Every record & field
Pull the full Buk data model - employees, payroll, time, absences, and recruiting - not just a fixed preset, so your people reports are never missing a field.
Buk
Buk
HR & PeopleDataddo extracts the full Buk data set - employees, payroll, time, absences, recruiting - and delivers it wherever your team needs it: into AI tools and agents, your warehouse like Snowflake and BigQuery, BI dashboards, and back into your finance and ops tools. Blend it with finance and ops data, backfill full history, and keep it fresh on your schedule - all fully managed, with the data plane running where you choose. No pipelines to build, no lock-in.
YOUR PEOPLE SOURCE OF TRUTH
Turn Buk into people reporting your whole team trusts
People data is only useful when it's complete, clean, and current. Dataddo extracts the full Buk data model, governs it, and serves it to every warehouse, dashboard, AI tool, and downstream system - continuously and without manual exports.
Blend with finance & ops
Combine Buk with your finance and operations data so headcount, cost, and workforce analytics live in one place.
Backfill full history
Load historical Buk data beyond the platform's export limits, so trend, tenure, and attrition analysis holds up.
Model, clean & mask before load
Normalize departments, roles, and currencies, and let the Data Quality Firewall stop bad rows while automatic PII detection masks sensitive employee fields before Buk data reaches your reports.
Fresh on your schedule
Incremental, scheduled syncs keep Buk data current - as often as hourly - without manual exports or full reloads.
Governed & monitored
Delivery alerts and quality checks catch gaps in Buk data early, so people dashboards never silently break.
DATASETS
What you can pull from Buk
The Buk connector provides a list of curated datasets - ready-made sets of records, fields, and metrics you can extract on a schedule. Need something specific? Any dataset can be forked and customized, or built from scratch, with our Universal Connector.
List of curated datasets
Idid
string
Person Idperson_id
string
Picture Urlpicture_url
sensitivestring
First Namefirst_name
sensitivestring
Surnamesurname
sensitivestring
Second Surnamesecond_surname
sensitivestring
Full Namefull_name
sensitivestring
Rutrut
sensitivestring
Nationalitynationality
sensitivestring
Country Codecountry_code
string
Civil Statuscivil_status
sensitivestring
Emailemail
sensitivestring
Personal Emailpersonal_email
sensitivestring
Addressaddress
sensitivestring
Citycity
string
Districtdistrict
string
Location Idlocation_id
string
Regionregion
string
Office Phoneoffice_phone
sensitivestring
Phonephone
sensitivestring
Gendergender
sensitivestring
Birthdaybirthday
sensitivestring
Universityuniversity
string
Degreedegree
string
Active Sinceactive_since
string
Statusstatus
string
Private Roleprivate_role
boolean
Code Sheetcode_sheet
string
Health Companyhealth_company
string
Pension Regimepension_regime
sensitivestring
Pension Fundpension_fund
string
Afcafc
string
Termination Reasontermination_reason
sensitivestring
Current Job Periodicitycurrent_job_periodicity
string
Current Job Frequencycurrent_job_frequency
string
Current Job Working Schedule Typecurrent_job_working_schedule_type
string
Current Job Zone Assignmentcurrent_job_zone_assignment
boolean
Current Job Company Idcurrent_job_company_id
string
Current Job Area Idcurrent_job_area_id
string
Current Job Contract Termcurrent_job_contract_term
string
Current Job Contract Typecurrent_job_contract_type
string
Current Job Start Datecurrent_job_start_date
datetime
Current Job End Datecurrent_job_end_date
datetime
Current Job Contract Finishing Date 1current_job_contract_finishing_date_1
string
Current Job Contract Finishing Date 2current_job_contract_finishing_date_2
string
Current Job Weekly Hourscurrent_job_weekly_hours
float
Current Job Base Wagecurrent_job_base_wage
sensitivestring
Current Job Cost Centercurrent_job_cost_center
string
Current Job Role Idcurrent_job_role_id
string
Current Job Role Namecurrent_job_role_name
string
Current Job Role Requirementscurrent_job_role_requirements
string
Current Job Role Role Family Idcurrent_job_role_role_family_id
string
Current Job Role Role Family Namecurrent_job_role_role_family_name
string
Current Job Role Role Family Quantity Of Rolescurrent_job_role_role_family_quantity_of_roles
string
Current Job Boss Idcurrent_job_boss_id
string
Current Job Boss Rutcurrent_job_boss_rut
string
Bankbank
string
Payment Methodpayment_method
string
Account Typeaccount_type
string
Account Numberaccount_number
sensitivestring
Progressive Vacations Startprogressive_vacations_start
datetime
Family Responsabilities Idfamily_responsabilities_id
string
Need a dataset, metric, or attribute you don't see?
Tell us what's missing and we'll add it to the connector.
WITH VS. WITHOUT
Who carries the load when things change
Keep Buk data flowing to every warehouse, dashboard, and tool - and see who owns it when an API or schema changes:
| Without Dataddo |
With Dataddo
|
Outcome for you | |
|---|---|---|---|
| API or auth change | You discover the breakage and scramble to fix it. | We update the connector and restore the pipeline - often before you notice. | Syncs from Buk keep flowing |
| Schema drift | Columns change and pipelines break or corrupt data silently. | Detected automatically and handled by configurable rules. | Only clean Buk data lands in reports |
| Endpoint deprecated | You re-engineer the integration. | We own the update - the data contract holds. | Your Buk reporting keeps working |
| Missing connector | You build and maintain a custom integration. | We build it and maintain it, under a ~4-week SLA. | Any Buk data you need, on request |
| Silent degradation | You find out when a report or model run fails. | Proactive monitoring catches anomalies and delays first. | Gaps caught before dashboards break |
| Debugging | You dig through logs across disconnected tools. | Run histories, payload inspection, and end-to-end lineage in one place. | Faster root-cause, fewer reporting gaps |
Data residency by design
Choose where Buk data is processed - same cloud, region, or sovereign
Buk is a cloud API, so the question isn't on-prem vs cloud - it's which region your data flows through. With Dataddo you run the data plane in the region you choose, so Buk payloads move straight to your destinations without transiting a third-party SaaS. Pin it to an EU or US region for compliance, or self-host when a downstream target lives inside your own network.
| Data Plane location | Typical data sensitivity | Why this setup |
|---|---|---|
|
Public cloud 
AWS
Microsoft Azure
Google Cloud
|
Low to moderate - general business, marketing, and product data; sources that are already cloud-native. | Fastest to stand up and scales elastically. Best when the data has no residency restriction and often already lives in the same public cloud. |
|
Regional & EU sovereign clouds
EU sovereign clouds
Regional providers
Private cloud
|
Regulated / residency-bound - PII, financial, and health data governed by GDPR or local law. | Keeps processing inside a specific jurisdiction to meet data-residency and sovereignty rules, while still running as managed infrastructure. |
|
On-premises 
Kubernetes
Red Hat OpenShift
VMware Tanzu
|
Highly sensitive / restricted - data that contractually or legally cannot leave the corporate perimeter. | Data never leaves your network. Required for air-gapped, classified, or locked-down environments; the Control Plane still manages it via metadata only. |
DATA DELIVERY
Every way to deliver Buk data
People data rarely has one home. Dataddo feeds Buk into AI and agents, loads it into your warehouse for workforce analytics, syncs records back into finance and ops tools, and delivers files to storage - all governed the same way.
| Transport type | What it does | Typical destinations | Typical business use cases |
|---|---|---|---|
| Data to AI & Agents | Feed Buk data into vector databases, LLMs, and AI agents so people copilots can reason over your workforce data. | Load Buk records into vector stores for retrieval-augmented HR assistants, Give AI agents and copilots governed access to live Buk people data | |
| ETL / ELT to your warehouse | Load Buk records and metrics into your warehouse for headcount and workforce analytics. | Centralize Buk alongside finance and ops data in Snowflake, BigQuery, or Redshift, Backfill Buk history for tenure and attrition analysis | |
| Sync back to finance & ops | Push modeled records built from Buk data back into finance, payroll, and ops systems. | Sync headcount and cost records from Buk into finance and planning tools, Keep Buk people data aligned across systems | |
| Files to storage & partners | Deliver raw or modeled Buk extracts to object storage and partners. | Archive raw Buk exports to S3, GCS, or Azure storage, Send scheduled Buk extracts to partners over SFTP |
Claude
OpenAI
Gemini
Mistral AI
Snowflake
BigQuery
Amazon Redshift
PostgreSQL
Salesforce
HubSpot
Monday
Google Sheets
Google Cloud Storage
Azure Blob Storage
SFTP
Case Studies
See what people and data teams build with Dataddo
65,000 Social Media Accounts. One Platform. Zero Manual Authorizations.
Beauty & Consumer Goods
How Livesport Activates Data, Saves Engineering Resources with BigQuery and Dataddo
Entertainment
How ID&T Group Activates Data from 1M+ Festival Fans and Dozens of Social Accounts
Entertainment
How Sensire Accelerated Migration of a Proprietary On-Premise Data Infrastructure to the Cloud with Dataddo
Healthcare
How Ringside.ai Builds a Data Product Better and Faster Using Dataddo
Marketing
How Publicis Groupe Brasil Uses Dataddo's API to Scale a Data Product
Advertising
FAQ
Buk as a source + Dataddo, answered
Where can I send Buk data?
To any of Dataddo's 150+ destinations - warehouses like Snowflake and BigQuery, BI dashboards, CRMs and marketing tools, object storage, and AI or vector stores - plus custom destinations on request.
Do I have to maintain the pipeline?
No. Dataddo is fully managed: we maintain the Buk connector, adapt to API and schema changes, and alert you if anything needs attention. There is no pipeline code for you to write or fix.
How is sensitive employee data handled?
Dataddo can mask or hash PII in Buk data before it lands, and if you run the data plane on-premises, payload data never leaves your network. Combined with SOC 2 Type II and ISO 27001 certification and EU or US residency, that keeps people data compliant end to end.
What if Buk changes their API?
That's on us, not you. Dataddo's team proactively tracks Buk API and schema changes and updates the connector before they break your pipeline. Continuous monitoring watches every sync, and if anything needs attention you get an alert - so your Buk data keeps flowing without you touching a thing.
Which Buk data and fields are available?
The full Buk data model - employees, payroll, time, absences, and recruiting - not a fixed subset. If a field you need isn't exposed yet, we add it on request, usually at no extra cost.
How is my data secured?
Dataddo is SOC 2 Type II and ISO 27001 certified. Data is encrypted in transit and at rest, PII can be masked or hashed, and EU or US data residency is available. Self-host the data plane and payload data never leaves your network.
Will API rate limits be a problem?
Dataddo handles Buk pagination, rate limits, and retries for you, and pulls incrementally on a schedule so you stay within API quotas without impacting your source.
Am I locked in?
No. Pipelines are source- and destination-agnostic - you can add or switch destinations without rebuilding, and data lands in native formats you own.