Data that holds up under scrutiny on Effective Data Consulting

Services for Enterprises

Mon, 01 Jan 0001 00:00:00 +0000

The same five services we offer every client, framed for the constraints of a large organisation: existing platform commitments, security and compliance review, and change that has to be sequenced against budget cycles.

Engagements typically begin with a fixed-scope assessment, which gives both sides an evidence base before committing to a larger statement of work.

Services for Startups

Mon, 01 Jan 0001 00:00:00 +0000

The same five services we offer every client, framed for the constraints of an early-stage company: limited engineering capacity, a foundation that has to be extensible rather than complete, and a budget that has to justify itself.

Most early engagements start with strategy or advisory, and expand into architecture once the sequence is clear.

Approach

Mon, 01 Jan 0001 00:00:00 +0000

Most consulting engagements fail in predictable ways: scope that was never specific, a deliverable nobody owns afterwards, or a recommendation that could never have been implemented in the environment it was written for. The structure below exists to close those gaps.

1. Scoping conversation

An hour, no charge, no obligation. We want to understand the actual problem, which is often not the one in the initial email. If we are not the right fit — or if the work does not need an outside party at all — this is where we say so.

About

Mon, 01 Jan 0001 00:00:00 +0000

The practice

Effective Data Consulting is a data and AI consultancy working with startups and established enterprises. We take on strategy, architecture, governance, and implementation work — usually some combination, because the boundary between advice and delivery is where most consulting engagements fail.

We are deliberately small. Engagements are led by the person doing the work, not handed to a delivery team after the sale.

Principal

Paul Raff leads the practice. He has worked on data and machine learning systems at both large enterprises and early-stage companies, which is the reason the two tracks on this site exist: the constraints are genuinely different, and advice that ignores that is not worth much.

Contact

Mon, 01 Jan 0001 00:00:00 +0000

The first conversation is an hour, no charge, and no obligation. If we are not the right fit we will say so, and where we can we will point you somewhere better.

Email

raff@effectivedataconsulting.com

To make the first exchange useful, it helps to include:

What you are trying to accomplish, in business terms rather than technical ones
Where you are now — team size, current stack, what has already been tried
What is forcing the timing — a launch, an audit, a funding round, a migration
Your timeline, even approximately

None of it is required. A single paragraph is a fine place to start.

Why metric definitions drift, and what actually stops it

Sun, 19 Jul 2026 00:00:00 +0000

A familiar situation: two dashboards report active users, the numbers differ by eleven percent, and the meeting stops while everyone tries to work out which is right. Someone volunteers to reconcile them. Two weeks later a third dashboard exists.

The instinct is to treat this as a data quality problem and go looking at the pipeline. Occasionally that is where the answer is. Far more often both numbers are computed correctly and they are answering different questions — one counts any session, the other counts a meaningful action; one attributes to signup date, the other to first activity; one excludes internal accounts and the other never knew to.