Modernize your JD Edwards data foundation

Your JDE data has outgrown your financial reports. Balances sit in F0902, the detail behind them in F0911, and most JDE reporting only ever reaches one of the two. QuickLaunch joins both into one governed model, then keeps expanding it from there.

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F0101 ABAN8 Address Number Master Data F0101 ABALPH Name Master Data F4211 SDDOCO Sales Order Order to Cash F4211 SDLITM Item Number Order to Cash F0411 RPAN8 Supplier Procure to Pay F4101 IMDSC1 Item Description Product F0911 GLOBJ Object Account Finance F03B11 RPAAP Open Balance Receivables F4801 WADOCO Work Order Manufacturing F0006 MCMCU Business Unit Organization JDE TABLE FIELD BUSINESS TERM DOMAIN
250+ Implementations across 25 years
3,000+ Pre-built measures and KPIs
81 Net Promoter Score across our customer base
8 to 12 Weeks to production across JDE modules

The one-table ceiling

Your GL is bigger than one JDE table

Every question that crosses a module boundary turns into its own project.

The one-table ceiling Finance, operations, and everyone ask questions that cross module boundaries, each becoming its own request. Finance asks Receipts not vouchered,next to the accrual. A separate request. Operations asks Work-order cost,in the same view. Another report added to the pile. Everyone asks The AP detail behindthe balance. A number that does not quite tie.
The one-table ceiling Finance, operations, and everyone ask questions that cross module boundaries, each becoming its own request. Finance asksReceipts not vouchered,next to the accrual.A separate request. Operations asksWork-order cost,in the same view.Another report added to the pile. Everyone asksThe AP detail behindthe balance.A number that does not quite tie.

The reason is structural. It is not a failure of the tool you have, and it is not something finance should have to become technical to work around. When reporting is built on one fact table, every question that needs the second table becomes a new build, or another export to Excel.

The GL expansion

Expand it once, not once per report

The GL expansion F0902 and F0911 flow into one integrated GL model that expands to PO receipts, work orders, sales orders and AP detail. Where most JDEreporting stops Where QuickLaunchstarts Where the modelcan expand F0902GL Balances F0911GL Transactions F0902 + F0911 One integrated GL model PO receipts Work orders Sales orders AP detail
The GL expansion F0902 and F0911 flow into one integrated GL model that expands to PO receipts, work orders, sales orders and AP detail. Where most JDEreporting stopsWhere QuickLaunch startsWhere the modelcan expand F0902GL Balances F0911GL Transactions F0902 + F0911One integrated GL model PO receipts Work orders Sales orders AP detail

One GL, not two reports.

Balances and transactions are already joined and validated, so the balance and the detail behind it always agree.

Expand without rebuilding.

Adding receipts not vouchered or work-order cost extends the same model. It is not a new report project.

A foundation, not an output.

The model sits on a governed lakehouse with an enterprise semantic layer, so Power BI, data science and AI all read the same definitions.

The balance in F0902, and the F0911 transactions behind it, in one drill.

IGI Wax runs the same foundation across nine to ten JD Edwards modules, so accounts receivable reads from the same definitions as the general ledger. Machine learning on that foundation then cut waste in one production unit from 8.5% to under 3%.

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5 min Credit dispute resolution, down from two to four hours
$8-10M Additional annual profit from ML on that foundation

For the data team

The hard part is already built

Landing JDE tables in a lakehouse is the easy part. Turning them into a governed semantic model the business can query is months of work against JDE's own structures and business rules. The JD Edwards Application Pack is that work, already done.

105 JDE tables modeled. 198 relationships mapped.

Washington Companies: The Build Cost More Than the Buy

The Washington Companies had successfully operated a business intelligence environment for 18 years using SAP Business Objects. However, as business demands evolved toward modern visualization and self-service analytics, they recognized the need to adopt a unified analytics strategy that could standardize metrics across autonomous business units while respecting their independence. Washington Companies installed the full QuickLaunch solution across all modules in 12 weeks, after two builds with two different Microsoft partners failed over an 18-month period.

7JD Edwards instances on one central foundation
50%reduction in equipment idle time
30 minof training before users self-serve
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Straight answers

Questions we get

What is a JD Edwards data foundation?

A JD Edwards data foundation is a governed semantic model built on JDE’s own tables and business rules, hosted on a lakehouse such as Databricks or Microsoft Fabric. Power BI, Excel, data science and AI tools all read the same definitions from it, instead of each report defining the numbers again.

Does this get us ready for AI?

That is usually the question behind the question. A governed semantic model with business-defined measures means Copilot, Databricks Genie or an agent answers from correct joins and trusted definitions rather than guesses. Without that layer, an AI tool is reading the same cryptic tables your reports were, and guessing at what they mean.

Is this another IT project?

Not in the way that phrase usually means. The model is pre-built, so the work is configuration and validation against your data rather than a build from scratch. Washington Companies runs analytics for about 25 operating companies across seven JD Edwards instances with a five-person BI team, and users self-serve after about 30 minutes of training.

Do we have to replace the reporting tool we use today?

No. The foundation sits underneath what you already run. Most teams start with the general ledger, keep existing JD Edwards reporting and ad hoc query in place, and decide later what moves. Nothing here begins by taking something away.

How long does it take?

Deployment runs 8 to 12 weeks. Washington Companies installed the full QuickLaunch solution across all modules in 12 weeks, after two builds with two different Microsoft partners failed over an 18-month period. Later instances went live in roughly five weeks each.

What does this cost, and how is it priced?

It depends on how many JD Edwards modules you bring in and which lakehouse you run on, so there is no list price we can put on a page honestly. What we can say is that the model is licensed and pre-built rather than billed as a custom build, which is why deployment runs weeks rather than the year a custom build takes. The walkthrough covers the shape of it, with no obligation attached.

What does my team actually have to do?

Access to a JD Edwards environment, someone who knows how your business uses it, and a working cadence for validation. The model then has to be fitted to how you actually run: your account structures, your business units, the calculations finance already trusts. Some teams do that themselves once they know the model. Most do it with us. Either way it is shaping something pre-built to your business rather than building from scratch, which is why this takes weeks. Washington Companies does it across seven JD Edwards instances with a five-person BI team.

Does this work if we are on an older JD Edwards release?

Yes. The model reads JD Edwards tables directly and is maintained across releases, so an upgrade on your side does not restart the analytics work. That is the part custom builds tend to get wrong, because they are pinned to the schema as it looked on the day they were written.

Next step

Your AI is only as smart as your data foundation

Start with the general ledger. The model you build there is the one Power BI, Excel, data science and your AI tools all read from next.

Recommended next step

See the expansion done, in 20 minutes.

We will show the join, the expansion, and what it takes to stand up, on real JD Edwards structures. Screen share, nothing to prepare, no commitment on the call.

Book the 20-minute GL walkthrough

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Score your data foundation in five minutes.

15 questions across five dimensions. You get a maturity score, a breakdown by dimension and specific next steps. No call attached.

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