Overview
Business Insights for Automation Service lets you expose and save in Automation Service, your Bizagi processes’ business information so you can use it for specific purposes like creating reports with third party tools or for AI analysis.
This is an additional service, purchased separately from your Automation Service subscription.
You can easily configure how and when the information is extracted from processes in Bizagi to make sure data preparation (cleaning, selecting data) is complete and that your datasets to contain high-quality data which is final and reliable when consumed.
For introductory information on this application, refer to Business Insights service.
This section describes the following topics:
•How to create a dataset.
oDataset structure (csv or manually).
oDataset Business key.
•How to delete a dataset project.
If you want to create a dataset for Reporting or Artificial Intelligence read carefully the Business key step.
To create a new dataset, follow these steps:
1. Log in to the Bizagi Business Insights service portal
When the service has been purchased, you will have access to an exclusive BI URL at https://bi-[YourCompany].bizagi.com/
Access rights are managed from the Customer Portal.
Log in providing your user credentials.
2. Create a new Business Insights service project
Click the plus icon to add a project.
A Business Insights service project's main purpose is to help you organize and manage the datasets you may have.
A Business Insights service project is not related to a Bizagi project and its processes.
Give the Business Insights service project a name, a meaningful description, and click Create Project when you are ready.
Click the New dataset button for a given Business Insights service project,
Give the dataset a name, a meaningful description and define its column structure.
You can either load a .csv file for the dataset to take the file's columns as definitions, or manually define columns.
Defining the structure from a .csv
If using the .csv option, click Select a .csv to upload your file:
The dataset automatically detects the data type of each column.
It is important that you double-check that each column is set with the appropriate data type. If there is a problem, you can manually change a column's definition.
You can choose String, Numeric, Boolean or Datetime as the data type.
Defining the structure manually
Click Create a schema manually to define each of the columns by entering its column name and choosing its data type:
You can choose String, Numeric, Boolean, Datetime or Collection as the data type.
Once the dataset structure is defined you must choose whether it will have normalized data or not. This is defined by assigning a business key that serves to differentiate each data record within the dataset, that is, there is only one data record per specific business key.
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Once a dataset is created is not possible to add or delete the business key. |
The business key can be one column or a combination of multiple columns.
If you defined one or more columns as the business key, there can be no duplicate records.
If you do not define a business key, there can be duplicate records.
We recommend carefully analyzing the use case of your dataset. The following table summarizes the use cases.
Use cases |
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With business key |
•Datasets for Reports generation. •Modify data within the dataset (using the business key). •Non-duplicate records (e.g. Id numbers, user names, email) |
Without business key |
•Datasets for Artificial Intelligence (AI) •Duplicate records (e.g. car brands, countries, item categories) |
The business key is defined simply by selecting the columns that will take this role. Columns with collection type data cannot be part of the business key.
Dataset with Business Key |
Dataset without Business key |
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Finally, click Create dataset. A warning window appears confirming the action since once a dataset is created is not possible to add or delete the business key.
With a defined business key
Without a defined business key
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Regardless of how the structure was defined, you can update it by adding extra columns manually. However, the new columns can not be business keys. |
At this point, your dataset will be created. You can start using it right away.
The created dataset should appear under a Datasets service project, and you can find its three default environments: Development, Testing and Production.
To delete a dataset project select the Delete project option at the right of the projects name.
When you delete a project you do not delete the default environments datasets or their records, but rather you delete the access to the project from the Business Insights portal, meaning that the Bizagi processes and the external applications that are connected to these can keep feeding, updating or consuming the data in the datasets.
Next steps
To learn about these different environments and their uses, refer to Dataset environments.