Most companies talk about being data-driven. But when it comes to understanding how data is actually used across the organization, they’re flying blind.

The truth is, the clearest record of how your company actually uses data isn’t in your dashboards, data catalog, or lineage graph. It’s in your SQL queries.

Queries are high-signal artifacts. They reveal intent, context, structure, and semantics all in one place. Yet most organizations treat them as disposable, invisible byproducts of work.

At Sherloq, we treat SQL queries as the primary source of truth about how people interact with data. In this post, we’ll explain why.

Why SQL Queries Are Valuable

Each query written by an analyst or engineer encodes real, production-grade context:

• What tables are used together (for example, common join paths)

• How business logic is implemented (such as “active users” or “churned customers”)

• Which fields are important and how they’re transformed

• How teams define metrics, apply filters, or structure cohorts

• What problems users are trying to solve, often visible in the WHERE clause
  
  

Unlike documentation, which is often stale or abstract, queries reflect the actual logic used to make decisions and ship work. They’re real-time, user-generated metadata.

Why SQL Context Gets Lost

In most companies, SQL lives in transient, siloed places:

• Snowflake worksheets

• BI tools like Looker or Mode

• dbt models

• GitHub repos

• Internal notebooks or shared drives
  
  

None of these are structured to retain or surface queries for future reuse. The same joins and filters get rewritten again and again without shared memory or alignment.

Even worse, there is no global visibility:

• You can’t answer, “Where is this field used?”

• You don’t know, “Who last queried this sensitive table?”

• You can’t discover, “How are people defining revenue this quarter?”
  
  

Queries Are the Missing Metadata Layer

Every organization invests in metadata tools like catalogs, lineage systems, and glossaries. But most of these operate outside the SQL itself. They require manual effort to define concepts and track usage.

Meanwhile, queries already contain that metadata. They are:

• Self-documenting

• Rich with lineage information

• Tied to real users, teams, and use cases

• Repeated and reused (or misused) across systems

Treating queries as a knowledge source lets you extract:

• Field and table popularity

• Common logic patterns

• Equivalent definitions across teams

• Drift in business definitions over time

This isn’t theory. It’s reality, buried in your logs and editors.

How Sherloq Turns Queries Into Knowledge

Sherloq integrates directly into the environments where queries are written, such as Snowflake, dbt, GitHub, and others. It builds a unified index of your organization’s SQL workflows.

We parse and enrich every query with:

• Table and field usage

• Join structure and logic fragments

• Author, timestamp, and query history

• Semantic embeddings for similarity search

This allows you to:

• Search for how a concept is implemented across tools

• Discover canonical ways to query a metric

• Reuse trusted logic instead of reinventing it

• Feed high-quality examples into AI copilots and LLMs

Over time, your query history becomes more than just logs. It becomes organizational memory, powering reuse, governance, and AI.

Don’t Let Your Knowledge Expire

SQL isn’t just a means to an end. It is a reflection of how your company understands and interacts with its data.

By treating queries as knowledge, not just code, you unlock:

• Higher-quality AI outputs

• Stronger alignment across teams

• Better onboarding

• Deeper understanding of how data is actually used

That’s why Sherloq is building infrastructure to make SQL searchable, structured, and reusable. We are turning scattered queries into shared intelligence.