- Release notes
- Getting started
- Installation
- Configuration
- Integrations
- Authentication
- Working with Apps and Discovery Accelerators
- AppOne menus and dashboards
- AppOne setup
- TemplateOne 1.0.0 menus and dashboards
- TemplateOne 1.0.0 setup
- TemplateOne menus and fashboards
- TemplateOne 2021.4.0 setup
- Purchase to Pay Discovery Accelerator menus and dashboards
- Purchase to Pay Discovery Accelerator Setup
- Order to Cash Discovery Accelerator menus and dashboards
- Order to Cash Discovery Accelerator Setup
- Basic Connector for AppOne
- SAP Connectors
- Introduction to SAP Connector
- SAP input
- Checking the data in the SAP Connector
- Adding process specific tags to the SAP Connector for AppOne
- Adding process specific Due dates to the SAP Connector for AppOne
- Adding automation estimates to the SAP Connector for AppOne
- Adding attributes to the SAP Connector for AppOne
- Adding activities to the SAP Connector for AppOne
- Adding entities to the SAP Connector for AppOne
- SAP Order to Cash Connector for AppOne
- SAP Purchase to Pay Connector for AppOne
- SAP Connector for Purchase to Pay Discovery Accelerator
- SAP Connector for Order-to-Cash Discovery Accelerator
- Superadmin
- Dashboards and charts
- Tables and table items
- Application integrity
- How to ....
- Working with SQL connectors
- Introduction to SQL connectors
- Setting up a SQL connector
- CData Sync extractions
- Running a SQL connector
- Editing transformations
- Releasing a SQL Connector
- Scheduling data extraction
- Structure of transformations
- Using SQL connectors for released apps
- Generating a cache with scripts
- Setting up a local test environment
- Separate development and production environments
- Useful resources
Introduction to SQL connectors
A connector handles the process of extracting data from a source system and transforming the data to make it usable for UiPath Process Mining. In a SQL connector, Extract and Transform are separate steps, of which the results are stored in the same database. Process Mining loads data from that database as input for the dashboards. See the illustration below.
A released app contains the dashboards definitions and covers all the steps to display the data into the dashboards.
In the Extract step, the data is extracted from the source system and stored in a database, without making any changes to the data (only filtering is applied to limit data necessary for the connector). The preferred extraction tool is CData Sync. Depending on the connector and source system, other tools may be used.
Transformations are applied to the data stored in the database to make sure the data adheres to a data schema which can be loaded in Process Mining.
In the Transform step, dbt is used to manage and run all the transformations, which are defined as queries in the Structured Query Language (SQL). Dbt is required for a SQL connector.
Refer to the Discover section in the Product lifecycle page for an overview of all supported apps, discovery accelerators, and connectors available for Process Mining.
If there is no connector available for your process, you can use the template connector in the devkit-connector that contains the basic setup for a SQL connector.
Next to Microsoft SQL Server and dbt, when you want to develop a SQL connector, a code editor is necessary.
|
Tool |
Used for |
Recommended |
|---|---|---|
|
Editor |
Editing the transformations and configurations. |
Visual Studio Code, which integrates with other tools needed for SQL connector development. |
|
Version control |
Tracking changes and collaborating on the connector development. |
Git. |
