Data Warehouse Consulting: One Reliable Source Behind Every Report

Data warehouse consulting helps you decide whether you need a data warehouse, then design and build it: a central database, modeled for reporting, that pulls data from your operational systems on a schedule, cleans and matches it, and keeps history. Lightray Solutions designs and builds warehouses on Microsoft platforms, and Edward Pinela, MBA, does the work from assessment to handover.

A warehouse is plumbing. Nobody looks at it directly. It exists so that every Power BI report, forecast and AI project reads from the same trusted numbers.

Warehouse projects have no list price; each phase is quoted in writing after the assessment, and platform costs are billed by Microsoft. Your first step is a free 30-minute strategy call with Edward, set up personally once you send the form or call, where you will hear honestly whether a warehouse is worth building yet.

Do you actually need a data warehouse?

Many small businesses do not, at least not yet. If your reporting draws on one or two clean systems, a well-built Power BI model can do the shaping itself. A warehouse earns its cost when several systems must be combined, codes must be matched between them, or you need history that the source systems overwrite.

Microsoft's Power BI guidance points the same way: for large volumes or history tracking, load a data warehouse on a schedule and point Power BI at it. You probably need one when several of these are true:

• Reports combine three or more systems, such as ERP, CRM, accounting, e-commerce or payroll
• The same customer, product or location has different codes in different systems
• You need history the source systems overwrite, such as which territory a customer belonged to last year
• Power BI refreshes are slow because every model reshapes the same raw data
• Several teams build reports, and their numbers do not agree
• You plan forecasting or AI work and need clean, governed data to start from

What does data warehouse consulting include?

An assessment and written recommendation first, then, if a warehouse is justified, the design and build: a dimensional model, shared customer and product lists, history tracking, scheduled pipelines, data quality checks, security and documentation. The scope follows your systems, and every piece is built in your environment. In detail:

• Assessment. An inventory of source systems, data quality, volumes, reporting needs and pain points, ending in a written recommendation. That recommendation may be that you do not need a warehouse yet.
• Dimensional model design. Fact tables for events such as orders, invoices and shipments, and dimension tables for customers, products, dates and locations. This star schema design is what Microsoft recommends as the basis for enterprise Power BI semantic models.
• Shared dimensions. One customer list and one product list used by every subject area, with mapping tables where systems use different codes.
• History tracking. Slowly changing dimensions, so reports can show last year's figures as they were, not as they look after this year's edits.
• Data pipelines. Scheduled extract, load and transform jobs from each source, with staging, error handling and logging.
• Data quality rules. Checks for duplicates, missing values and unmatched codes, with exceptions reported instead of silently dropped.
• Security and documentation. Access roles, a data dictionary, and a trail from each report figure back to its source.

Which platform should the warehouse run on?

We build on Microsoft platforms and choose the one that fits your data, your team and the licenses you already own. There is no single right answer, and the cloud is not automatically better. The table below compares the options we most often recommend.

If you already run a warehouse on another platform, we will tell you on the first call whether we are the right people to extend it.

How does a data warehouse project run?

One subject area at a time, in four steps: assessment and roadmap, design of the first subject area, build and reconciliation, then connecting Power BI and handing over. Starting with the area that matters most, usually sales or finance, puts working reports in front of you early and lets each later area reuse what was already built.

• 1. Assessment and roadmap. Sources, quality, volumes and priorities reviewed, with a written recommendation and a phased plan.
• 2. Design one subject area. Usually the one that hurts most, such as sales or finance, modeled and agreed with the people who own those numbers.
• 3. Build, load and reconcile. Pipelines built, history loaded, and totals reconciled against your system reports before anyone relies on them.
• 4. Connect reporting and hand over. Power BI semantic models pointed at the warehouse, documentation delivered, and your team trained to run the loads and extend the model. The next subject area reuses the same customer, product and date dimensions, so each addition builds on the last.

When is a data warehouse not the right fit?

If you have one main system with its own reporting module, or a few clean sources and a Power BI model that refreshes comfortably, a warehouse adds cost and one more thing to maintain without much benefit. Strengthening the Power BI model is the better first step, through our Power BI consulting services.

And if nobody in your organization will own the warehouse after launch, plan that ownership, or ongoing support, before you build.

If you need data engineering, streaming data and data science alongside the warehouse, a broader Microsoft Fabric implementation may be the right scope. If your immediate problem is moving an on-premises database to the cloud, see Azure cloud migration services.

Why work with Lightray Solutions on your data warehouse?

A warehouse is only worth building if the reports on top of it get used. Edward Pinela, MBA, designs it with the Power BI reports in mind, since he builds those too, and knows how CRM and ERP data behaves at the source. He has 20+ years of experience and 200+ delivered projects; Lightray is rated 4.9★ on Google.

• An honest assessment. If you do not need a warehouse yet, you will hear that before any build is quoted.
• Built in your environment. The warehouse, pipelines and documentation live in your tenant and belong to you.
• No long-term contracts. Each phase is scoped and approved on its own.
• Straight answers. Every question gets a reply within 4 business hours, written by the consultant building your warehouse.

Further reading: Microsoft Learn — Dimensional modeling in Microsoft Fabric Warehouse.