process-mining

2021.10

true

Release notes
- 2024
  - 2021.10.4
- 2022
- 2021
Getting started
- About Process Mining
- Introduction to UiPath Process Mining
- User roles
- UiPath Process Mining components
- Platform architecture
  - Server architecture
  - Integration options
- From data to dashboard
- App and Discovery Accelerator development
Installation
- Hardware and software requirements
- Server installation
- Updating the license
- Deploying Apps and Discovery Accelerators
- Deploying the UiPath Process Mining Profiler
- Deploying a Connector (.mvp)
- Updating UiPath Process Mining
- Updating a customized version of an App or Discovery Accelerator
- Installing a training environment
Configuration
- Server configuration
- Using a Git repository
- Creating accounts for developers
  - Two-Factor authentication
- Backup
- About telemetry
- Set up Audit Logs
  - Category details
Integrations
- Set up integration with UiPath Automation Hub
- Set up Actionable Insights
Authentication
- Set up single sign-on through Azure Active Directory
- Set up single sign-on through Integrated Windows Authentication
- Set up single sign-on through SAML for Microsoft Active Directory
  - Configuring ADFS
- Adding Superadmin AD Groups
- Adding End-user AD Groups
- Set up LDAP
- Two-Factor Authentication
- Set up a Credential store
  - Setting up an Azure Key Vault Credential store
  - Use a Credential store
Working with Apps and Discovery Accelerators
- Working with charts
- Working with Process graphs
- Sending automation ideas to UiPath Automation Hub
- Filters
- Favorites
- Export
- Selecting the preferred language
AppOne menus and dashboards
- Introduction to AppOne
- Analyzing data in AppOne
- Overview of menus and dashboards in AppOne
- Menu Overview
- Menu Process
- Menu Timing
  - Timing - Timing
  - Timing - Due Dates
- Menu Conformance
- Menu Users
- Menu Details
AppOne setup
- Input tables of AppOne
TemplateOne 1.0.0 menus and dashboards
- TemplateOne menus and dashboards
- Menu Overview
- Menu Analysis
- Menu Efficiency
  - Efficiency - Automation
- Menu Compliance
  - Compliance - Tags
  - Compliance - Due Dates
- Menu Details
TemplateOne 1.0.0 setup
- Getting Started with TemplateOne
- Steps to roll-out TemplateOne 1.0.0
- Input tables of TemplateOne 1.0.0
- Adding custom attributes
- Configuring the context bar
TemplateOne menus and fashboards
- TemplateOne menus and dashboards
- Menu Overview
- Menu Analysis
- Menu Efficiency
  - Efficiency - Automation
- Menu Compliance
  - Compliance - Tags
  - Compliance - Due Dates
- Menu Details
TemplateOne 2021.4.0 setup
- Getting started with TemplateOne
- Steps to roll-out TemplateOne
- Input tables of TemplateOne
  - Input tables of TemplateOne 2021.4.0
- Loading data into TemplateOne
Purchase to Pay Discovery Accelerator menus and dashboards
- Introduction to Purchase-to-Pay Discovery Accelerator
- Analyzing data with Purchase-to-Pay Discovery Accelerator
- Overview of menus and dashboards
- Menu Overview
  - Overview - Procurement
  - Overview - Accounts Payable
- Menu Procurement
- Menu Accounts Payable
- Menu Efficiency
- Menu Compliance
- Menu Details
Purchase to Pay Discovery Accelerator Setup
- Input tables of the Purchase-to-Pay Discovery Accelerator
  - Input tables of Purchase-to-Pay Discovery Accelerator 21.10
  - Input tables of Purchase-to-Pay Discovery Accelerator V. 21.4
- Adding automation estimates
Order to Cash Discovery Accelerator menus and dashboards
- Introduction to Order-to-Cash Discovery Accelerator
- Overview of menus and dashboards
- Menu Overview
- Menu Analysis
  - Analysis - End to End
  - Analysis - Deviations
- Menu Efficiency
  - Efficiency - Automation
  - Efficiency - Customers
- Menu Details
  - Details - End to end
Order to Cash Discovery Accelerator Setup
- Input tables of the Order-to-Cash Discovery Accelerator
  - Input tables of the Order-to-Cash Discovery Accelerator V21.4.1
  - Input tables of the Order-to-Cash Discovery Accelerator 21.4
- Adding automation estimates
Basic Connector for AppOne
- Deploying the Basic Connector
- Introduction to Basic Connector
- Input tables of the Basic Connector
- Loading data
  - Mapping attributes
  - Cleaning input data
- Adding tags
- Adding automation estimates
- Adding Due dates
- Adding Reference models
- Setting up Actionable Insights
- Setting collapsible charts
- Using the output dataset in AppOne
- Output tables of the Basic Connector
SAP Connectors
- Introduction to SAP Connector
- Loading data in the SAP Connector for AppOne
- 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
- Order-to-Cash Process in UiPath Process Mining
  - Roles in the Order-to-Cash process
- Introduction to SAP Order-to-Cash Connector for AppOne
  - Entities
  - Activities
- Input Data of the SAP Order-to-Cash Connector for AppOne
- Other settings
- Optional attributes
- Order-to-Cash tags
- Order-to-Cash Due dates
- Order-to-Cash Reference models
SAP Purchase to Pay Connector for AppOne
- Purchase-to-Pay process in UiPath Process Mining
  - Roles in the Purchase-to-Pay process
- Introduction to SAP Purchase-to-Pay Connector for AppOne
  - Entities
  - Activities
- Input data of the SAP Purchase-to-Pay Connector for AppOne
- Other settings
- Purchase-to-Pay tags
- Purchase-to-Pay Due dates
SAP Connector for Purchase to Pay Discovery Accelerator
- Introduction to SAP Connector for Purchase-to-Pay Discovery Accelerator
  - Entities
  - Activities
- Input Data of the SAP Connector for Purchase-to-Pay Discovery Accelerator
- Configuring the SAP Connector for Purchase-to-Pay Discovery Accelerator
- Configuring the activity code
SAP Connector for Order-to-Cash Discovery Accelerator
- Introduction to SAP Connector for Order-to-Cash Discovery Accelerator
  - Entities
  - Activities
- Input data of the SAP Connector for Order-to-Cash Discovery Accelerator
- Configuring the SAP Connector for Order-to-Cash Discovery Accelerator
Superadmin
- The Superadmin page
- Collaborative development
  - Workspace conflicts
  - Commit
- Creating releases
- Viewing the branch history
- Creating Apps
- Modules
Dashboards and charts
- Creating dashboards
- Adding charts on a dashboard
- HTML panels
- Process graphs
- Legacy charts
  - Adding a compare period filter to a dashboard
- Migrating legacy charts to new charts
Tables and table items
- Connection string tables
  - Connection string types
  - Table scope
- Join tables
- Global tables
- Introduction to table items
- Datasource attributes
  - Attribute selectors
  - Adding new attributes to an App or Discovery Accelerator
- Metrics
- Filters
- Display format
- Expressions
- Maps
- Actions
Application integrity
- Maintain Application integrity
- Application issues
  - Finding Application issues
  - Solving Application issues
- Application Profiling
  - Profiling aalysis
  - Example analysis
How to ....
- Rebrand and restyle Apps and Discovery Accelerators
- Translate apps
- Use sharding in your applications
- Use generic script datasources
  - Example: Creating a Python Script
  - Example: Creating an R Script
- Create an anonymized dataset
- Set up native SAP extraction
  - Installing the Z_XTRACT_IS_TABLE Function Module on Your SAP System
- Set up automated data refreshes
- Use an access matrix to enable role-based access to data
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
- Troubleshooting
- Performance
- Security

Process Mining

DELIVERY:

Automation Cloud Automation Cloud Public Sector Automation Suite Standalone

RELEASE: 2021.10

Last updated Sep 2, 2024

Steps to roll-out TemplateOne 1.0.0

Introduction

This page describes the necessary steps to roll out a customized version of TemplateOne to end-users. It starts with the input data and covers all the steps that are needed to provide the data in a meaningful way to end-users.

Step 1: Set up the TemplateOne for development.

Step 2: Customize TemplateOne.

Step 3: Release the customized version of TemplateOne.

Step 4: Configure the database connection for TemplateOne.

Step 5: Run the transformations and load the data.

Step 1: Set up TemplateOne for development

Follow these steps to set up TemplateOne for development.

Step	Action
1	Upload the TemplateOne release (.mvtag) to the Superadmin Releases Tab.
2	Create a new app and use the released TemplateOne app as the base app. See Creating Apps - Creating an app from a base app. Make sure that you select the Git repository you created for the app.
3	Go to the Git repository and create a local checkout of the TemplateOne branch. This enables you to work on the content outside of Process Mining. It is advised to use a Git GUI client. For example GitKraken or GitHub Desktop.

Release contents

The local checkout contains several files and folders. See the illustration below.

Below is an overview of the main contents of the release.

Folder	Description
`.mv`	Folder containing the information of the build of the Process Mining software.
`.vscode`	Workspace settings that are relevant when working in Visual Studio Code.
`dashboards`	The `.mvp` file containing the dashboards definitions.
`documentation`	System and process specific documentation. For example, how to configure the specific SQL connector, an explanation of the process, and applicable design choices.
`extractors`	Instructions on extracting data and loading it in the database. By default, CData Sync is used to extract data. A load-from-file extraction is included, that enables you to load raw data files that fit with the input of the connector.
`resources`	Folder containing translation files and dashboard settings.
`sample_data`	`.csv` files in the format of extracted data that you can use as a sample dataset in case you do not have a connection with the source system. This sample data fits with the input of the connector so that you can use it to validate your development setup, but also to preview the released app.
`scripts`	Scripts to automatically extract, transform, and load the data, that you can schedule in your production environment.
`transformations`	The dbt project containing the SQL statements to transform the data.
`.gitignore`	Git specific file that lists the contents of the app which should be ignored in version control.
`build.txt`	Info on the connector and dashboard part that were combined to create this app.
`license.txt`	Standard license file of the UiPath Process Mining product.
`release_notes.md`	Release notes of the app.
`settings.json`	Internal settings for the app. The contents of this file do not have to be updated.

See the illustration below for an overview of the setup.

Step 2: Customize TemplateOne

When TemplateOne is set up for development, you can customize the transformations and edit the dashboards as desired.

See Customizing a SQL connector.

See App and Discovery accelerator development.

Step 3: Release the customized version of TemplateOne

Follow these steps to make the customized version of TemplateOne available to end-users.

These steps must be performed on the Process Mining server.

Step	Action
1	Create a release. See Creating Releases. A release tag is created in the Git repository. This version is to be installed on the production server.
2	Deploy the release. See Deploying apps and discovery accelerators.

Step 4: Configure the database connection for TemplateOne

To load data from the SQL Server database for use in TemplateOne you must configure the connection to the SQL Server database. You can do this by specifying the Configuration Settings in an external configuration file in .csv format. The TemplateOne.settings.csv file is included in TemplateOne release.

Important: All SQL Server databases that have a 64-bit version can be accessed using an ODBC connection. The required 64-bit ODBC driver must be installed on the UiPath Process Mining server, and the server must be able to access that specific system.

Follow these steps to configure TemplateOne.

Step	Action
2	Go to the Superadmin Workspaces tab, and locate the Dashboards folder. See the illustration below.
3	Download the `TempateOne.settings.csv` file and configure the settings as described below.
4	Go to the Superadmin Server data tab and upload the `TemplateOne.settings.csv` file. Important: Make sure you use the exact name of the file (`TemplateOne.settings.csv`).

Note:

The TemplateOne.settings.csv file:

uses ; as delimiter and “ as quotation character.
must contain two lines: a header line with predetermined field names, and a line containing all values.

Configuration fields

Below is a list of the fields in the TemplateOne.settings.csv that can be used to configure TemplateOne, with a description and expected or example values.

Setting	Description
Driver	The name of the ODBC driver used for the SQL Server database connection. For example, `ODBC Driver 18 for SQL Server`. The driver must be installed on the UiPath Process Mining server, and the server must be able to access that specific system.
Server	The name of the server on which the SQL Server database is installed.
Database	The name of the SQL Server database that is used for TemplateOne.
Schema	The name of the schema in the SQL Server database that is used for TemplateOne.
User	The user account that is used to log in to the SQL Server database.
Use credential store	Define whether the credential store is used. Possible values are `true` or `false`. If this setting is set to true, the password field must contain the identifier for the credential store password field you are trying to use. See Use a Credential Store.
Password	Password of the account that is used to log in to the SQL Server database, or the password identifier from the credential store. In case the credential store is used, Use credential store should be set to true.

Using a Credential store for password storage

A credential store allows you to use passwords without showing the actual password. For the ODBC connection from the SAP Connector to the SAP database, it is also possible to use a Credential store to store the actual password of the SAP account in a secured way. For more information, see Use a Credential Store.

Step 5: Run the transformations and load the data

Perform the following steps on the production server to run the transformations and load the data into the SQL Server database.

Step	Action
1	Check out the released version of the app on the production server. It is advised to use a Git GUI client. For example GitKraken or GitHub Desktop.
2	Configure the dbt project and the profiles. See .
3	Configure the scripts for CData Sync and dbt. . .
4	Run the SQL Connector: • Start Windows PowerShell as admin. • Go to the `scripts/` directory. • Execute `run.ps1`.

On this page

Introduction
Step 1: Set up TemplateOne for development
Release contents
Step 2: Customize TemplateOne
Step 3: Release the customized version of TemplateOne
Step 4: Configure the database connection for TemplateOne
Configuration fields
Using a Credential store for password storage
Step 5: Run the transformations and load the data

Was this page helpful?

PREVIOUSGetting Started with TemplateOne

NEXTInput tables of TemplateOne 1.0.0

Support and Services

Get The Help You Need

UiPath Academy

Learning RPA - Automation Courses

UiPath Forum

UiPath Community Forum

Trust and Security

Cookies Policy