The discipline that makes the rest of the practice trustworthy. We design the policies, tooling and ownership model that turn a working data stack into a governed one: definitions everyone agrees on, quality the team can detect before leadership does and master records that don't drift apart between systems.
Define how data gets owned, prioritized and decided on across the business. We work with leadership to set decision rights, the data org's operating cadence and the policies that govern access, quality and change. The result is a data function that runs like an operating discipline rather than a backlog of tickets, with clear escalation paths when teams disagree on a definition or a priority.
Reconcile customer, product and account records across systems into a single golden record. We map identifiers, resolve duplicates and define ownership for each field so downstream models stop disagreeing about who is who. The clean entity layer stops the 'which Salesforce record is the real one' question from cascading into every metric.
Stand up a catalog where every dataset, model and metric has an owner, a description and a lineage view that shows what depends on what. We implement Atlan, dbt's catalog or OpenLineage-based tooling so analysts can find the right table and engineers can see what breaks downstream before they ship a change. The result is fewer 'does this number exist already' questions and faster impact analysis when a source system changes.
Producer-consumer data contracts at the boundary between source systems and the warehouse, so a backend team can't silently break an analytics model by renaming a column. We define the contract format, the enforcement layer (CI checks, schema registry, dbt tests) and the change-management workflow that keeps both sides aligned. The result is fewer pipeline outages caused by upstream changes nobody warned the data team about.
Automated testing, freshness monitoring, anomaly detection and observability tooling stitched into the pipeline and surfaced where the team works. The system tells the data team when a row count drops, a field starts producing nulls or a load misses its window, well before a leadership question makes the same point louder. Fewer fire drills, and a noticeable decline in 'is this dashboard right' Slack threads.
Row-level and column-level access controls, PII handling, audit trails and the policy work behind GDPR, CCPA, SOC 2 and HIPAA where applicable. We implement them in Snowflake, BigQuery or your platform of choice, then document the policies clearly enough that a security review doesn't stall a procurement cycle. The result is a data estate that holds up to auditors and that the security team trusts to extend new datasets into.
Ownership, certification and deprecation processes for the business metrics that show up in board decks and operating reviews. We define metric stewards, the certification workflow that moves a number from 'someone built it once' to 'this is the company definition', and the deprecation path for legacy versions. The result is one canonical version of every metric leadership cares about, with the audit trail to prove it.
Thirty minutes with a 829 Analytics partner. You leave with a prioritized view of what to build first, what's worth waiting on, and the business metric anchoring each move. Whether or not we end up working together.