Sheet P-01 / Data products: reporting and machine learning
We design and deliver data products: the reports, metrics and machine learning models that turn trusted data into daily decisions. From the KPI the board watches to the forecast that sets next quarter's purchasing, each one built to production standards, with an owner, a user and a number attached.
Dashboards multiply, yet the monthly pack still takes a week to assemble and three teams still report three different margins. The forecasting model that promised so much runs on one laptop, when it runs at all. The data is there; the product is not. We treat reports, metrics and models as products built to one module: each with an owner, a user, a definition the business has agreed on, and a fixed place in the working week, so the next one is built like the last.
One of these parts will be the module, and the thickness of the columns will be equal to one module.
Executive and operational reporting in Power BI or the tool your teams already use, built on one semantic layer so every number reconciles. The monthly pack that assembles itself, the KPIs the board can drill into, and the operational views teams open every morning.
One definition of revenue, margin, churn and every other number that matters, agreed with the business, written down and enforced in the model. Three teams, one answer, and an audit trail from the figure on the slide back to the source.
Forecasting, scoring and classification models for demand, churn, pricing and risk: built where the business case is clear, validated against real outcomes, and deployed into the systems where the decision is made rather than left in a notebook.
Monitoring, retraining and change management, so reports stay correct and models stay accurate as the business moves. Every product has an owner, a service level and documentation, and your team can run it without us.
Which decision, which number, who owns it. We write the question down before anyone opens a tool, and agree the definition with the people who will act on the answer.
Reports, metrics and models built on your platform's semantic layer, to production standards: tested against real outcomes, versioned, documented and reviewed with the people who will use them.
Into the meeting, the workflow or the system where the decision is made. Monitored, maintained and handed over, with your team trained to own it.
Every product starts with the decision it serves and the person who makes it. If nobody would act on it, we do not build it.
Reports and models share one semantic layer, so the board pack, the operational view and the forecast agree with each other, and models train on data that is right.
Your analysts and engineers build alongside us. Documentation, training and hand-over are part of every engagement, so the products outlast any one employee or supplier, datalyft included.
Power BI · Python · scikit-learn · MLflow · dbt · SQL
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