This guide gives you a quick introduction to custom dashboards: how to create datasets and charts and organize them into a dashboard. Since WorkFusion Analytics is originally based on Superset, you can refer to the Superset official documentation for additional details.
The goal of this article is to provide insight on how to deal with a customer’s information without risk of sensitive data disclosure to third parties not involved in the project.
Allows managing of database and S3 data operations.
The role-based access mechanism (RBAC) limits access to data through Analytics dashboards based on the following filter categories:
To monitor process metrics, Work.AI offers Superset-based Analytics installed together with the Product. To start working with it, you only need to configure access for users. It does not require any additional third-party licenses and provides the following capabilities:
Global variables store common values used in different Business Processes (BPs) without hard-coding them in Bot Tasks. In particular, global variables can store the following information:
Work.AI generates a considerable amount of data. Much of it results from completed Business Processes (BP) or internal maintenance. Accumulation of obsolete data can lead to the following issues:
The page describes the process designed to enable the following:
The Overview dashboard provides a high-level summary of daily operations and overall automation health. From it, you can access the following data:
To access the dashboard, navigate to Analytics > Dashboards and click Scheduler monitoring on the dashboard list.
To manage the access to Superset dashboards and related components, use standard Control Tower roles and permissions. To view or change the Superset-related permissions in Control Tower, navigate to System setting > Role management.
To assist you in real-time process monitoring, analyzing data, and presenting it effectively, WorkFusion Analytics offers the following tools:
You can start a Business Process (BP) from a Manual Task. Below are some code samples of how you can perform various operations with it.
A Data Source is a mechanism providing input data and configuration for your Business Processes (BPs) and tasks. The input format is best suited for those use cases where the data resides on an external source, such as an SFTP Server or Amazon S3 Cloud.
Before labeling, the most essential information the Subject-Matter Expert (SME) should share with the Data Analyst (DA) includes the following:
To validate the accessibility of an S3 object from a different host, follow the steps below:
Goal of the step: Train Subject Matter Experts (SMEs) to provide a high level of labeling accuracy for collecting a quality dataset.
To upload files to the Amazon AWS S3 storage, install and use one of the following third-party S3 clients:
There are several ways how to upload files to MinIO. You can upload files to the storage in a web browser or via the Master Server.
The Split-Join rule is used to separate every single record (or document) from Input Data into a few records to let them pass through different steps (either Bot or Manual Tasks) of a Business Process (BP) in parallel (in the split point) and then combine the processed records back into a single record or a document (in the join point) to process the consolidated results from the previous steps further.