Build AI/ML Models with Live YouTube Analytics Data using Dataiku

Dataiku is a data science and machine learning platform used for data preparation, analysis, visualization, and AI/ML model deployment, enabling collaborative and efficient data-driven decision-making. When paired with the CData JDBC Driver for YouTube Analytics, Dataiku enhances data integration, preparation, real-time analysis, and reliable model deployment for YouTube Analytics data.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live YouTube Analytics data. When you issue complex SQL queries to YouTube Analytics, the driver pushes supported SQL operations, like filters and aggregations, directly to YouTube Analytics and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze YouTube Analytics data using native data types.

This article shows how you can easily integrate to YouTube Analytics using CData JDBC Driver for YouTube Analytics in Dataiku DSS (Data Science Studio) platform, allowing you to prepare the data and build custom AI/ML models.

Preparing the Dataiku DSS environment

In this section, we will explore how to set up Dataiku, as previously introduced, with YouTube Analytics data. Be sure to install Dataiku DSS (On-Prem version) for your preferred operating system, beforehand.

Install the CData JDBC Driver for YouTube Analytics

First, install the CData JDBC Driver for YouTube Analytics on the same machine as Dataiku. The JDBC Driver will be installed in the following path:

Connecting the JDBC Driver in Dataiku DSS

To use the CData JDBC driver in Dataiku, you must create a new SQL database connection and add the JDBC Driver JAR file in the DSS connection settings.

1. Log into Dataiku DSS platform. It should open locally in your browser (e.g. localhost:11200)
2. Click on Navigate to other sections of Dataiku menu on the top right section of the platform and select Administration.
3. Select the Connections tab.
4. In Connections, click on New Connections button.
5. Now, scroll down and select Other SQL databases.

6. Generate a JDBC URL for connecting to YouTube Analytics, beginning with jdbc:youtubeanalytics: followed by a series of semicolon-separated connection string properties.

   YouTube Analytics uses the OAuth authentication standard. You can use the embedded CData OAuth credentials or you can register an application with Google to obtain your own.

   In addition to the OAuth values, to access YouTube Analytics data set ChannelId to the Id of a YouTube channel. You can obtain the channel Id in the advanced account settings for your channel. If not specified, the channel of the currently authenticated user will be used.

   If you want to generate content owner reports, specify the ContentOwnerId property. This is the Id of the copyright holder for content in YouTube's rights management system. The content owner is the person or organization that claims videos and sets their monetization policy.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the YouTube Analytics JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.youtubeanalytics.jar

   Fill in the connection properties and copy the connection string to the clipboard.

   A typical JDBC URL is given below:

   jdbc:youtubeanalytics:ContentOwnerId=MyContentOwnerId;ChannelId=MyChannelId;InitiateOAuth=GETANDREFRESH
7. On the New SQL database (JDBC) connection screen, enter a name in the New connection name field and specify the basic parameters:
   • JDBC Driver Class: cdata.jdbc.youtubeanalytics.YouTubeAnalyticsDriver
   • JDBC URL: JDBC connection URL obtained in the previous step
   • Driver jars directory: the folder path where the JAR file is installed on your system

   Next, select the SQL dialect of your choice. Here, we have selected 'SQL Server' as the preferred dialect. Click on Create. If the connection is successful, a prompt will display, saying 'Connection OK'.

8. The Data Catalog window will appear. Select the desired connection, catalog, and schema from the Connection to browse, Restrict to catalog, and Restrict to schema dropdowns, then click on List Tables. The Dataiku platform will list all the required tables.
9. Select any table from the list and click Preview to view the table data. Click Close to exit the window.

Creating a new project

To prepare data flows, create dashboards, analyze the YouTube Analytics data, and build AI and ML models in the Dataiku DSS platform, you need to first create a new project.

1. Select Projects from the Navigate to other sections of Dataiku menu.
2. In the Projects screen, click New Project and select + Blank Project.
3. In the New Project window, assign a Name and Project Key. Click Create. The new project dashboard opens up.
4. Select Notebooks from the menu at the top of the project screen.
5. Click on + Create Your First Notebook dropdown menu and select Write your own option.
6. In the New Notebook window, select SQL.
7. Now, select the required connection from the Connection dropdown and enter a name in the Notebook Name field.

Testing the connection

To test the YouTube Analytics connection and analyze the YouTube Analytics data, write a query in the query compiler and click Run. The queried/filtered YouTube Analytics data results will then appear on the screen.

Get Started Today

Download a free, 30-day trial of the CData JDBC Driver for YouTube Analytics to integrate with Dataiku, and effortlessly build custom AI/ML models from YouTube Analytics data.

Reach out to our Support Team if you have any questions.