Data Sources

An overview of data sources and its advanced data collection functionalities

A data source simply assembles data stored in data tables and provides a visual summary of the data in the form of rows and columns.

In Quixy, there are three unique concepts in defining a data source, the adoption is same, but the process of data collection varies:

1. You can JOIN two or more data tables to create a Data Source,
2. You can MERGE two or more data sources to create a mammoth data source, and
3. You can even write SQL QUERY to accumulate data from the data tables.

Both the concepts share the same responsibility in adoption & standard actions.

Usage/Adoption Types:

1. Generating Reports (Grids, Charts, Documents)
2. Views (List screen)
3. References (fetching data into application)

• Add-ons (Static Columns & Business Rules)

Manage Data source: View Records, Edit Data source, Copy Data source, Rename Data source, and Delete Data source.

Let’s deep-dive into the details of the data source Adoption Types and Actions:

Data source Adoption Types

1. Report: A report uses the data from a data source to transform it into an infographic or tabular representation that helps users to make informed decisions. Quixy’s report engine is capable of transforming data into 40 distinct representations. Look at Chart Report.

2. Views: A view is an actionable report. It draws data from a data source and represents it in a tabular form providing you the capability of configuring the pre-defined actions that can bridge a process. Learn more about Views.

3. References: References empower the users to fetch the existing data of a database into applications to fulfill the needs of a use case. Learn more about References.

Add-Ons: This provides a leverage to the adoption techniques by allowing the users to create and attach external data fields to the selective data source. However, this will always remain in a stand-by position without effecting the data source until it is used in any of the Reports, View, or References. You will have two options when configuring an Add-on.

1. Static Columns: This provides you the opportunity to add an extra data column with static data.
2. Business Rules: This option allows you to dictate how the data should orient in the static columns and the data source. These business rules work the same way it happens in app creation. Learn more about Add-Ons.

Manage Data sources

Actions allow the admins to maintain/diagnose a data source to ensure its working condition and make changes according to the required manifestations. Below are the various actions available for a data source:

1. View Records: This to preview all your data records on one page.
2. Edit Data source: This to make changes in the data source.
3. Copy Data source: This is to produce a duplicate copy of a data source with defined requirements.
4. Rename Data source: This is to adjust the name of a data source. You also have a straightforward way to rename a data source. Refer to the GIF below.
5. Delete Data source: This is to delete a data source. However, there is a condition that the data source must be freed from all its relationships before deleting it.

Data Source Notifications

This enables citizen developers to effortlessly send personalized, data-centric emails to users, allowing them to take meaningful actions directly on the data using supporting artifacts. With Data Source Notifications, there's no need for additional tasks; this feature ensures that you stay in control and keep your data dynamic and up to date.

Data Source Scheduler Notifications

Scheduler notifications are automated alerts or messages that are triggered based on predefined schedules or conditions. They are often used in software applications to notify users about important events, deadlines, or updates.

How do Scheduler Notifications Work?

Scheduler notifications work by allowing users to set up rules or schedules for when notifications should be sent. These rules can be based on time triggers (e.g., send a notification every day at 9 AM) or event triggers (e.g., send a notification when a specific condition is met in a data table).

Types of DS Schedulers

Individual Type: The individual scheduler feature allows users to set up custom schedules for specific data records or entries within a data table, triggering actions or notifications unique to each record. For instance, in a task management system, each task record could have its own individual scheduler to send a reminder email when its deadline approaches. This capability enables personalized and targeted communication, ensuring that each data record is managed according to its specific requirements.

Group Type: The Grouped type in Data Source Scheduler Notifications allows users to group related data according to a chosen data column and send these grouped records as separate email notifications. This is particularly useful for organizing updates or notifications based on specific criteria within the dataset. For example, in a sales application, you could group sales leads by region or by product category, sending separate notifications for each group.

List Type: The List type in Data Source Scheduler Notifications consolidates all data records into a single email notification. This simplifies communication by providing a comprehensive list of all records in a compact format. For instance, in a task management system, you could use the List type to send a daily summary of all tasks assigned to a team, ensuring everyone is informed about the current tasks without overwhelming them with individual notifications for each task.