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Overview

Resources are the individual tables, views, API endpoints, or files within a connection that Entegrata collects. Each resource represents a specific dataset you want to synchronize to your data lakehouse.

Key Concepts

What is a Resource?

A Resource is a collectible data entity discovered within a connection:
Name
string
required
The resource identifier (table name, view name, API endpoint path, or file name)
Type
enum
required
The kind of resource:
  • Table - Database table with data rows
  • View - Database view (virtual table)
  • Endpoint - API endpoint providing data
  • File - Data file or spreadsheet
Status
enum
required
Collection state:
  • Active - Resource is collecting data
  • Inactive - Resource is not collecting
Fields
array
Columns or properties within the resource (e.g., customer_id, name, email)

Resource Lifecycle

1

Discovery

Resources are automatically discovered when you create a connection or when discovery runs (every 3 hours)
2

Configuration

Enable resources and configure collection settings (schedule, load type, filters)
3

Active Collection

Enabled resources collect data according to their configured schedules
4

Monitoring

Track collection jobs, performance, and data quality
5

Maintenance

Update settings, handle schema changes, or disable resources as needed

Resource Types

Tables

Database tables containing rows of structured data:
  • Most common resource type
  • Have defined schemas with columns and data types
  • Support full and incremental loads
  • May have primary keys defined by the database

Views

Database views (virtual tables based on queries):
  • Derived from one or more tables
  • Schema defined by the view query
  • Typically use full load (incremental may not be supported)
  • Primary keys must be user-defined

Endpoints

API endpoints providing structured data:
  • REST API paths or GraphQL queries
  • Schema discovered from API responses
  • Support pagination and filtering
  • May have rate limits

Files

Files containing structured data:
  • Excel spreadsheets, CSV files, JSON documents
  • Schema inferred from file structure
  • May contain multiple sheets or sections
  • Typically use full load

Resource vs. Connection

Understanding the relationship:
AspectConnectionResource
ScopeEntire data sourceSingle table/view/endpoint
DiscoveryDiscovers all resourcesDiscovered within connection
ScheduleDefault for all resourcesCan override connection default
Enable/DisableAffects all resourcesAffects only this resource
AuthenticationStores credentialsInherits from connection
CollectionMay trigger all resourcesTriggers single resource

Collection Settings

Each resource can be configured with:

supp

Resource Status Indicators

Resources display status information:

Active Resource

Active resource with toggle on
  • Toggle is ON (green)
  • Collects according to schedule
  • Jobs appear in collection history

Inactive Resource

Inactive resource with toggle off
  • Toggle is OFF (gray)
  • Does not collect data
  • No jobs created

Load Type Indicators

Resources show their configured load type:
Load type badges
  • Full - Full load every collection
  • Incremental - Incremental load with change tracking
Click the badge to quickly open collection settings.

Getting Started with Resources

Common Workflows

Initial Setup After Creating Connection

1

Wait for Discovery

Allow automatic discovery to complete (1-5 minutes)
2

Review Resources

Browse the discovered resources in the Resources table
3

Enable Required Resources

Toggle on the specific tables/endpoints you need
4

Configure Settings

Set load types, unique keys, and filters for each resource
5

Save and Monitor

Save changes and watch the first collection jobs

Ongoing Maintenance

  • Monitor collection jobs - Check for failures or performance issues
  • Handle schema changes - Respond to discovery alerts about schema modifications
  • Adjust schedules - Optimize timing based on data freshness needs
  • Update filters - Refine data selection criteria

Best Practices

Start Small

Enable a few resources first, verify they work, then add more

Use Incremental When Possible

Incremental loads are faster and more efficient for large tables

Set Unique Keys

Always define unique keys to ensure proper deduplication

Apply Filters Early

Filter at the source to reduce data transfer and storage

Monitor First Collections

Watch initial jobs to catch configuration issues early

Document Decisions

Keep notes on why certain resources are enabled/disabled

Next Steps