Azure Solutions Architect
Azure Data Expertise You Can Count On
Azure gives a mid-market business the same data infrastructure the largest enterprises run on. The catch is that it hands you the parts, not a finished platform. Allston Yale is a Microsoft data consultancy for the $50M to $100M companies, in Texas and across the USA, whose lean IT teams need that platform running without an enterprise-sized department to run it.
01
Custom-Fit Azure Data Solutions
Nearly all the Azure advice out there assumes a dedicated cloud team on the receiving end of it. That is not who we build for. Our clients are the people running data alongside three other jobs, and our work is to get Azure and Power BI set up right the first time, so their days go to decisions and not to chasing broken pipelines.
02
What Microsoft Azure Consulting Actually Involves
“Azure” covers hundreds of services, but a data team only needs a handful of them to matter: Azure SQL for the databases, Data Factory to move data around, Synapse and Data Lake Storage for scale, Databricks when the workloads get heavy, and Purview to keep the whole thing governed. Consulting is the work of turning that toolbox into one platform that mirrors how your business runs, rather than a pile of subscriptions you were handed and left to wire together.
In practice that means designing the ingestion, the databases, and the warehouse, structuring the lake, building the transformations, putting governance in place, and wiring up the Power BI layer your team lives in. The less glamorous calls get made too, the ones that sink more projects than any technical failure: which capacity tier to size to, how to keep the monthly bill predictable, how to lock it down.
One clarification, because it matters here. We are a data and analytics shop, not a general cloud infrastructure firm. The services that turn raw data into decisions are where we go deep. When a job calls for networking, app hosting, or anything outside that lane, we say so and bring in the right people rather than stretch to cover it.
03
Built for Lean Teams, Not Big Departments
Restraint is the whole difference in a mid-market build. A fair share of the value we add is talking clients out of services they will not use and architectures they could never maintain. We size to the workloads you actually run, lean on the fewest moving parts that do the job, and write everything down so a small team can take the keys the day we leave.
None of it is a black box. Every pipeline, database, and workspace comes with an explanation and a proper handover, because a platform you cannot run without us is not much of an asset. What you are left with is a system your own team drives with confidence, and a consultancy you could part ways with tomorrow and be fine.
04
Microsoft Azure Implementation and Ongoing Support
Some engagements start on an empty Azure tenant. More of them start with a decade of SQL, SSIS packages, and spreadsheets that still run half the business. The sequence holds either way: understand what is there, design where it should end up, move the data and the reports, and prove the numbers still tie out before anyone trusts a dashboard again.
How far we go after launch is up to you. Some clients keep us on to run the whole platform; others want an occasional architecture review, or a number to call when they hit something unfamiliar. You set the level of involvement. Our part is making sure nothing important is ever left without an owner.
05
Industry Experience
Oil and gas, energy and utilities, manufacturing, healthcare: these are the sectors that anchor the Texas economy and reach well past it, and most of our work lives among them. A production feed, an insurance claim, and a job-cost ledger are nothing alike as reporting problems, and treating them as though they were is how generic builds come apart.
A plant-performance platform for a manufacturer shares almost nothing with a claims model for an insurer or a project-margin view for a builder. We turn up with patterns shaped by your sector, not a template with your name dropped into it.
06
Azure and Fabric, Together
Worth clearing up a common mix-up: Azure and Microsoft Fabric are not rival products you pick between. Fabric runs on Azure, and Microsoft has made it the front door for analytics from here on. The real question is one of division of labor, which workloads stay in the classic Azure data services and which are better served by Fabric, and how to cross between them without breaking things in transit.
We treat that as one strategy rather than two. Where your Azure estate is pulling its weight, we build on it and leave it alone. Where Fabric would fold a tangle of Synapse, Data Factory, and Power BI into a single place, we will make the case, and we will be equally clear about the times the move would cost more than it gives back today.
Working out whether Synapse or Fabric should own a given workload, or how Azure SQL and Power BI ought to sit together? We have laid those out in plain language, our guides on Microsoft Fabric vs Azure SQL and Power BI vs Azure, and we are always happy to reason through it with you first.
What working with Us Looks like
People tend to find us after a stretch of pipelines that fail overnight and reports the leadership team has stopped believing. The ask is rarely complicated: numbers they can trust, without a fight to produce them. The systems we hand back are built to run without drama and to hold up over time, which counts for far more than how they photograph in a pitch.
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
How much does Azure cost to run for data and analytics?
Azure charges for what you use. Compute, storage, and data movement across services like Azure SQL, Data Factory, and Synapse each meter on their own, so the bill tracks your real usage. Keeping it sensible comes down to sizing every service to actual demand and switching off whatever sits idle, and we build that model with you before you sign up for anything.
How long does an Azure data implementation take?
A tight first phase, one or two priority workloads live on Azure with Power BI over the top, usually lands in a matter of weeks. Larger migrations run in stages after that, so you see something working early rather than holding your breath for a single all-or-nothing launch.
Should we use Azure or Microsoft Fabric?
Usually both. Fabric sits on Azure and draws analytics into one platform, while plenty of capable services still live in classic Azure. We help you sort which workloads belong where, protect what already works, and shift to Fabric only where the change earns its keep, including the times when the smart move is to stay exactly where you are.
Do we need to leave Power BI behind to modernize on Azure?
Not at all. Power BI runs on top of your Azure data, so the reports and skills your team already has carry straight over. More often than not we are reinforcing what you have and setting a cleaner foundation beneath it, rather than asking anyone to start from scratch.
Talk to an Azure Consultant
Whether you are still sizing up Azure or already mid-build and after another set of eyes, ten minutes of conversation beats another deck. Book a time, and we will talk through what you are dealing with and where Azure is worth it for you.
