How to manage your data sources

Data sources are the foundation of topics. You will need to connect at least one data source to start creating your topics. All the information you need for training the advisor comes from them. Therefore, it is important to manage your data sources correctly, by knowing what to do when you want to add or remove one and when you want to edit something.

Here's all the information you need on data source management.

Data source types

crystal supports these data sources now:

  • MySQL (Versions supported: 5.8+)

  • PostgreSQL (Versions supported: from 7.4 to 12)

  • Microsoft SQL Server (Versions supported: ODBC Driver 11 for SQL Server)

  • Azure SQL

  • Oracle (Versions supported: 12+)

  • IBM DB2

  • Amazon Redshift

  • SAP Hana

  • Web Connector (read more below)

  • Azure Synapse

  • MongoDB

  • Google Sheets

  • Google BigQuery

  • Snowflake

The following data sources are coming soon:

  • Salesforce

  • Hive

  • SQL SSAS

  • Teradata

  • Microsoft Dynamics CRM

Remember to always keep track of crystal updates here by checking out the Release notes section.

Web Connector

Can't see your data source? You can always build your own adapter and connect other data sources with the Web Connector. Read more about the Web Connector.

Add a new data source

To add a data source, from the Self-Service Console click on the Data sources management button in the upper-right corner of the page.

If you don’t have any connected data sources, you will be invited to add your first data source to your project.

Otherwise, you will see the list of data sources already connected to your project.

Click on Connect if it’s your first time or Add new data source if you already have some data sources and start the process to connect a new data source. The first thing you have to do is select the technology you are going to use.

Remember that you might need someone from the IT department to help you connect a data source, because after selecting the the data source type you will need to provide specific information, which are the standard parameters of the data source (Host, Url, port and so on).

Note that you need to assign a name to the data source in order to continue and that there cannot be more data sources with the same name.

Once you have filled out the information requested, click on Test and connect.

If all the parameters are correct and if there are no connection problems, your data source is now ready to be used for generating topics. If some information provided was not accurate, you will receive an error message and you will have to revise the fields. If you decide to use the Web Connector instead, you will have to indicate different parameters.

Edit data source details

You may want to change your data source name or the password you chose, or even to change the place where it’s hosted. In order to change your data source details, select the data source you want to edit. All fields can be updated, but the update will succeed only if the connection test will have a positive outcome.

Click on Edit and you will be enabled to edit the details of your data source.

If you want to change the data source name, you can do it anytime by clicking on the pencil icon next to the name. When you're done with the change, click on Save: that's it!

Once you have finished editing your data source details, click on Test and connect to confirm the changes.

If these changes have an impact on topics already published, you will be provided with a list of all the topics that will be deleted and you will be asked to confirm your decision.

If you confirm, the topics will be deleted and the editing will be complete.

Oauth authentication (Google BigQuery)

You can connect your BigQuery data source by simply signing-in with your Google account.

To do that, select BigQuery in the Add new data source menu:

A new window will prompt with two options: Manual Authentication or Oauth Authentication. Select the second one, then click on Next:

Sign-up with your Google account to connect your BigQuery data source.

You'll be able to enter your Project ID and Data source name. Therefore, click on Test and connect to proceed:

Remove a data source

To remove a data source, select it and open the details.

Now click on Delete. Since the cancellation of a data source will lead to the elimination of all the topics that are using it, you will be asked to confirm your decision. You will see the list of the affected topics that will be deleted.

If you confirm, the data source will be removed along with all the connected topics.

Was this article useful for you? Check out other interesting materials in the Tutorials for admins section of our Resources!

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