This article walks the reader through how Automated Insights works and how to explore it
ClearQuery was designed to provide its users with immediate access to key pieces of information, which we refer to them as "Automated Insights." During data ingest / update, ClearQuery analyzes the user’s data and highlights key pieces of information, outliers, and other points of interest. These insights are generated immediately, providing users actionable analytics with minimal effort, by displaying trends and analytics in visual formats and written language – This is done for two reasons:
- Actionable Insights are key to user success.
- Time is money and CQ’s goal is to save the user both!
This article will take the user through how to use and fine-tune the Automated Insights feature to better suit their analytical needs.
Within Automated Insights, there are multiple tabs available: Categorical, Numeric, and Geographical Insights. Based on the user’s data, ClearQuery breaks the insights down into these three categories which provide valuable information in different ways:
- Categorical Insights provides analytics based on the fields within the imported dataset that were marked as categorical for the field type.
- Numeric Insights provides analytics based on the fields within the imported dataset that were marked as Number or Decimal for the field type.
- Geographical Insights provides analytics based on geographical coordinates stored within the dataset. (Currently only provided for Elastic connections and manually uploaded data)
Categorical and Numeric Insights
Within these two tabs, charts are configured similarly. Each chart provides several different pieces of information as well as mini features:
Beyond the visual display ClearQuery provides analytical insights in written language directly beneath each chart / graph, allowing users to gain insights without having to interpret the chart themselves.
Note: Charts in CQ are configured by default to show the top 10 results from a given field. Showing more than 10 results can make the visual difficult to interpret. AskCQ allows users to define the number of fields to include in a chart – “Show me the top 25 “cities.”
In the top right corner of each chart the user will find two buttons:
- Save button (💾): Once the user has configured the chart to be the appropriate view, it can be saved by clicking the save icon. The user will be prompted with the following:
- Name - Give the chart a name that describes the purpose of the chart, this will allow other users to understand the value it provides.
- Owners - Provide ownership to other users - this permission allows other users the ability to view, modify, and / or delete it.
- Dashboards - Immediately assign this chart to a dashboard by selecting the desired one.
- Save to Home checkbox - assign the chart to the user's customizable Home Page.
- Change button (🔧) - This allows the user to change the chart type.
Depending on the data displayed within the chart, the chart feature may allow the user to change how the data is presented within the chart. At the top left of the chart, the user can see a description of the chart “Number of records broken down by Categorical Keyword.” Notice how there is a dotted line underneath “Number of records” - this field can be changed to:
- Average
- Maximum
- Minimum
- Sum Total
When the user modifies this field, the system also allows the user to change the source field as well. Note: Once the user makes the appropriate changes, they must save the chart to use it in the future. If the user leaves Automated Insights or refreshes the page, the chart will revert to the original Automated Insight configuration.
Underneath each chart there are up to two buttons that can be selected to see the data in a different format:
"Show data in tabular form" shows the data in a table format - showing the top 1000 results, allowing the user to see the total figures for more entities than are displayed in the chart:
Show Categorical Trends: If your data contains a date field, this button shows how the data within the chart has changed over time.
At the bottom of the chart, you can narrow in on a specific date range by moving the sliders on either side of the chart.
All insights can be further filtered via the Filter menu or by clicking into the chart itself.
Recommendation Engines Layout:
For Categorical and Numeric Insights by default, if the dataset has “current” data, meaning data from within the last 30 days, Automated Insights will display charts based on the system’s Recommendation Engine. If the user wants to change the ordering of the insights, the users can do so by clicking on the customization cog in the top right corner of the feature and setting their preferred order. To make that order display or to turn back on the Recommendation Engine order, simply switch the toggle between Recommendation Engine and My Order, as seen below:
Geographic Insights
This tab is where ClearQuery takes the data, containing geographic coordinates (geolocation field types) and displays the data over a map. Data points within proximity to each other are grouped into buckets. Users can either zoom in on the map or select a bucket to narrow in on it.
In the top right of the map, the following information is provided:
- Precision: Indicates the accuracy of the map based on the level of zoom. As the user zooms in, the precision becomes more accurate.
- Points: Displays the number of records currently being shown on the map.
Below that, the user can change the view from either Marker Clusters or Heat Map, and the user can draw a bounder box to create a custom map filter.
If you have additional questions regarding this topic, please reach out to your Account Manager or contact ClearQuery Support (support@clearquery.io).