Integration
Your data sources talk to each other. There’s a single place to ask questions, not five systems that disagree.
A real data strategy answers three questions before anyone builds a dashboard: what should we measure, where does the trustworthy version of that data live, and who owns it. Get those right and everything downstream gets faster.
Most teams don’t have a data strategy. They have data chaos
- Reports break the moment source data changes.
- You build the same dashboard three times because nobody knows how to share data.
- Month-end reconciliation takes days because nobody trusts the numbers.
- Your BI team spends half its time firefighting instead of building.
What good data strategy looks like
Governance
When a report says revenue is $2M, everybody believes it. Shared definitions, ownership, and standards for your core metrics.
Scalability
Your foundation scales from 1M rows to 500M without a rebuild. It’s designed for where you’re going, not just where you are.
Common engagements
Clear, scoped ways to start, each with a defined timeline and outcome.
Data Audit & Roadmap
We map your current data landscape and hand back a prioritized, phased roadmap you can act on immediately.
Data Consolidation
Bring data from 3 to 5 systems into one consistent place, with hands-on team enablement so your people can own it.
Data Warehouse Design
Design and build a dimensional model engineered to scale from 1M to 500M+ rows without a costly rebuild later.
Data Strategy
- The plan: what to measure, how it’s governed, and the sequence to get there
- Lightweight, and it starts delivering value in weeks
- Aligns people and definitions before you touch tools
- Answers “what should we build, and why”
Data Warehouse
- •The build: a dimensional model engineered for scale and speed
- •Heavier: a multi-week engineering effort
- •Follows the strategy, not the other way around
- •Answers “where does the data physically live”
You need the strategy first. A warehouse is one possible output of it, never a substitute for it.
Tools & platforms
SQLTableauPower BICloud Data PlatformsDimensional ModelingETL/ELT
What good looks like
- Everyone agrees on what the core numbers actually mean.
- A clear, funded roadmap instead of endless ad-hoc requests.
- Fragmented systems connected into one consistent view.
- A foundation that scales with you. No painful rebuild later.
“The data challenges resulted in several revisions to thinking around which data elements to include and how to present the data. Fred served as a great thought partner and was patient and flexible as we revisited our decisions.”
Frequently asked questions
- What is a data strategy, exactly?
It is the set of decisions you make before anyone builds a dashboard: what you should measure, where the trustworthy version of that data lives, and who owns it. Get those right and everything downstream gets faster.
- How long does a data strategy engagement take?
A data audit and roadmap usually runs 2 to 4 weeks, consolidating 3 to 5 systems runs 4 to 8 weeks, and a full data warehouse design runs 8 to 16 weeks. We scope the right starting point with you first.
- Do we really need a data warehouse?
Not always. A warehouse earns its place when you have several systems that disagree or data volumes a spreadsheet model cannot handle. We recommend one only when it clearly pays off, and we tell you if it does not.
- Where do you start if our data is a mess?
With a data audit. We map your current sources, metrics, and ownership, then hand back a prioritized roadmap you can act on immediately, so the cleanup happens in the right order.
Related work
Strategy and governance underpin every dashboard we ship. The reporting systems in our success stories all sit on a defined metric model and integrated data sources. It’s the same foundation this work delivers.
Explore our success stories