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Build Interactive Dashboards from FTP Data in Amazon QuickSight

Create a virtual MySQL database for FTP data in CData Cloud Hub and import FTP data into Amazon QuickSight SPICE to build interactive dashboards.

Amazon QuickSight allows users to build interactive dashboards in the cloud. When paired with the CData Cloud Hub, you get cloud-to-cloud access to FTP data for visualizations, dashboards, and more. This article shows how to create a virtual database for FTP in Cloud Hub and build dashboards in Amazon QuickSight with access to FTP data.

The CData Cloud Hub provides a pure MySQL, cloud-to-cloud interface for FTP, allowing you to easily build visualizations from FTP data in Amazon QuickSight. By importing your FTP data into the Amazon QuickSight "Super-fast, Parallel, In-memory Calculation Engine" (SPICE), you can leverage the powerful data processing features of the Amazon ecosystem to build responsive dashboards. And with the ability to schedule refreshes of the data stored in SPICE, you control how up-to-date your dashboards are.

Create a Virtual MySQL Database for FTP Data

CData Cloud Hub uses a straightforward, point-and-click interface to connect to data sources and generate APIs.

  1. Login to Cloud Hub and click Databases.
  2. Select "FTP" from Available Data Sources.
  3. Enter the necessary authentication properties to connect to FTP.

    To connect to FTP or SFTP servers, specify at least RemoteHost and FileProtocol. Specify the port with RemotePort.

    Set User and Password to perform Basic authentication. Set SSHAuthMode to use SSH authentication. See the Getting Started section of the data provider help documentation for more information on authenticating via SSH.

    Set SSLMode and SSLServerCert to secure connections with SSL.

    The data provider lists the tables based on the available folders in your FTP server. Set the following connection properties to control the relational view of the file system:

    • RemotePath: Set this to the current working directory.
    • TableDepth: Set this to control the depth of folders to list as views.
    • FileRetrievalDepth: Set this to retrieve and list files recursively from the root table.

    Stored Procedures are available to download files, upload files, and send protocol commands. See the Data Model chapter of the FTP data provider documentation for more information.

  4. Click Test Database.
  5. Click Privileges -> Add and add the new user (or an existing user) with the appropriate permissions.

With the virtual database created, you are ready to build visualizations in Amazon QuickSight.

Import FTP Data into SPICE and Create Interactive Dashboards

The steps below outline creating a new data set based on the virtual FTP database in Cloud Hub, importing the dataset into SPICE, and building a simple visualization from the data.

  1. Log into Amazon QuickSight and click "Manage data."
  2. Click "New data set," select MySQL as the data source, configure the connection to your Cloud Hub instance, and click "Create data source."
  3. Select a table to visualize (or submit a custom SQL query for your data).
  4. Click "Edit/Preview data" to customize the data set.
  5. Select "Import to SPICE for quicker analytics" and click "Visualize."
  6. Select fields to visualize and a visual type.

Schedule Refreshes for SPICE Data Sets

QuickSight users can schedule refreshes for data sets that are imported into SPICE, ensuring that data being analyzed is only as old as the most recent refresh.

  1. Navigate to the QuickSight home page.
  2. Click "Manage data."
  3. Select the data set you wish to refresh.
  4. Click "Schedule refresh."
  5. Click Create, configure the refresh settings (time zone, repeat frequency, and starting datetime), and click Create.

SQL Access to FTP Data from Cloud Applications

At this point, you have a direct, cloud-to-cloud connection to FTP data from your Amazon QuickSight dashboard. You can create new visualizations, build interactive dashboards, and more. For more information on gaining SQL access to data from more than 100 SaaS, Big Data, and NoSQL sources from cloud applications like Amazon QuickSight, refer to our Cloud Hub page.