Reporting · Analytics · Engineering
We help finance teams replace manual spreadsheets and fragmented data with reliable reporting and practical automation.
Book a 30-minute Google Meet conversation. A practical place to start.
Connected. Checked.Prepare · Validate · Automate01 / What we do
From one recurring spreadsheet to a connected data workflow. A focused scope, with room to grow.
Turn monthly preparation into a dependable workflow your finance team can use.
Bring scattered sources together and make business performance easier to understand.
Address high-friction operations with a tailored data or AI workflow.
Not sure where to start? Let’s identify your biggest bottleneck.
Book a discovery call02 / Why work with us
Built on our founder’s experience in data engineering and analytics across retail, financial services, asset management, and climate analytics. We connect what your business needs with what the data can do.
Meet your consultant
I’m the founder of Klarity Data. I’ve worked in data engineering, analytics, and finance reporting across retail, financial services, asset management, and climate analytics.
I enjoy helping people make sense of complex data and find practical ways to improve how they work. Alongside a team of 2–5 data professionals, I help organizations use data and AI to make better decisions, automate everyday tasks, and build solutions that can grow with them.
Experience with monthly finance reporting, vendor reconciliation, and investment performance data helps us connect technical work to real business questions.
Python, SQL, distributed pipelines, Databricks migrations, and Spark tuning provide a path from a focused reporting fix to a more connected workflow.
Direct collaboration from requirements and scope through implementation and deployment, with clear deliverables and an agreed way to validate them.
Where we’ve worked
Kelvin’s experience ranges from data analysis to senior data engineering. He has worked in enterprise retail and investment management environments, bringing a practical understanding of reporting, data pipelines, and the needs of the people who use them.
Experience includes prior professional roles and project work. Organization scale describes the wider business, not project budgets. Names and identifying details are kept confidential.
03 / Selected experience
Examples from our founder’s professional experience, including work before Klarity Data. Names and identifying details are omitted.
REPORTING AUTOMATION
The challenge: A recurring reporting process required repeated extraction, spreadsheet preparation, and reconciliation.
Estimated annual effort avoided
~208 hoursEstimated repetitive work avoided per year in the specific workflow.DATA ENGINEERING
The challenge: Large recurring datasets needed consistent transformations for monthly reporting.
PERFORMANCE ENGINEERING
The challenge: A processing bottleneck was delaying a Spark workload’s output.
Figures reflect the specific prior work described in our experience records. Annual time saving is an estimate; results depend on scope, data, and the starting workflow.
Have a similar challenge? Let’s find your next step.
Book a discovery call04 / How we work
Work directly with a technical consultant who understands the data and the business problem.
Map the bottleneck, sources, stakeholders, and the outcome you need.
Agree on deliverables, timeline, price, and acceptance criteria before building.
Build, validate against real workflows, document, and hand over a usable solution.
05 / Let’s talk
Tell us what takes too much time, where your data gets stuck, and what better would look like. We’ll discuss the fit and a practical way forward.
Opens the Google Calendar booking page for a 30-minute call.