Data Engineering & Analytics
Your sales system says one number, accounting says another and the spreadsheet says a third. We pull every source into one warehouse, clean it once, and build dashboards that answer the questions you ask every Monday.
every system agrees
dashboards, not monthly decks
clean data for forecasting
Everything a data engineering & analytics project covers.
Pull data from every system into one clean warehouse and put dashboards on top that answer the questions you actually ask on Monday morning.
Data pipelines and a central warehouse
Dashboards for owners, managers and investors
Cleanup and consolidation of messy data
AI-ready data for forecasting and automation
Four steps, working software every week.
A fixed price, a written plan and weekly builds you can try. Here is how it plays out for data engineering & analytics.
List the questions
What do you need to know daily, weekly, at board meetings. Dashboards are designed backwards from those.
Connect the sources
Pipelines from your CRM, accounting, eCommerce, spreadsheets and apps into one warehouse.
Model and clean
Customers deduplicated, products matched, definitions agreed. One version of the truth.
Dashboards and alerts
Role-based dashboards, scheduled reports and alerts when a number moves.
What do you need? See a timeline instantly.
Tick the pieces of your project. The estimate updates as you go, and you can send it to us with one click.
What we build with, and who we build it for.
Technology we typically use
Industries we have done this for
Healthcare & Medical
Patient portal with online intake
Private Equity
Portfolio reporting dashboards
Logistics & Distribution
B2B ordering app
Retail & eCommerce
Online store connected to your POS
Non-Profit & Government
Donor and member management
Engineering & Architecture
Project and drawing management
Science & Research
Sample, inventory and data management
Manufacturing
Production and order tracking
Things people ask about data engineering & analytics.
Our data is a mess. Can you still help?
Messy data is the normal starting point. Cleanup and matching is a defined step in every project, and we document the rules we used.
Which BI tool do you use?
We use what your team will open: Metabase, Looker Studio, Power BI or a custom dashboard inside your own app.
Can we use AI on our data?
Yes, once it is clean and in one place. Forecasting, anomaly alerts and a chat assistant that answers questions from your data are common follow-on projects.
Ready to talk about data engineering & analytics?
Tell us what you have today and what is not working. We reply within one business day with a plain-language plan.