Data Engineering
Pipelines that deliver correct data on time, every time.
Cloud, Data & Reliability
Stop arguing about whose spreadsheet is right
When three departments calculate revenue three ways, every meeting starts by reconciling numbers instead of deciding anything.
- Engagement
- Phased implementation project
- Typical timeline
- 8–16 weeks
- Delivered across
- All 50 US states
Overview
The symptom is familiar: an analyst spends the first week of each month assembling a report from six systems, executives receive it late, and someone questions a number that turns out to be defined differently in another team's version. The underlying problem is that no single definition of the business's core metrics exists anywhere authoritative.
We build the layer that fixes it. A data warehouse consolidating your sources, a modeling layer where metrics are defined once in version-controlled code, and dashboards that read from that shared definition. When someone asks how revenue is calculated, there is a documented answer rather than a debate.
The goal is self-service. Dashboards that answer standing questions without an analyst, with governed data access so people can explore without producing contradictory numbers. That frees analysts to do actual analysis rather than assembling recurring reports forever.
- Typical reporting cycle compression
- Days→minutesTypical reporting cycle compression
- Metrics defined once, in version control
- One definitionMetrics defined once, in version control
- Standing questions answered without an analyst
- Self-serviceStanding questions answered without an analyst
Business benefits
What business intelligence changes for you
The reasons this work earns its budget, stated as outcomes rather than features.
A single source of truth
Consolidated warehouse with metrics defined once in code, so every dashboard and report agrees by construction.
Automated data pipelines
Scheduled, monitored ingestion from your systems, eliminating manual exports and the errors that come with them.
Dashboards by role
Executive summaries, operational detail and analyst exploration each designed for their audience rather than one report for everyone.
Data quality monitored
Automated tests on freshness, completeness and consistency, so problems surface before they reach a board deck.
Governed self-service
Role-based access to explore safely, with certified datasets that prevent the proliferation of conflicting analyses.
Documented and maintainable
Lineage, definitions and transformations documented, so the system survives the departure of whoever built it.
Problems solved
If any of this sounds familiar
These are the situations clients describe in the first conversation, and what we do about each.
“Month-end reporting takes a week of manual work.”
Automated pipelines and pre-built reporting so the cycle becomes review and interpretation rather than assembly.
“Departments report different numbers for the same metric.”
A shared semantic layer with metrics defined once, documented and version-controlled, ending the reconciliation problem at its root.
“Every question requires an analyst and a two-day wait.”
Self-service dashboards for recurring questions with governed exploration, reserving analyst time for genuinely new questions.
“We do not trust the numbers in our dashboards.”
Automated data quality testing, documented lineage and a reconciliation process against source systems to rebuild confidence.
Our process
How we deliver it
Each stage has a defined output, so you always know what you are getting and when.
- 01
Requirements and metric definition
Identify the decisions BI must support and agree precise definitions for each core metric with the teams that use them.
- 02
Data architecture
Source inventory, warehouse design, pipeline architecture and refresh strategy sized to real requirements.
- 03
Pipeline build
Ingestion, transformation and testing implemented as version-controlled, monitored code.
- 04
Modeling and dashboards
Semantic layer built and dashboards designed by audience, reviewed with the people who will use them.
- 05
Enable and iterate
Training, documentation and an ongoing cycle of adding sources and metrics as the business asks new questions.
Technologies used
The tools behind the work
Chosen for maintainability and hiring depth rather than novelty. We will justify any choice on request, and we avoid technology that makes you dependent on us.
- Snowflake
- BigQuery
- dbt
- Fivetran
- Airbyte
- Power BI
- Looker
- Metabase
- Airflow
Industries served
Where this work lands most often
Sector context changes what good looks like. These are the industries where we have delivered this service repeatedly.
Why Mova
What working with us on business intelligence is like
The same commitments apply to every engagement, regardless of size or service.
A defined first step
We scope a fixed-price starting point so you can evaluate us on business intelligence before committing to a program.
Senior people, named
The team you meet is the team that delivers. You will know exactly who is accountable.
You own the output
Code, accounts, files and documentation are yours from day one, with no lock-in of any kind.
Measured, then reported
We baseline before starting and report against it honestly — including the months that fall short.
Questions
Business Intelligence: common questions
The questions we are asked most about business intelligence, answered directly.
If you regularly combine data from more than two or three systems, yes. Below that, direct connections and a good BI tool are often sufficient and considerably cheaper to run.
More in Cloud, Data & Reliability
Keep exploring
Related services
Analytics
Measurement you can act on and defend.
Machine Learning Solutions
Prediction, classification and forecasting on your own data.
ERP Development
Operational backbones that fit your business, not a template industry.
Business Consulting
Operating problems solved with evidence and follow-through.
Next step
Ready to talk about business intelligence?
Thirty minutes with someone who has delivered this work. We will tell you what it would take, roughly what it would cost, and whether Mova is the right fit.
No pitch deck. A 30-minute conversation about what you are trying to achieve.