Fetching Historical Data in Azure Data Factory
Triggers are like job schedulers for the execution of pipeline runs in the Azure Data Factory. Presently there are three types of triggers that are supported in ADF. Schedule trigger: A trigger that executes a pipeline on an absolute schedule Tumbling window trigger:...
User-Defined Schema in Databricks
If you’ve been working with CSV files in Databricks, you must be familiar with a very useful option called inferSchema while loading CSV files. It is the default option that is widely used by developers to identify the columns, data types, and nullability,...
Dynamic Data Masking
This post is the continuation of Azure SQL security recommendations. In the earlier posts, we visited the concept of Row-level security for limiting user access to related data. Today, we will look at how to mask sensitive data using Dynamic Data Masking feature....
Row Level Security – Azure SQL Server Security Recommendations (Part 2)
This post is the continuation of the Azure SQL Server security recommendations series. In my previous blog, we went through the filter predicate. In this blog, we will cover block predicate and highlight some of the best practices recommended by Microsoft. ...
Parameterize Connections in Azure Data Factory
Azure Data Factory is a managed cloud service that is built for complex data orchestration processes and hybrid extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects. In this blog, we will demonstrate how to parameterize connection...Related Blogs
