Executive and operational dashboards
Role-specific dashboards in Power BI or custom web interfaces that show the handful of measures each team needs, with drill-downs to the underlying records.
Data Analytics
Data analytics solutions that end the argument over whose numbers are right
We build the pipelines, data models and dashboards that turn scattered exports into a single, governed view of performance. Metrics are defined once, refreshed on schedule and traced back to their source, so weekly reviews focus on decisions instead of reconciling spreadsheets.
- Core capabilities
- 6
- Step delivery process
- 5
- Case studies
- 6
Overview
At a glance
Data pipelines, KPI systems and dashboards that give leadership one set of numbers to run the business on.
Data analytics covers everything between the systems where your data is created and the decisions made from it: extracting records from CRMs, ERPs, billing platforms and ad accounts, cleaning and modeling them in a warehouse, defining metrics consistently, and presenting the results in dashboards and reports people actually open. The goal is not more charts. It is fewer, better numbers that leadership, finance and operations all agree on.
This work fits companies that have outgrown spreadsheet reporting: month-end packs that take days to assemble, KPIs that change depending on who pulled them, and simple questions that go unanswered because the data lives in several places. It also fits teams preparing for AI or machine learning projects, which depend on the same clean, well-modeled data.
We begin discovery with decisions, not tools. Which questions does each team need answered, how often, and what would they do differently with the answer? From there we audit data sources and quality, agree on metric definitions in writing, and set measurable targets such as refresh frequency, report delivery times and reconciliation against finance figures. Pipelines are built with tests and freshness alerts, access is controlled by role, and personal or sensitive fields are masked or excluded unless there is a clear reason to include them.
Engagements usually deliver in slices. The first release covers one domain, such as sales pipeline or revenue, end to end from source to dashboard, so you see value early and we validate the data model with real users. Additional domains follow on the same foundation. We document every metric and pipeline, train the people who will maintain reports, and can stay on to monitor data quality and extend the platform as your questions change.
Business problems solved
Where it pays off first
The operational bottlenecks Data removes for growing teams.
- Solved
Every team reports a different number
Sales, finance and operations each pull figures from their own tools, so meetings start with reconciling metrics instead of deciding what to do about them.
- Solved
Month-end reporting eats days of analyst time
Analysts export CSV files, paste them into spreadsheets and rebuild the same charts every cycle, leaving little time for the analysis the business actually needs.
- Solved
Dashboards nobody trusts or opens
Reports built directly on raw tables break silently when a source changes, and after a few wrong numbers people stop using them altogether.
- Solved
Data scattered across disconnected systems
Customer, order, marketing and financial data live in separate platforms with no shared identifiers, which makes basic cross-functional questions hard to answer.
Capabilities
What our Data work covers
Modular building blocks we combine into a solution that fits how your team already works.
KPI systems and metric definitions
Documented definitions for revenue, margin, retention, pipeline and operational KPIs, implemented once in the data model so every report calculates them the same way.
Data pipelines and warehousing
Scheduled, tested pipelines that bring data from your CRM, ERP, billing and marketing platforms into a cloud warehouse, with alerts when a load fails or data goes stale.
Business intelligence
Modeled data and self-service BI that let managers explore trends, segments and cohorts on their own, without filing a request for every new question.
Reporting automation
Weekly performance summaries, board packs and client reports generated and distributed on schedule, replacing hours of manual exporting and formatting.
Data visualization
Charts and layouts designed around the decision they support, with clear comparisons and annotations that explain what changed and why it matters.
How we deliver
A clear path from idea to production
Every Data engagement follows the same transparent, milestone-driven process.
- 01
Decision and data audit
We interview stakeholders about the decisions they make, inventory data sources, and assess quality, gaps and access constraints.
- 02
Metric definitions and data model
KPI definitions are agreed in writing and translated into a warehouse model designed for accuracy, performance and the questions that come next.
- 03
Pipeline build
We build tested, scheduled pipelines with freshness monitoring and reconcile key figures against finance and source systems.
- 04
Dashboards and reporting
Dashboards and automated reports are built with the people who will use them, then refined based on how they hold up in real reviews.
- 05
Adoption and handover
We document metrics and pipelines, train report owners, and set up ongoing data quality checks so trust in the numbers lasts.
Use cases
What teams build with it
Representative scenarios — every build is scoped to your data, systems and goals.
Use case 01
Unified revenue and pipeline reporting
CRM, billing and finance data are modeled together, so leadership sees bookings, revenue and forecast from one source with numbers that tie back to the ledger.
Use case 02
Automated month-end management pack
The monthly performance pack refreshes and distributes itself, so finance spends close week reviewing variances rather than building slides.
Use case 03
Marketing spend and attribution view
Ad platform, web analytics and CRM data are joined to show cost per qualified lead and channel contribution, so budget shifts rest on evidence.
Use case 04
Operations KPI monitoring
Fulfillment, service level and throughput metrics refresh through the day, with alerts when a measure drifts outside its agreed range.
Technology
Tools we build with
Proven, well-supported technology — chosen for your stack, not our preferences.
- Backend
- Python
- Databases
- PostgreSQL
- Cloud
- AWS
- Google Cloud
- Data & BI
- Apache Airflow
- dbt
- Power BI
FAQ
Questions about Data
Do we need to replace our existing BI tools or data systems?
Usually not. We keep what is serving you, whether that is Power BI, a cloud database or a set of well-used spreadsheets, and add what is missing, which is most often a proper data model and reliable pipelines. We recommend new tools only when the current ones cannot meet a clear requirement such as data volume, refresh frequency, access control or cost.
What if our data is messy or incomplete?
Most companies' data is, and it is not a reason to wait. During discovery we profile each source for gaps, duplicates and inconsistent definitions, then decide what to clean in the pipeline, what to fix at the source and what to flag clearly in reports. Data quality indicators sit alongside the metrics themselves, so everyone knows how far to trust each number.
How quickly can we have a working dashboard?
A first dashboard covering one domain, such as sales pipeline or revenue, typically takes a few weeks from kickoff, depending on how many sources are involved and how clean they are. We deliberately start narrow so the data model is validated with real users before we expand. Later domains move faster because they build on the same pipelines and metric definitions.
How do you handle access to sensitive financial and customer data?
We apply least-privilege access from the start:
- Read-only credentials for source systems wherever possible
- Role-based permissions in the warehouse and dashboards, with row-level security when teams or clients should see different data
- Personal and sensitive fields masked or excluded unless a report genuinely needs them
Credentials live in a secrets manager, and at the end of an engagement all access is removed or transferred to you.
Start a project
Tired of reconciling reports before every meeting?
Walk us through the decisions you need data for and where that data lives today. We'll outline a data model, a first dashboard release and what it takes to keep the numbers trustworthy.