How to Query Sage Intacct Data with AI When Dimensions Don't Land as Tables
Sage Intacct's product is its dimensions. None of them lands as a table in the replicated schema. Every dimension question bins on a string that drifts on rename.
How to Query Jira Service Management Data with AI When Request Type Hides in a Custom Field
Customer Request Type does not land as a column on issue. It lives in issue_field_history under a customfield id that differs per instance, and the obvious grouping returns three buckets, not fifty.
How to Query NetSuite Data with AI When Multi-Book Silently Doubles Every Dollar
NetSuite's standard reports filter the transaction accounting line to one accounting book automatically. The warehouse copy of the same tables does not, so a naive SUM adds every dollar once per book.
How to Build a ServiceNow Semantic Model That Governs Inherited Tables
Declare the inheritance join and the missing company FK, sign them off, and the incidents-by-customer chain comes back governed instead of flagged.
How to Query ServiceNow Data with AI When the Join Isn't a Foreign Key
Incident extends task, so the join between them is not a foreign key. Introspection has nothing to infer and the governance analyzer never sees the join.
How to Build a Salesforce Semantic Model That Can't Double-Count Your Pipeline
A four-step walkthrough on replicated Salesforce: introspect the schema, correct the grain and the custom fields, sign the definitions off, then verify the breakdown ties to the total.
How to Connect Your Warehouse to Claude, Cowork and ChatGPT
Claude Desktop launches an MCP server on your machine. Cowork, claude.ai and ChatGPT connect inbound from the vendor's cloud. Which route you need is decided by one question.
How to Query Salesforce Data with AI Without Double-Counting Your Pipeline
The QBR needs eight quarters of pipeline by product. Salesforce cannot produce it, so the data lands in a warehouse. There the same question overstates pipeline 2.5x and reorders the slide.
The Data Lake Promise Might Finally Be Coming True
We dumped Salesforce and ServiceNow into the lake and got a landfill of codes and GUIDs. Why the missing ingredient was always context, and how AI finally makes it affordable.
The query we refuse to run
A fan trap or chasm trap can inflate an aggregate by 3x and nothing errors. Here is how our Analytics Agent detects the hazard from join cardinality and refuses to ship the wrong number.
Snowflake Cortex Analyst vs Databricks Genie vs BigQuery Gemini: warehouse-native AI compared
An honest head-to-head of the three warehouse-native AI products. Where each wins, where each loses, and the architectural blind spot they all share.
Why naive prompting isn't a data agent
A staging Postgres taken down. Wrong customers in dashboards. 4% revenue drift. Three production failures that taught us a data agent is context engineering, not prompting.