Services
From scattered sources to decisions you can defend.
We work with the data you already have: SQL Server, Oracle, MySQL, flat files, exports from the systems your teams use every day, and the spreadsheets that hold it all together for now.
Start with the reporting problem. We will help you work out whether it needs a focused repair, a better data foundation, or a more complete redesign. The deliverables below are examples we scope together; not every engagement needs all of them.
01 / Data integration
Data integration
Connect the sources, agree on definitions, and organize the result in a warehouse or reporting database that other tools can trust.
Typical work: dimensional modeling, SQL Server and Oracle warehouse design, consolidating inherited Google Sheets and Excel workbooks, and reconciling numbers that disagree across systems.
Two reports show different totals, nobody is sure which database is the source of truth, or a key number lives in one person's spreadsheet.
- A source inventory: every system, export and spreadsheet that feeds a number.
- Agreed metric definitions, written down once.
- An organized reporting database or warehouse other tools can read.
- Reconciliation checks that show when two systems stop agreeing.
02 / Automation
Automation
Replace manual downloads and copy-paste with scheduled pipelines that validate data before anyone looks at it.
Typical work: Python ETL, SQL-based transformations, scheduled refreshes, validation rules with alerts, and clean-up of forms and intake processes that feed bad data downstream.
Someone spends the first hour of every day refreshing reports, or a monthly close depends on steps that only one person knows.
- Scheduled data workflows that run without a person at the keyboard.
- Validation with visible failure handling: a flag when something is wrong, never silence.
- Intake and form clean-up so bad data stops at the source.
- A documented handoff, so the process does not depend on one person.
03 / BI and visualization
BI and visualization
Dashboards and reports that start from the question, not the chart type. Built to be read quickly by the people who need to act on them.
Typical work: Tableau dashboards and governance, Python and Plotly reporting, executive and operational views, and forecasts that show a range rather than a single promised number.
You have dashboards and still get asked "so what does this mean?" in every meeting.
- The business questions written down before anything is built.
- Views built to answer them, with the next question one click away.
- Metric definitions the team agrees on and can find.
- Guidance on reading the results, so the dashboard outlives the handover.
Specialist service
Genesys BI
Contact-center reporting from Genesys data: interactions, agents, queues and historical trends, reconciled against what the floor actually experienced.
The same integration, automation and visualization discipline, applied to the platform contact centers run on.
The platform report, the warehouse and the payroll file disagree, or history disappears at the retention limit before anyone has used it.
- Interaction, agent and queue reporting with agreed definitions.
- History retained and organized beyond platform retention limits.
- Reconciliation against the platform's own numbers before anyone sees a view.
- Contact-center data joined to the outcome it produced in CRM, collections or reservations.
How an engagement runs
Listen, investigate, agree, build, support.
Listen
What you need to know, who needs it, and how it is produced today.
Investigate
Trace the sources and the manual steps to where the numbers stop matching.
Agree
Priorities, scope and what done looks like, in writing, before building starts.
Build and support
The practical version first, documented and handed over, with support as questions change.
Not sure which one you need?
Tell us what the reporting looks like today. We will help you work out which of these fits, and whether a smaller fix is enough.