The GoodData demo workspace comes with several Insights to illustrate how GoodData's Analytical Designer works. We suggest that you review this article before proceeding to Getting Started with Building Insights and Getting Started with Building KPI Dashboards
In this section, you will examine six chart types that we ask you to modify further. However, feel free to explore the options and settings on your own. To preserve the insights in their original form, ensure that you click the Save as new button.
Percentage of Customers by Region
Chart type: Stacked area
Purpose: Analyzes the share of customers in sales regions over the last 12 months.
In the VIEW BY section, you can change the date granularity and group data by quarter or you can also apply regional filters.
Revenue by Category Trend
Chart type: Stacked area
Purpose: Shows revenue trends as shares per product category since data collection began
Go to Configuration and experiment with colors and labels (Canvas section). As you will see, using labels in this visualization is rather counterproductive.
Product Revenue Comparison (over previous period)
Chart type: Column chart
Purpose: Compares revenues per product category in the last 12 months with the revenues from the previous 12-month period.
As you can see, GoodData offers a suggestion for the next step of your analysis in the RECOMMENDED NEXT STEPS box. Click Apply and see what changes.
Chart type: Treemap
Purpose: Offers a visual map of resources spent per campaign category and name. Hint: Expand the browser window to reveal text tags.
Play around with filtering to restrict the chart to a campaign type, name or category.
Revenue per $ vs Spent by Campaign
Chart type: Scatter plot
Purpose: Explore which campaign was the most effective in terms of revenues per every dollar you spent.
Drag and drop the measure from y-axis (Revenue per Dollar Spent) onto to the Measure (X-AXIS) field to switch the axis.
Chart type: Combo chart (columns + lines)
Purpose: Explore correlation between revenue and number of orders over time.
Adjust the density of the date visualization in the VIEW BY field by grouping the data into quarterly or weekly segments. You can further analyze the data by dragging the Product Category measure onto the FILTERS bar. Then select which product categories you want to analyze.
There are two KPI Dashboards in the demo workspace - Overview and Product Details. They both start with simple KPI displays using essentially simple standalone measures taken directly from the data catalog and modified by the Date range filter.
Dashboards are interactive.
For example, you can quickly change the time frame for the data display simply by changing the date range in the View mode:
The Date Filter applies to all elements on the dashboard. However, you can choose to exclude individual elements in the Edit mode by unticking the Date option.
Explore how individual elements react to mouse/cursor movements.
Again, we encourage you to experiment with the demo dashboards to understand their behavior and capabilities.
Now that you explored the insights and dashboards in the demo workspace, you can proceed to build your own: