← Back to Blog

Data Visualization with Discover

Informer Discover Makes Visualizing Data Easy

With Discover, Informer 5 does a lot of the thinking for you by automatically serving-up interesting business intelligence Visuals based on the Filters and type of Fields you select. This is a huge timesaver!

In Discover, you simply click on the filter icon to identify the criteria you want to use to visualize and explore data on a macro level in your Dataset. See Figure 1.

You can also apply data filters to your individual charts within a multi-chart view without affecting the other visuals. Just select a field you want to analyze without being concerned with how you want to present it. Then quickly change the charts and other information.

Sort & Group Data Instantly

Discover groups all your Dataset column fields by data type (i.e., text, date, Boolean). This enables you to make quick selections and see resulting data visualization displays based on the type of field you choose. By selecting Boolean fields (Yes/No-type information) the resulting visual quickly shows you how many of the characteristic you have, or don’t have. See Figure 2.

Date fields generate trend analysis charts. Location fields generate geographic maps (e.g. heat maps, Google Maps, state maps, county maps, etc.). You can also combine multiple selection fields to aggregate information into a singular chart, for example: revenue, gender, age, location. The Leaderboard visual provides a ranking based on values associated with what you are aggregating.

Visualize Data in Multiple Ways

Visual options vary depending on the type of data visualization you are configuring:

  • A pop-up list enables you to change the chart type. You can also change the title and description for the Visual.
  • For graphical Visuals such as pie or column charts, you can change the chart type, Y-axis value, primary and secondary grouping value, and maximum number of items to show.
  • If the selected Field is a date, you have the option to change the Interval (Year, Month, Day, Month of Year, etc.).
  • For Leaderboards, you can change the Field to display the aggregate value used for ranking See Figure 3.
  • Pivot tables allow you to change the Fields used for rows and columns, as well as the aggregate value used in the body of the table.

Filtering on Areas of Interest

Filters are a very powerful data analytics productivity tool in Informer. They enable you to easily narrow down your data to focus on your area of interest. There are two types of data Filters within Informer – Dataset Filters and Visuals Filters.

Visual Filters – In addition to the overall Dataset Filters, Visuals have their own Visual Filters that apply to a specific Visual. Discover displays all the selectable fields within its Visual Card view, as shown in Figure 3. When you select different combinations of these fields, you will see how easy and fun it is for you to uncover new insights into your data from all the Visuals served up. To narrow down your Dataset even further, simply continue to add more Filters. See Figure 4. You can merge multiple filters together or save a specific filter. You can also save the filters for your Visual in your Datasets.

Dataset Filters – Enable you to narrow the scope of Visuals so you can quickly glean business intelligence insight into your area of interest without needing to configure charts or graphs. For example, if you select a location based field, Discover will automatically present heat maps highlighting the data behind the location field, (e.g., a Visual of Total Student Enrollment across the United States). By selecting a combination of fields, you automatically see Visuals like Trend Charts, Leaderboards, Averages, Totals, and Statistics.

Discover Reports

There are two types of Reports used in Discover: Dashboard Reports and Comparison Board. After choosing the Dataset you would like to visualize and selecting a field to group your data, you will be presented with several different Visual options (Date Fields, Text Fields, and Numeric Fields).

  • Date Fields display Visuals such as trend charts, pivot tables or statistics. (See Figure 5).
  • Text Fields – For text fields such as country, state, or city, using maps and possible leaderboards or other similar charts would best complement your data visualization. To generate new Visuals from text fields, choose your desired values underneath the fields indicated by green quotation mark icons. (See Figure 6).
  • Numeric Fields – Create statistics, total boxes, leaderboards, and similar charts. (See Figure 7).

Related Posts