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Data source:

Before you start

    1. Getting started

    • Create your first insight
    • The data model
    • Saved metrics
    • Filter variables
    • What's next?

    2. Model refactoring

    • Querying multiple tables

    3. Advanced metrics

    • Simple aggregation locking
    • More aggregation locking
    • Advanced aggregation locking
    • Ranking filters
    • What's next?

    4. Upload your file

    • What's next?

    Create your first insight

    Now it is time for the fun stuff. You should be in the Analytical Designer screen that looks like this:
    Drag and drop user interface to create create insights.
    You can see the columns of your file in the catalog panel on the left. The modeling metadata (facts, attributes, human readable column names) provided in the last step help GoodData to provide this intuitive interface.
    Let’s create an insight:
    • To get started, simply drag the “Order ID” column onto the Measures panel. This automatically creates a Count of unique Order IDs.
    • Note that the system knows to apply a Count as we annotated the “Order ID” column as an attribute instead of as a numerical fact.
    • Note that if you drag in “Order Line ID,” you will get a different count.
    • Then, use the Compare helper to slice by “Category.”
    • Finally, drag “Order Status” to the Stack By panel to further slice the columns.
    Using recommendations to leverage the currently displayed insight.
    We have a first insight! Click the Save button at the top right corner of the screen to save it for later. Name it: “Orders by Status and Category”.
    Let’s try another one.
    • Click the Clear button in the toolbar to clear the insight.
    • Drag the “Price” column into the Measures panel. This gives us the Sum of all prices on all order lines, but it does not consider how many times the products have been sold at their price.
    • Note that we can apply different mathematical functions to this column, because the Price column was annotated as a numerical fact.
    • Click the little chevron icon to the left of “Sum of Price” item in the Measures panel, and change “Sum” to “Average” to show the average product price.
    • Now, drag “Category” to the View By panel.
    We can see that the “Outdoor” category contains the highest priced items. But what is the range of prices?
    • Click the little chevron icon to the left of “Sum of Price” item in the Measures panel, and change “Average” to “Minimum.”
    • Drag another copy of the “Price” column to the Measures panel. Click the little chevron icon to the left of “Sum of Price” item in the Measures panel, and change “Sum” to “Maximum.”
    Now we can easily see the range of prices for each category.
    Viewing price range for each category.
    Given the ease of use, many analytical queries can be handled by business analysts or regular users instead of needing an engineer to write SQL for each of these variations!