Database Table Mapping and Relationship Discovery

This workflow helps teams map out database tables and their relationships before conducting analysis, reducing query time and improving accuracy by providing Claude with structured guidance on data location and relationships. This approach minimizes hallucination and creates reusable table maps for consistent analysis.

QUERY:

I need you to find and write out each of the tables we might need for [ANALYSIS_TYPE]. What information do we already know? [TABLE_1] has [KEY_FIELDS] likely needed. [TABLE_2] has [KEY_FIELDS] likely needed. Where are we most likely to find [SPECIFIC_DATA_TYPE]? Map out the tables and key relational fields for me.

Goal: Have Claude systematically explore and document the database structure, identifying key tables and their relationships for a specific analysis use case.

QUERY:

Map the tables and key fields for [ANALYSIS_PURPOSE]. I need a comprehensive view of tables needed for [SPECIFIC_USE_CASE] using our [DATA_SOURCE] data. Include the relational keys between tables and the most important fields in each table.

Goal: Generate a complete mapping of tables, fields, and relationships that can be saved and reused for future analysis sessions.

QUERY:

Using this table mapping: [PASTE_TABLE_MAP], analyze [SPECIFIC_QUESTION]. Here's where the data is located: [TABLE_LOCATIONS]. Focus your queries on these specific tables and relationships rather than exploring the schema.

Goal: Conduct efficient analysis by providing Claude with pre-mapped table relationships to avoid redundant exploration and improve accuracy.

QUERY:

Using our [DATA_SOURCE] data, analyze [ENTITY_TYPE] and how they show up in our [BUSINESS_PROCESS]. Focus on the intersection of [TABLE_1], [TABLE_2], and the [SPECIFIC_FIELD] field. Also look for mentions in activities, emails, and notes where [ENTITIES] might be referenced in conversations with customers.

Goal: Execute a targeted analysis using the pre-built table maps for extracting insights from both structured and unstructured data sources.

Teams:

Data Analysts Marketing Product Management Sales Operations

Sources:

Dynamics 365 Salesforce

Watch:

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