install it, document it, and fix breakages out of your banked hours.
It depends on your edition, how much history you need, and what your administrator is willing to open up. This is the honest comparison behind the scope estimate you approve before any hours are spent.
| Access path | Best for | Tradeoff |
|---|---|---|
| Read-only MySQL account | Server installs on your own network; full history, incremental loads | Needs database credentials from your administrator and a gateway |
| Fishbowl API | Editions or hosting arrangements where direct database access is not offered | More work per record, and narrower coverage than the database |
| Staged copy in SQL Server | Large transaction volumes, or joining Fishbowl to other systems | Adds a database to run — worth it once history gets long |
| Scheduled report exports | Small, stable extracts and quick proofs of concept | Stays semi-manual; does not scale to years of transactions |
| Accounting system alongside | Financial statements, AR and AP sitting next to the unit detail | Ledger only — no part-level stock or build detail on its own |
Fishbowl holds the unit-level truth and the accounting system holds the ledger, and the two answer different questions. Reporting from either alone leaves a gap: the stock system cannot produce a P&L, and the ledger cannot tell you which SKU is turning. Modeling them together closes it.
We align the item, customer and vendor keys across both, so gross margin by SKU and the income statement are read from one refreshed model rather than two exports reconciled by hand. Teams that want the ledger side built out first should start with our QuickBooks Power BI dashboard build; if your books run on Xero instead of QuickBooks, the same pattern applies with a different source. Either way, the inventory model stands on its own and the finance layer clips onto it.
Small and mid-sized manufacturers, assemblers, wholesalers and distributors running Fishbowl — usually with an owner, controller or operations manager who is tired of rebuilding the same workbook. You buy prepaid Flex hours that never expire: Starter $2,500, Growth $4,600 or Power $8,000, with rates from $100/hour on the largest block.
Most tasks ship in 3–5 business days once you approve the scope estimate; a first full inventory build is larger and gets a clear timeline up front. The usual pattern is a Growth or Power block for the connection, the model and the first pages — that work is front-loaded — then the remaining hours spent on extra views, DAX changes and refresh care. There is no project minimum and no retainer: you send a request, we reply with a scope and the hours it needs, and hours deduct only for work you approve. The mechanics are laid out on how prepaid Flex hours work.
Everything. The Power BI file, the semantic model and DAX, the extraction logic, the refresh schedule and the service account all live in your tenant and on your server. There is no black box, no licence to us and no lock-in — if you never send another request, the dashboards keep running.
We publish to your workspace, document the access route and the records we read, and walk your team through the model so someone internal can maintain it. Most clients then keep a few banked hours for what follows: a page for a second warehouse, a measure that has to track a changed costing method, or a refresh that broke when credentials rotated. That is post-launch support without a retainer — the same hours, spent when you need them.
business days, typical
hours, never expire
own everything
Connection, modeling, DAX and refresh care all draw from the same banked hours. See Flex pricing →
How it works
Tell us your Fishbowl edition, where the server lives, whether QuickBooks or Xero holds the books, and the views you need first. We reply with a scope and an hours estimate before any work begins — hours deduct only for builds you approve.
A senior US-based engineer sets up the read-only access with your administrator, lands the records incrementally, builds the star schema and the DAX, and ties on-hand value and margin back to the reports your team already trusts before anyone sees a chart.
We publish to your workspace, configure the gateway and scheduled refresh, document the connection and the model, and hand everything over. You own it outright; we keep the refresh healthy from your banked hours whenever you want us to.
Representative perspective
We knew what we held. We had no idea what was turning. Seeing dead stock ranked by the cash tied up in it changed what we bought the following quarter.Owner, small contract manufacturer
Representative perspective
Margin used to be an invoice-level average that made everything look fine. Once it was broken out by part, two of our best-selling SKUs turned out to be the problem.Controller, wholesale distributor
Tell us your Fishbowl edition, where the server sits and the views you need. We'll confirm the access route, scope the task and quote the hours before any work begins — drawn from prepaid Flex hours that never expire, with no project minimums.
FAQ
There is no first-party Fishbowl connector in Power BI, so we build the connection ourselves. The Fishbowl server keeps its records in a MySQL database, so a read-only database account is usually the cleanest route; the Fishbowl API is the alternative where your edition or your hosting makes database access awkward. We confirm which route your install supports before any hours are spent.
Usually a read-only account scoped to the records behind the views you want, plus the host and port your server listens on. Where Fishbowl runs on your own network we also configure an on-premises data gateway so refresh can reach it. The exact list goes into your scope estimate before work starts.
Yes, for the financial statements. Fishbowl holds the unit-level detail and QuickBooks holds the ledger, so the two answer different questions. We can model them side by side, aligning the item and customer keys, so gross margin by SKU and the P&L are read from one refreshed model instead of two exports.
We do not point reports at the live server and hope. We land the records into a modeled copy, run each refresh incrementally so only changed rows move, and schedule it outside your working hours where volume warrants it. Reports then query the model, not the system your warehouse staff are using.
No. We are an independent, US-based Power BI practice and claim no Fishbowl or Microsoft partnership. Our engineers are Microsoft-certified, and we build only with documented, supported tooling: the access route your Fishbowl administrator approves, plus Power BI's published gateway, refresh and semantic model features.
Book a free demo
Tell us the task. We scope it, you approve, and a senior consultant delivers — typically in 3–5 business days. Prepaid hours that never expire.
The fastest way to reach us is the form — tell us the task and we'll reply within one business day.