Create Data Visualizations Based On Azure Data Lake Storage Data in Mode

Mode is a collaborative data platform that combines SQL, R, Python, and visual analytics in one place. When paired with CData Connect Cloud, you get instant, cloud-to-cloud access to Azure Data Lake Storage data for use in data visualizations. This article shows how to connect to Azure Data Lake Storage in Connect Cloud, connect to Azure Data Lake Storage data in Mode, and create a simple visualization using that data.

CData Connect Cloud provides a pure cloud-to-cloud interface for Azure Data Lake Storage, allowing you to build data visualizations from live Azure Data Lake Storage data in Mode — without replicating the data to a natively supported database. In order to create visualizations, users write SQL queries to gather data. Using optimized data processing out of the box, CData Connect Cloud pushes all supported SQL operations (filters, JOINs, etc.) directly to Azure Data Lake Storage, leveraging server-side processing to quickly return the requested Azure Data Lake Storage data.

Configure Azure Data Lake Storage Connectivity for Mode

Connectivity to Azure Data Lake Storage from Mode is made possible through CData Connect Cloud. To work with Azure Data Lake Storage data from Mode, we start by creating and configuring a Azure Data Lake Storage connection.

1. Log into Connect Cloud, click Connections and click Add Connection
2. Select "Azure Data Lake Storage" from the Add Connection panel
3. Enter the necessary authentication properties to connect to Azure Data Lake Storage.

   Authenticating to a Gen 1 DataLakeStore Account

   Gen 1 uses OAuth 2.0 in Azure AD for authentication.

   For this, an Active Directory web application is required. You can create one as follows:

   1. Sign in to your Azure Account through the .
   2. Select "Azure Active Directory".
   3. Select "App registrations".
   4. Select "New application registration".
   5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
   6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
   7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

   To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen1.
   • Account: Set this to the name of the account.
   • OAuthClientId: Set this to the application Id of the app you created.
   • OAuthClientSecret: Set this to the key generated for the app you created.
   • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

   Authenticating to a Gen 2 DataLakeStore Account

   To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen2.
   • Account: Set this to the name of the account.
   • FileSystem: Set this to the file system which will be used for this account.
   • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
4. Click Create & Test
5. Navigate to the Permissions tab in the Add Azure Data Lake Storage Connection page and update the User-based permissions.

Add a Personal Access Token

If you are connecting from a service, application, platform, or framework that does not support OAuth authentication, you can create a Personal Access Token (PAT) to use for authentication. Best practices would dictate that you create a separate PAT for each service, to maintain granularity of access.

1. Click on your username at the top right of the Connect Cloud app and click User Profile.
2. On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
3. Give your PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured, you are ready to connect to Azure Data Lake Storage data from Mode.

Connect to Azure Data Lake Storage in Mode

The steps below outline connecting to CData Connect Cloud from Mode to create a new Azure Data Lake Storage data source.

1. Log-in to Mode
2. In the top-left corner of the screen, click the down-arrow next to your name and select Connect a Database...
3. On the next screen, select Microsoft SQL Server.
4. Enter the Microsoft SQL Server credentials:
   • Display Name: the name for the connection.
   • Host/Port: enter tds.cdata.com in the Host field and 14333 in the Port field.
   • Database name: enter the Connection Name of the CData Connect Cloud data source you want to connect to (for example, ADLS1).
   • Username: enter your CData Connect Cloud username. This is displayed in the top-right corner of the CData Connect Cloud interface. For example, test@cdata.com
   • Password: enter the PAT you generated on the Settings page
   Leave the rest of the connection settings at their default values unless you need to modify them.
5. At the bottom of the page, click Connect to ensure that you can connect to CData Connect Cloud.
6. Upon success, the following screen appears.

Your connection is now available for use in Mode. To connect to additional data sources from your CData Connect Cloud account, repeat the setup steps above, changing the value for Database for each data source.

Creating A Mode Visualization

To create a visualization in Mode, follow these steps:

1. On the current screen, click New Report. The SQL query text editor appears. Enter the following query: SELECT * FROM [ADLS].[Resources]; Click Run. The app now shows the query result:
2. Running the query activates the New Chart tab. Click this tab and select Pie Chart.
3. Now, drop a dimension in the Color section and a measure in the Angle section.

   We have now created a visualization of Azure Data Lake Storage data in Mode using CData Connect Cloud!

Get CData Connect Cloud

To get live data access to 100+ SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect Cloud today!