The Scenario
You are a systems integrator and you are building a data pipeline that needs to map external system identifiers to BambooHR's department codes, location IDs, and job title values.
The source systems use their own naming conventions. The pipeline needs a translation layer — a set of lookup tables that sit in a Google Sheet and get refreshed whenever BambooHR's configuration changes.
The HR team updates departments and locations a few times a year. The last time they did a reorg, the pipeline silently dropped records for two weeks because the department names in the mapping table were stale.
The bad version:
- Log into BambooHR, navigate to Settings, find the Departments list.
- Manually copy each department ID and name into a sheet column.
- Navigate to Locations, repeat.
- Navigate to Job Titles, repeat.
- Three separate manual copy operations for data that could change again in two months.
The job is to build a pipeline, not to maintain lookup tables by hand.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet and pulls BambooHR metadata — departments, divisions, locations, job titles — in one call.
Fetch all BambooHR departments, divisions, and locations and write each list into a separate tab of this sheet with the ID and name columns.
SheetXAI calls the BambooHR metadata endpoints, retrieves each list, and writes them into separate tabs with consistent ID and label columns — ready to reference as lookup tables.
What You Get
- A separate tab per metadata type: Departments, Divisions, Locations.
- Columns: ID and name (or label) for each entry.
- All active entries included — no filtering required.
- The tabs are ready to use as VLOOKUP or INDEX/MATCH reference tables immediately.
What If the Data Is Not Quite Ready
You also need job title metadata in the same workbook
The pipeline maps source system job codes to BambooHR job title IDs.
Fetch BambooHR departments, divisions, locations, and job titles. Write each into a separate tab with ID and name columns. Tab names: Departments, Divisions, Locations, JobTitles.
You want a combined reference tab with a 'type' column for easier pipeline lookups
The pipeline reads a single reference sheet and uses a type column to determine which dimension a row belongs to.
Fetch BambooHR departments, locations, and job titles. Write all entries into a single 'Reference' tab with columns: type (Department/Location/JobTitle), ID, and name.
You need to flag any IDs that appear in the current pipeline config but are no longer in BambooHR
The pipeline config lives in the 'PipelineConfig' tab. Column A has BambooHR IDs the pipeline currently maps to.
Fetch all BambooHR department and location IDs. Compare against column A of the 'PipelineConfig' tab. Write 'active' or 'stale' in column B of that tab for each ID.
Full metadata refresh with stale-ID detection in one prompt
Fetch BambooHR departments, divisions, locations, and job titles. Write each into its own tab (Departments, Divisions, Locations, JobTitles) with ID and name columns. Then compare all fetched IDs against column A of the 'PipelineConfig' tab. Write 'active' or 'stale - [type]' in column B of that tab for each row.
The pattern: the metadata pull, the tab distribution, and the stale-ID audit all happen in one instruction — one run refreshes the entire mapping layer.
Try It
Get the 7-day free trial of SheetXAI and open your pipeline reference workbook, then ask it to pull the current BambooHR metadata into lookup tabs. Set a reminder to re-run it after any BambooHR configuration change so the pipeline mapping stays current.