Data Warehouse & Engineering
From Excel Hell to Data You Can Rely On
Allston Yale provides data warehouse consulting and data engineering services for mid-market companies in Texas and across the USA. We build the warehouse or lakehouse and the pipelines beneath your reporting, so data lands where it should, on schedule and ready to use.
01
Life After Excel Hell
Most mid-market reporting still runs on spreadsheets stitched together by hand every month. It works until it does not: a broken formula, a version nobody can find, a number two people calculate differently. A real data foundation ends that monthly scramble for good.
02
Why Good Reporting Needs a Real Foundation
A dashboard is only as trustworthy as the data underneath it. Without a proper warehouse and pipelines, even a beautiful report is guessing, pulling from sources that do not agree and refreshing whenever someone remembers. The foundation is what makes the reporting believable.
This is the unglamorous half of analytics, and the half that decides whether the rest holds up. Get it right and the dashboards above it simply work; get it wrong and no amount of visual polish will save them.
03
How We Build Your Warehouse and Pipelines
We start from the decisions your reporting needs to support, then design the smallest warehouse or lakehouse that delivers them reliably. We build the pipelines that feed it, reconcile the sources, and schedule the refreshes so the data arrives on time without anyone touching it.
Along the way we document how everything fits together, so a lean team can run and extend it later. The goal is data engineering your own people can maintain, not a black box that only we understand.
04
Pipelines That Run Without You
The point of the plumbing is that you stop thinking about it. Once the pipelines are built, data moves from source to report on schedule, month-end assembly disappears, and your team spends its time acting on numbers instead of producing them by hand.
05
Warehouse, Lakehouse, or Both?
Not every business needs the same architecture. A classic warehouse suits clean, structured reporting; a lakehouse handles messier and larger data; and many mid-market teams end up with a blend. We recommend the data warehouse solutions that fit your data and budget, not the trendiest option.
06
Right-Sized, Not Over-Engineered
It is easy to build a platform far larger than a mid-market team can maintain. We deliberately do the opposite, sizing the warehouse and pipelines to your real workloads, so you get reliability without paying for capacity and complexity you will never use.
07
Built on Power BI and Microsoft Fabric
We build on Microsoft Fabric, where the lakehouse, warehouse, and pipelines live in one platform, with Power BI reporting on top. Whether you are consolidating in Fabric or extending an Azure data warehouse you already run, see our Microsoft Fabric consulting and Power BI consultant pages.
08
Industry Experience
We provide data warehouse consulting across the industries we serve, from oil and gas, energy, and manufacturing to healthcare, financial services, insurance, construction, and retail. Each brings its own data sources and volumes, and the right foundation looks different for each.
That context saves time. We arrive knowing the systems your sector runs, from ERPs and historians to claims and point-of-sale, so the pipelines connect to the real sources feeding your business rather than a generic template.
What working with Us Looks like
Clients often expect data engineering to be an endless, invisible project. Ours is meant to be scoped, delivered, and handed over, leaving you with a foundation that quietly works and a team that knows how to keep it running.
32%
INCREASE IN DECISION SPEED
27%
REDUCTION IN OPERATIONAL COSTS
2.4x
INCREASE DATA UTILIZATION
96%
DATA ACCURACY IMPROVEMENT
Data-Driven Demand Forecasting with Analytics Data Platform
Analytics Data Platform Facilitating a Greener Future
Common Questions
Do we need a data warehouse, or is Power BI enough?
It depends on your data. A small, clean setup can live in Power BI alone for a while. Once sources multiply or refreshes get slow and fragile, a proper warehouse or lakehouse underneath is what keeps the reporting fast and trustworthy.
What is the difference between a warehouse and a lakehouse?
A warehouse stores clean, structured data ready for reporting; a lakehouse also holds raw and unstructured data at larger scale. Microsoft Fabric supports both, and we pick the mix that fits your data rather than forcing one pattern on everything.
Will this stop our manual month-end reporting?
That is usually the first win. Once the pipelines are built and scheduled, the data assembles itself, so the month-end copy-paste marathon gives way to reports that are simply ready when your team opens them.
Can our small team maintain it afterward?
Yes, by design. We size the build to a lean team and document how it works, so your people can run and extend the warehouse without depending on us. Independence is the point, not a permanent retainer.
Talk to Us About Your Data
If your reporting rests on spreadsheets or refreshes that break more often than they should, a short conversation will show what a real foundation would change. Book a time and we will map what it would take to build it.
