Advanced Dashboards (Amazon QuickSight)
For organizations that require advanced BI capabilities and reporting, we have partnered with Amazon QuickSight to provide extensive capabilities to connect, store, manipulate, and visualize data.
We have recently launched a new integration with Amazon QuickSight to replace DOMO as the default advanced dashboard provider. This new integration offers even more robust capabilities built directly into the Zinier product. For more information on QuickSight, contact your customer success manager.
Overview of Amazon QuickSight
This page is intended to provide an overview of how Zinier works with Amazon QuickSight. For more detailed documentation on how to build dashboards and manipulate data in QuickSight, go to the Amazon QuickSight Documentation.
Amazon QuickSight is a cloud-based BI tool that when integrated with Zinier, allows you to create and share Dashboards and Reports, providing extensive capabilities to connect, store, manipulate, and visualize data. An overview of the capabilities is listed below:
Data Preparation
Clean, transform, and combine data for better visualization using tools that don’t require extensive knowledge of SQL or ETL.
Data Visualization
Visualize data in graphs, charts, and other visualization options via a drag-and-drop interface.
Create customized dashboards and collections to organize, analyze, and report on your business data.
Organize the data with advanced data permission by role, department, or even KPIs.
Data Sharing
Schedule reports to individuals or groups at specific dates and times.
Embed single cards or entire dashboards in the Zinier app to mix visual cues with transactional data.
Frequently Asked Questions (FAQ)
What is Amazon QuickSight?
Amazon QuickSight is a Business Intelligence tool that Zinier solutions will use to create and share Dashboards and Reports for customers.
What is a Dashboard vs Analysis?
An Analysis is QuickSight’s Authoring experience. Here you can create edit existing dashboards, create new dashboards, adjust filters, manage branding, etc.
A Dashboard is QuickSight’s Reader experience. Here users can interact with dashboards, filter views, export data, etc.
How do we Partition and Protect Customer Data?
There are customer specific datasets, dashboards and analyses. During the DevOps stage, authentication & authorization access for the customer solution is set up to manage the visibility for the respective customer datasets.
What are User Roles in QuickSight and how does that relate to Zinier?
QuickSight has three main roles: Admin, Author, and Reader.
Admin: Admins can add new datasets and update existing datasets and perform other administrative tasks such as purchasing additional SPICE capacity. Admins can also perform Author and Reader actions.
Author: Authors can edit an Analysis and publish dashboards. In Zinier, Users with a Solution Admin or Solution Developer role will also have Author permissions.
Reader: Readers can view and interact with Dashboards. In Zinier, Web User (or similar) role will also have Reader permissions.
Can a single Zinier org use information from other Zinier orgs to create dashboards?
Yes, we can point orgs (such as a Parent org with multiple Child orgs) to the same namespace and leverage data across orgs to create dashboards.
How do I access a Dashboard or Analysis in Zinier?
Note: All QuickSight access for an Org will be contained in Zinier.
If a user has a Web User role in Zinier, they will be able to see any Dashboards for their organization in the Dashboard Module of their solution.
If a user has a Solution Admin/Developer role in Zinier, they will able to see the QuickSight Authoring experience in Studio Z embedded in the Dashboard page. They will also be able to see any published Dashboard in the solution’s Dashboard Module (Like a Web User)
Reader View
The Reader view is what users see from the QuickSite Dashboard module within the Zinier web application. As mentioned above, Web User (or similar) role will also have Reader permissions in Zinier.
Out-of-the-box Dashboards
By default, users with access to the Reader View will be able to access 5 out-of-the-box dashboards:
Work Order by Status (pie chart)
Tasks by Status (pie chart)
Technician Efficiency (Bar Chart)
Task Completion rate (by day) (Bar Chart)
SLA Compliance (Bar Chart)
What can I do as a Reader?
Filtering Dashboards: Filter dashboards at a page level or on individual visualizations to get the most useful view.
Drilldown: Double click into dashboards to see additional views
Export: Export CSVs of visualizations in your dashboard
Authoring Capabilities
How can I edit (and publish) the default Dashboards?
If you have a Solution Admin/Developer role, you will also be able to edit and publish changes to the default dashboards from within Studio Z. To do so follow the steps belowL
Open the Studio Z app by clicking on the Zinier Apps icon on the top right of the screen.
Navigate to the Studio Z > Dashboard module
Open the analysis titled: <org_name>_analysis
Edit any of the default Dashboards here
When you are done editing, select “Publish dashboard” and choose the option to “Override a Dashboard” to ensure the changes are reflected.
Your particular solution’s dashboard should be selected by Default. If it’s not search for, <org_name>_dashboard.
How can I create and publish new Visualizations?
Note: At this time, Authors can only add additional sheets in an Org’s existing analysis. Solutions cannot create new a new analysis or embed dashboards to other Zinier modules.
To create and publish new visualizations, follow the steps below:
From the Dashboard module in Studio Z, Open your org’s analysis
Select a Visual type from the menu on the left and add it to an existing sheet or new sheet in the Analysis.
Select from the available fields from the Field list within a dataset to build your visualization. Learn more about each visual type here.
Once you are done Authoring, select “Publish dashboard” and choose the option to “Override a Dashboard” to ensure the changes are reflected.
Your particular solution’s dashboard should be selected by Default. If it’s not search for, <org_name>_dashboard.
Can I use multiple datasets in a single Visualization?
No. QuickSight only supports one dataset per visualization.
Can I filter across multiple datasets?
No. QuickSight filters are tied to a dataset. They will only apply to visualizations using that datasource.
How do I perform ETL on data?
“Extract, Transform, and Load (ETL) is a three-phase process where data is extracted, transformed and loaded into an output data container.”
In our prior tool DOMO, Zinier workflow outputs or calculations were directly connected to and stored in the DOMO instance. In QuickSight, we can't leverage any workflows/calculations directly but we can store the results of the workflow in a Zinier model and use that in QuickSight. An alternate method is to use raw, existing Zinier models and perform calculations/general ETL in QuickSight using their Aggregate Functions and Calculated fields.
Our recommended approach is to perform necessary ETL + Calculations and build data models in Zinier before building visualizations in QuickSight.
Standard Chart Types
For more information on visual types / charts, visit the QuickSight documentation her
Visual Type | Purpose |
---|---|
Single Measure Bar chart | Visualizes values for a single measure for a dimension grouped by another dimension. Each bar represents the grouped dimension and each partition within the bar represents the value of the child dimension. |
Clustered Bar chart | Visualizes values for a single measure of a dimension grouped by another dimension. Each group (parent dimension) has bars representing the child dimension. |
Stacked Bar chart | Visualizes values for a single measure for a dimension grouped by another dimension. Each bar represents the grouped dimension and each partition within the bar represents the percentage of the value of the child dimension. |
Stacked 100 Percent Bar chart | Visualizes changes of one or more dimensions over a period of time. |
Line chart | Displays lines with areas below them color-coded to make it easier to compare values relative to each other. |
Area Line chart | Displays lines with areas below them color coded to make it easier to compare values relative to each other. |
Combo chart | Consists of a line chart and a bar chart to visualize two different types of data. |
Pie chart | Displays the proportionality of values of a dimension relative to each other. |
Donut chart | Visualizes the weights of each value in a dimension. |
Gauge chart | Displays one dimension in comparison to another dimension. |
Key Performance Indicator (KPI) | Visualizes a key value and its target value. |
Scatter plot | Visualizes two or three measures for a dimension with different sizes of bubbles to represent the number of items for that intersection of measures. |
Heat map | Visualizes the intersection of two dimensions with color coding to differentiate the category or intensity of the range. |
Tree map | Visualizes one or two measures for a dimension with the size of each rectangle representing a value’s proportion relative to other values. |
Word cloud | Displays how often a word appears compared to other words in a data set. |
Geospatial chart | Visualizes the values of one or more dimensions across a geographical map with the size of each circle representing the value of an item for that location relative to other locations. |
Table | Displays the customized table view of data. |
Pivot Table | Displays the values for the intersection of two or more dimensions in a table. |