Dealing with “SQL Bulk Copy failed due to received an invalid column length from the bcp client” Errors in Azure Data Factory

When you are amid a pesky IT issue, it can be difficult determining whether the problem is down to a bug/system fault or human error. Like this recent example involving Azure Data Factory illustrates, it is generally best to assume the latter, to avoid any prolonged difficulty.

Resolving AADSTS50126: Invalid username or password Errors During Azure SQL Database Deployment Task (Azure DevOps Pipelines)

We saw a few weeks ago how to utilise Azure Active Directory (AAD) Security Groups to manage Azure SQL database access at scale. When using this feature, you must ensure database changes are deployed out using an AAD administrator account or similar, a task which may be difficult to achieve in an Azure DevOps Pipeline.

Sink Limitations with the Dynamics 365 Customer Engagement/Common Data Service Connector for Azure Data Factory

The Dynamics 365 Customer Engagement/Common Data Service connector for Azure Data Factory can, in most cases, fit into your data integration needs. However, it is worth highlighting the two field types which are, specifically, not supported; namely, the Customer and Owner field types.

Working with Custom Dynamics 365 Customer Engagement Dataset Schemas in Azure Data Factory V2

By default, the Dynamics 365 Customer Engagement connector for Azure Data Factory V2 exposes a predefined list of fields, that must have data mapped to them for any Copy Data task to complete successfully. This behaviour can be impractical depending on your particular scenario; fortunately, there is a way in which you can override this.

Dynamics 365 Customer Engagement Connector Confusion with Azure Data Factory

Azure Data Factory V2 not just has 1, but three separate connectors that all claim to hook up to Dynamics 365 Customer Engagement/Dynamics CRM! So which connector is the "right" one to use and what differences do they have? With a little help from Alan Partridge, we can clear up any confusion...

Working with Variables in an Azure DevOps Release Pipeline

Working with variables within your Azure DevOps Pipeline can give you a high degree of latitude when planning your software deployments. When utilised as release variables, additional functionality is exposed, allowing you to alter the conditional flow within your pipeline dramatically. In this week's post, we'll find out how to use them in practice.