EXILLAR
Data Warehouse

Your Analysts Aren't Wrong. Your Data Model Is.

Running BI queries against your production database slows the app down for real users, and the problem compounds as the business grows. Letting teams build their own gold tables means the next board meeting will include an argument about whose revenue number is correct. We build cloud data warehouses on Snowflake, Microsoft Fabric, Azure Synapse, and Databricks: properly modelled, tuned so cost tracks actual usage, and built to be extended without a refactor every six months.
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Data Warehouse
  • Kenvue

  • Harley Davidson

  • FK Pharma

  • D&K Ventures

  • Recurrent Energy

  • Amlak

  • Bravas Technology

  • Omega

  • Enhance

What Bad Warehouse ArchitectureActually Costs You

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BI reports run against the production database. The app slows down every time someone refreshes a dashboard, and it gets worse as query volume grows.
01
Every team has built its own gold table. Finance, marketing, and ops quote different revenue numbers. The post-mortem is always the same.
02
The Snowflake or Redshift bill climbs every month. Nobody can say which queries or users are responsible
03
There’s no proper dimensional model. No star schema, no slowly changing dimensions, no historical tracking. Everything is a flat export from somewhere.
04
Analysts file a ticket for every new metric because the core model isn’t stable enough to extend on their own.
05

Where Are You Starting From?

BI is running against the production database and slowing down the app
Warehouse Implementation
No warehouse yet we need the first one built properly
Warehouse Implementation
Migrating from on-prem SQL Server, Oracle, or Teradata to the cloud
Warehouse Migration
Snowflake, Redshift, or Synapse costs are climbing and we don’t know why
Warehouse Cost Optimisation
The data model is a mess, every team has their own gold tables
Dimensional Modelling and Refactor
We need historical tracking and slowly changing dimensions done properly
Temporal and SCD Design
Different teams have different revenue and customer numbers
Semantic Layer Design
Moving to a Databricks, Fabric, or Snowflake lakehouse architecture
Lakehouse Migration
What can I help with ?

    What a Well-Built Warehouse Actually Delivers

    Six outcomes, each passing the “buyer pictures a specific moment” test.

    BI stops fighting the product for resources

    BI queries stop hitting the production database. Customer-facing performance is no longer something the data team has to answer for in the standup.

    Revenue is one number again

    Finance and marketing stop arguing over the revenue number. The definition is written down, in the model, once, and it's the same definition for everyone.

    Audits stop being a weekend scramble

    An auditor asks what a customer record looked like six months ago. You pull it in under a minute, not over a weekend.

    Cost stops growing on autopilot

    The Snowflake bill stops growing independent of actual usage. Auto-suspend and resource monitors are part of the build, not something added when the invoice arrives.

    New metrics ship in hours, not weeks

    The CFO asks for a new metric on Friday. The analyst builds it by Monday because the model underneath is stable enough to extend.

    The data team builds products again

    The data team stops spending half the week unblocking analysts. They build data products. Analysts self-serve from a trusted model.

    How We Engage

    1

    Discovery and audit
    We start with a warehouse audit or discovery session, understanding your source systems, current model, query patterns, and what downstream consumers actually need before recommending anything.

    2

    Design and build in layers
    We design the target architecture, agree on modelling conventions, and build in layers (staging, transformation, semantic), with cost controls, observability, and documentation included from the first commit, not optional.

    3

    Parallel run, cutover, and handover
    We run parallel testing before cutover, migrate cleanly, and hand over with full documentation including runbooks and a clear path for extending the model without breaking what’s already there.

    Every Quarter You Leave a Broken Warehouse in Place, It Costs You More

    The longer your analysts work around a bad model, the more entrenched the workarounds become. Book a warehouse assessment and we’ll look at what you have before the next invoice cycle closes
    Book a warehouse assessment
    Round Shape

    Tools We Work With

    Cloud Warehouses
    Lakehouse Formats
    Modelling & Transformation
    Ingestion & Orchestration
    Semantic Layer & Metrics
    Legacy Sources (for migration)
    FinOps & Performance
    Microsoft Partner Stack

    What Clients Say About Working With Exillar

    Umair handled my problem timely and efficiently. He is easy to collaborate with and I will be using him again.
    Travis

    Travis Wayne Kelley

    War Room Operations | United States

    Super good explanation, patience and a good sense of indagatory about the data, sources, etc. The solutions suggested were very safisfactory.

    Héctor Raúl Rodríguez Díaz

    Fresenius Kabi | Chile

    It is always a pleasure to work with Umair and his team. Rock start service!
    Alex

    Alex Bleicker

    Asygma Ltd | Austria

    Honestly, this has been an outstanding experience from start to finish. The team went far beyond my expectations — not only did they understand a very complex real-world operation, but they were also able to translate it into a functional and well-structured system. Their communication, patience, and willingness to adapt to my requirements were truly impressive. What I appreciated the most is how committed they were throughout the entire process. They were always available, proactive, and focused on delivering real value, not just completing the task. The system works great, and you can tell there is a lot of thought and effort behind it. This is not just a basic delivery — it’s a solid, professional solution. I would 100% recommend working with them, and I’m definitely looking forward to continuing this project long-term. Great job to the entire team.
    latamsa

    Andres Garrido Assad

    Latamsa - Lavanderias Tamaulipecas | Mexico

    Excellent work as always by Umair and team. Umair and team continue to provide excellent work product. Highly recommend, responsive and attention to detail.Umair + Exillar team continue to impress and innovate as business needs evolve
    User

    Criag Peters

    D &k Ventures | United States

    Thanks for the project. If you are an Executive, you need a PowerBI dashboard. great working with the team. Many ongoing projects with Umair. Great person to work with
    Luios Philips

    Louis Philippe

    Growloup | Canada

    These guys are true professionals, they helped me improve the idea of ​​the work I wanted to develop, very kind and prepared. We will definitely do more work together. second work and I’m very statisfied.
    User

    Jacopo

    Willybesmart | United States

    Thanks for the exceptional work!
    hANS

    Hans Gildenhuys

    Industry MC | United States

    It was a great experience.

    Miguel

    Truespot | United States

    Working with Exillar has been amazing. Bhavisha has has gone above and beyond to get us what we need. Very pleased. ~Sherwin
    User

    Sherwin Loudermilk

    Loudermilk Homes | USA

    Great working with Umair, fantastic communication and excellent delivery! Would surely recommend Umair to anyone for sure! THINGS THAT WENT WELL Politeness, Delivery time, Went above and beyond, Proactive communication, Level of cooperation, Language fluency, Deep understanding, Quick responsiveness, Attention to details, Code expertise, Bug free, Exceeded expectations, Documentation. Professionalism of work.
    Wasim

    Wasim

    Visualiste Face Clinic | UK

    The guys were great to work with, very fast to reply and have a deep understanding of PowerBI. This become a learning experience for me as they shared best practices for PowerBI.
    Darcy

    Darcy

    Bravas Technology | United Kingdom

    Industries We've Worked In

    Retail & E-Commerce
    Healthcare
    Finance & Banking
    Real Estate & Construction
    IoT & Technology
    Manufacturing & Industrial

    Retail & E-Commerce

    Customer analytics, inventory forecasting, and analytics engines that reduce churn and increase basket size.

    Healthcare

    Patient data platforms, clinical reporting, and HIPAA-compliant analytics environments for providers and health-tech.

    Finance & Banking

    Real-time transaction analytics, fraud detection, regulatory reporting, and risk dashboards.

    Real Estate & Construction

    Project data consolidation, budget tracking dashboards, and supply chain analytics across multi-site operations.

    IoT & Technology

    High-volume device data ingestion, stream processing, and analytics platforms for connected product companies.

    Manufacturing & Industrial

    Operational analytics, quality control monitoring, and supply chain visibility platforms.

    Got Questions?

    Which platform do you recommend Snowflake, Fabric, or Synapse?
    It depends on your existing infrastructure, BI tooling, and team skills. If you’re Microsoft-heavy, Fabric or Synapse will usually win on integration and licensing. If you’re cloud-agnostic and want the most mature warehouse ecosystem, Snowflake is hard to argue against. We recommend based on your situation, not ours.
    Both. Inheriting an existing warehouse and either extending or refactoring it is a significant part of our work. We’ll assess what’s salvageable and what needs rebuilding before we touch anything.
    With parallel running. We build and test the new environment alongside the existing one, validate outputs, and cut over with business agreement. We don’t flip a switch and hope.
    That’s a design constraint, not an afterthought. We write documentation, create runbooks, follow modelling conventions your team can extend, and build nothing that requires us on call permanently.
    EXILLAR