Getting Started with Loading CSVs to GoodData

In this tutorial, you will learn how to upload a CSV file to your GoodData workspace. You will work with a single sample CSV file. However, GoodData supports uploading multiple CSV files which you can use to build a logical data model (LDM) in the LDM modeler.

If you are on the Growth and Enterprise plans, see Load CSV Files to a Workspace with the LDM Modeler.


Prerequisites - Before You Load the Data

Ensure that you are logged into your GoodData account.

Your GoodData Workspace

Before you load any data to the GoodData platform, you must create at least one workspace (also known as a project). The method depends on your GoodData pricing plan. For details, see Create a Workspace (Project).

Your GoodData workspace is the place where you load your data, create metrics, share data visualizations and dashboards, create ad hoc analyses, and much more. Each workspace has its own project ID.

Note: In GoodData, terms Project and Workspace are interchangeable.

Upload a CSV File with LDM Modeler

You can easily upload CSV files to your workspace and build a logical data model from them.

For the following tutorial, download the order_lines.csv sample file. Ensure the downloaded file keeps its *.csv suffix.

Start this tutorial with a new or empty workspace.


  1. On the top navigation bar, click Load .
    A data load entry page opens.
  2. In the CSV tile, click Import.

    The Choose a CSV file dialogue opens in the LDM modeler.
  3. Browse for the downloaded CSV file, then click Import.

    GoodData starts processing the file.
  4. The Import dataset from filename.csv window enables you to determine the nature of the columns in your CSV file. For the purpose of this tutorial, click Import.
  5. LDM Modeler opens displaying the logical data model of your dataset.
  6. To finish, click Publish to save the logical data model and your data to your workspace.
  7. In the pop-up dialog window, keep the default options and click Publish.
  8. When the publishing process ends, close the confirmation window.
  9. Click Visit data load page, then click your name in the top right corner and click Analyze data to proceed to Analytical Designer:

Using CSVs to Create a Logical Data Model

To upload your own files, see Load CSV Files to a Workspace with the LDM Modeler and ensure that you read CSV File Requirements for CSV specifications.

For a comprehensive guide on working with CSV files in data modeling, see Create a Logical Data Model from CSV Files.

To learn more about data modeling in general, see Data Modeling in GoodData.

Create Your First GoodData Insights

Now that you loaded the sample data into your GoodData workspace, you will learn how to create simple insights using Analytical Designer available in the Analyze tab.

To go to Analytical Designer from your Data Integration Console, click your account name in the upper right corner, then click Analyze data.

The goal of this tutorial is to break down raw sales figures by order category and status, and examine the pricing structure of your sales.

As you can see, the columns of the original csv sample file appear in the catalog panel on the left. This is possible thanks to the GoodData’s ability to work directly with human readable data modeling metadata (facts, attributes, column names).

Exercise 1 - Order Category and Order Status

To create your first insight:

  1. Drag and drop Order ID onto the Measures panel. This automatically creates a Count of unique Order IDs.
    Analytical Designer applied Count because the Order ID column was annotated as an attribute instead of as a numerical fact.
  2. In the Compare helper, select Product Category from the drop-down menu and click Apply.
    The number of orders is now split by the product category.
  3. Drag and drop Order Status to the Stack By panel to look into the data in more detail..
    The columns are now further split by the status of the orders.
  4. Click the Save button in the top right corner of the screen to save the insight and name the insight it Orders by Status and Category.
    You have just created your first insight! 

Exercise 2 - Sales Pricing Structure

In the following example, your insights will analyze the pricing structure of your sales - the highest priced items and the price range.

Follow these steps:

  1. Click the Clear button in the toolbar to clear the insight.
  2. Drag and drop Price onto the Measures panel.
    This displays the Sum of all prices on all order lines but it does not consider how many times the products were sold at their price.
    Note: You can apply different mathematical functions to this particular column, because the Price column was annotated as a numerical fact.
  3. In the Measures panel, click the arrow to the left of Sum of Price item, and from the drop-down menu select Average to display the average product price.
  4. Drag Category to the View By panel.

You see that the Outdoor category contains the highest priced items. But what is the range of prices?

  1. In the Measures panel, click the arrow to the left of Avg of Price and change Average to Minimum.
  2. Drag and drop Price to the Measures panel again.
    A new Sum of Price item appears.
  3. Click the arrow to the left of Sum of Price, and from the drop-down menu, change Sum to Maximum. You can now see the range of prices for each category.

You can easily handle many analytical queries without needing to write SQL for individual variations.

Next Steps

Now that you created your first insights using our sample data, you can either:

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