Two layers of work: the tools that get the data right, and the strategy that gets the organization to actually use it.
The right tool for the problem, not the loudest one in the market. AI is applied throughout this work as an accelerant, not treated as a separate offering bolted onto the side.
AlteryxWorkflow automation for the processes that currently eat days of someone's month: blending, cleansing, and self-service applications that replace manual, error-prone spreadsheet work.
TableauVisualization that gets decisions made faster, dashboards built to answer the question a leader actually has, not to look impressive in a demo.
Snowflake & SQLA modern warehouse foundation so reporting and analytics stop being built on top of someone's local extract, with the SQL to go with it, T-SQL, Snowflake's dialect, whatever the platform speaks.
ExcelStill where a lot of real business decisions get made. Built to be sturdy, auditable, and something a finance team can actually own after the engagement ends.
This is the layer most consultants skip. A tool rollout without this layer produces a dashboard nobody opens twice.
Built as a hub and spoke, not a central command structure. The COE sets standards, governance, and tooling; functional teams keep ownership of their own analytics. That distinction is what determines whether a COE gets adopted or resented.
Rather than centralizing every report build, champions are coached and embedded directly within functional teams, so capability spreads instead of pooling in one department.
Training built as real infrastructure, not a single kickoff session. A repeatable enablement model that keeps producing capability after the engagement is over.
Progress tracked against concrete numbers, people trained, reports created or modified, hours reduced, rather than assumed from a rollout date on a project plan.