Onboarding Guide For Viewers (Advanced Analytics)

For Viewer group, Advance Analytics (AA) enhances the data visualization experience by providing advanced charting options, interactive widgets, and intelligent features powered by Artificial Intelligence and Machine Learning. With AA, you can delve deeper into your data and gain valuable insights, enabling a richer and more engaging experience as you explore and analyze information.

Interacting with Widgets

  • As an viewer now you can drill down to a widget to gain better understanding of data. Here is an article to help you get started with it - Drill into a widget example

  • Now you also add or remove a columns/rows into a pivot table without editing the widget itself. Please follow the example to get more clear understanding - Interactive Pivot

Monitoring your key KPIs

  • Now you can monitor and get alerts for the important KPIs using Pulse. To enable Pulse and alerts here is an article that will help you Pulse.

Using AI/ML features

Insight Miner:

  1. Insight Miner can be access by clicking on the widget menu (ellipsis) → Get insights

2. Under Get Insights, the available data point will be listed to run Insight Miner → select the data point to get the insight. New window will popup listing most of the findings.

Explanations:

This feature helps you to understand what caused the data to change it could it sudden spike or drop into the values or change in pattern.

  1. For example over here we have scrap rate on daily basis. and want to understand what caused the spike on 24th Apr → Right click on data point → click on explanation

2. In the Explanation pane you could see the breaking point, anomalies and your selected point ( A ). You can also change the date against which you need the explanation ( B ). And on the right you could see the possible explanation for this change ( C ) .

3. The score for the Explanation shows that “Machine Wrapper” is the strongest Explanation (Contributed the most to the change in Scrap value between 17th Apr and 24th Apr). Other fields such as Scrap Group and reasons also contributed to the change but with a lower score.

 

 

  • Keep in mind that, depending on your data, the Possible Explanation with the highest score might not always be the most suitable. You will usually know, based on context, which explanations make the most sense in your case

  • You can delete a Possible Explanation, if you'd like to.

Exploration Paths:

  1. To view exploration widgets Click on the light “bulb icon”  in your indicator widget → A window is displayed with suggested exploration widgets.

  1. Switch between the two tabs “Break by” and “Trend over time” to view all the exploration widgets.

  2. To download an exploration widget to a PNG file, click the  button at the bottom of the widget.

  3. (Optional) To provide positive feedback to the algorithm about the exploration widgets, you can like the widget . This provides more input to the algorithm, enabling it to optimize its results over time.

 

Note that clicking  “I found this useful” would not influence the results already upon your next session with the widget, as it takes time to refine the results.

 

To know more how these Advanced Analytics AI features algorithms works Click Here!!!

Quest:

Quest enable user to apply the set of enabled advanced analytical analysis on the widgets to access the quest models .

  1. To access these model click on Deep analysis → select from the list of enable models

Deep analysis option would be only visible if Quest models are enabled by designer for the widgets

Here in example we have selected Local Estimate ,post which you could see a estimate line over the chart along with the description.

 

Details for the data requirements of the quest model can be used can be found here: https://slxdev.atlassian.net/wiki/spaces/SD/pages/2615017515