Sample Data (Faker) Integration

Integrate Sample Data — Test Your Pipeline

Generate realistic sample marketing data and let AI agents test queries on mock campaigns, leads, and attribution data before connecting real platforms.

SOC 2 Type II
1,000+ Data Sources
Any Warehouse or BI Tool
A
Improvado Agent
Connected to Sample Data (Faker)
Show me the latest test dataset performance across all environments.
You have 12 active test datasets generating 847K records/day. Your staging environment is processing 3.2M synthetic transactions with 99.4% data validity. Production sandbox shows 156 concurrent test users.
Flag any datasets with schema drift in the last 48 hours.
Found 3 datasets with schema changes: customer_profiles added 2 fields, order_events modified timestamp format, and product_catalog updated 18% of enum values. All changes documented in version control.
Trusted by data-driven teams
DockerOMDhimsillyMattelASUSActivision
1,000+
Integrations
200+
Sample Data (Faker) Fields
99.9%
SLA Uptime
<5 min
Setup
SOC 2
Type II
Improvado Key Takeaways

Generate sample data for testing pipelines

Improvado's Faker integration creates realistic sample datasets that mirror actual marketing data structures. Generate mock campaigns, leads, revenue, and attribution data with proper relationships and realistic metrics. Sample data follows the same schema as real marketing platforms for accurate testing. Refresh datasets on demand to test different scenarios and edge cases.

200+ metrics and dimensions Campaigns, ad groups, keywords, audiences, geo, device — all granularity levels from the Sample Data (Faker) API
15-minute refresh cycles Near real-time sync with 99.9% SLA uptime. No stale dashboards.
Cross-channel normalization Marketing CDM unifies your data with 1,000+ sources into one schema. No manual mapping.
Any warehouse or BI tool Snowflake, BigQuery, Redshift, Databricks, Power BI, Tableau, Looker Studio
AI Agent access via MCP Query, write, and monitor Sample Data (Faker) through Claude, ChatGPT, Cursor, or any MCP client
Enterprise-grade security SOC 2 Type II, HIPAA, GDPR, CCPA. Raw data never leaves your environment.
OAuth setup in under 5 minutes No API keys, no code, no developer setup. Schema changes handled automatically.
Zero ongoing maintenance Pagination, rate limits, API versioning — all managed. Your team focuses on analysis.
Integration Details

Test unified data models before production

Sample data flows through Improvado's Marketing Common Data Model just like real platform data. Test data transformations, dashboard logic, and reporting workflows without affecting production systems. Validate cross-platform attribution models using mock data from multiple simulated sources. Teams can develop and test analytics processes while waiting for actual platform connections.

Faker Library v19 · No auth · On-demand · full refresh
Schema Overview

Data objects and fields Improvado extracts from Sample Data (Faker)

Object Fields
Campaign
spend impressions clicks conversions ctr cpc campaign_name
Ad Group
ad_group_name bids impressions clicks conversions status
Ad
ad_id ad_name format impressions clicks spend ctr
Keyword
keyword_text match_type cpc impressions clicks conversions quality_score
Conversion
conversion_id conversion_name conversion_time conversion_value campaign_id
How it works

From connection to autonomous action in three steps

1

Connect

Connect your Faker data generation pipelines through API configuration. Point the agent to your test data schemas, generation rules, and environment endpoints—no separate authentication needed since it operates within your infrastructure.

2

Ask

Ask questions like 'Which test datasets have the highest cardinality variance?' or 'Show me data quality scores across all faker instances' or 'What's the current PII masking coverage in staging?'

3

Act

The agent adjusts generation rates, updates schema definitions, modifies data distribution rules, pauses or resumes faker instances, and applies new anonymization patterns across test environments.

Use Cases

What teams ask their AI agent about Sample Data (Faker)

Real prompts from enterprise marketing teams. The agent reads your data, answers in seconds, and takes action when you ask.

See how teams use Improvado →
A
Improvado Agent Analysis

Test new dashboard designs with realistic sample data before connecting real platforms

Your AI agent analyzes Sample Data (Faker) data and delivers actionable insights — automatically, in seconds.

2 days → 30 min
A
Improvado Agent Cross-channel

Validate attribution models using sample multi-touch customer journey data

Your AI agent analyzes Sample Data (Faker) data and delivers actionable insights — automatically, in seconds.

4 hrs → 15 min
A
Improvado Agent Reporting

Train team members on new reporting tools using safe sample datasets

Your AI agent analyzes Sample Data (Faker) data and delivers actionable insights — automatically, in seconds.

Manual → auto
AI Agent Access

Your agent trains on realistic data — zero risk to production

Read

The agent reads dataset generation metrics, record volumes, schema versions, data quality scores, cardinality distributions, field-level statistics, environment health status, and validation rule compliance across all faker instances.

Write

It scales generation rates, updates data schemas, modifies distribution patterns, applies anonymization rules, creates new test datasets, archives deprecated data, and adjusts sampling strategies based on testing requirements.

Monitor

It monitors schema drift, data quality degradation, generation rate anomalies, validation failures, environment resource usage, and automatically alerts when test data patterns diverge from production characteristics.

The AI agent queries mock campaign data, sample customer journeys, and test attribution models that mirror real marketing structures. It lets teams validate dashboard designs, test complex attribution logic, and practice natural language queries on safe datasets before connecting actual platforms.

Claude ChatGPT Cursor Gemini Any MCP Client
Improvado Agent · Sample Data (Faker)
You
Compare data generation volume across test environments this week
A
Test Data Generation
Environment Records/Day Growth
staging.customer_data 284K records +23%
dev.transaction_feed 198K records +41%
qa.user_events 156K records +12%
sandbox.inventory 127K records -8%
perf_test.orders 82K records +67%
5 environments · 847K daily records · avg +27% growth
You
Increase transaction_feed generation rate by 50% for load testing
A
Dataset Generation Scaled
dev.transaction_feed now generating 297K records/day
Destinations

Send Sample Data (Faker) data anywhere

Load normalized data to your preferred warehouse, BI tool, or cloud storage. Click any destination to see its integration guide.

SOC
SOC 2 Type II Audited data management
H
HIPAA Healthcare compliance
EU
GDPR EU data protection
CA
CCPA California privacy
Compare

They extract data. Improvado deploys an agent.

Traditional tools move data from A to B. Improvado gives you an AI agent that reads, acts, and monitors — with Sample Data (Faker) as one of 1,000+ integrated sources.

Feature Improvado Supermetrics Funnel.io Fivetran
Data fields extracted 200+ ~90 ~120 ~80
Total integrations 1,000+ ~150 ~500 ~300
Cross-channel normalization (CDM) ✓ Built-in ✗ Manual ● Basic mapping ✗ Raw only
AI Agent access (MCP) ✓ Read, Write, Monitor
Data warehouse destinations ✓ 16+ warehouses & BI tools Sheets, Looker, BigQuery BigQuery, Snowflake, Redshift ✓ Broad warehouse support
Refresh frequency Every 15 min Scheduled triggers Daily / 6hr Every 15 min (premium)
SOC 2 Type II & HIPAA ✗ SOC 2 only ✓ SOC 2
Best for Teams that want an AI agent, not a pipeline Small teams, spreadsheets Mid-market, data teams Engineering-led ELT pipelines

Comparison based on publicly available documentation as of April 2026. Feature availability may vary by plan tier.

FAQ

Frequently asked questions

What types of sample data can Improvado generate?
Improvado generates sample data for campaigns, leads, conversions, revenue, customer journeys, and attribution touchpoints. Data includes realistic metrics like CTR, conversion rates, and revenue amounts with proper statistical distributions. Sample datasets mirror real marketing platform schemas for accurate testing.
How realistic is the generated sample data?
Sample data uses realistic business logic with proper relationships between campaigns, customers, and conversions. Metrics follow industry benchmarks for CTR, conversion rates, and customer lifetime values. Data includes seasonal patterns, weekend effects, and other real-world variations found in actual marketing data.
Can I customize the sample data parameters?
Yes, you can specify date ranges, volume levels, metric ranges, and campaign types for generated data. Configure customer journey complexity, attribution touchpoints, and revenue distributions to match your testing needs. Adjust data characteristics to simulate different business scenarios and edge cases.
Does sample data work with all Improvado destinations?
Sample data flows to the same destinations as real marketing data - BigQuery, Snowflake, Redshift, Azure, Tableau, Power BI, and Looker. Use identical data pipeline configurations to test warehouse loading, transformation logic, and BI tool connections. Switch from sample to real data without changing destination settings.
How do I replace sample data with real platform data?
Simply disable the Faker connector and enable your actual marketing platform connections. Real data will flow through the same pipeline and destination configurations you tested with sample data. No changes needed to warehouse schemas, transformations, or dashboard connections.
Is sample data generation included in all plans?
Sample data generation is available across Improvado plans for testing and development purposes. Generate unlimited sample datasets during trial periods and for ongoing testing needs. Contact support for specific volume requirements or custom sample data scenarios.