At an enterprise level, every project schedules and runs multiple Azure Data Factory pipelines but tracking their outcomes in ADF studio is a cumbersome process.

Data security is hot topic given the data breach we hear about it every day.

Dynamic data masking is a feature that is available in Synapse analytics to restrict the exposure of sensitive data to the end users.

This article provides a step-by-step guide for getting started with Azure Synapse Link for Azure SQL Database.

The newly released feature ‘Synapse link for SQL’, enables near real-time analytics into Azure Synapse analytics over operational data from both Azure SQL and SQL Server 2022.

The log analytics will monitor the synapse pipelines and provide us more insights once if the job fails.

Introduction: Azure synapse analytics provides standard database templates for various industries to use and create DB model as per their company needs.

Introduction: In day to day operations we must have faced requirements to backup and restore or copy an Azure data factory from existing to new ones.

Introduction: One of the main objective of any business that is using cloud services is to optimize resources and lower the on-going costs.

Introduction: Parameterization is very useful when you want a reusable code that you can use forever and get the output by executing it only by changing the parameter for all your future requirements.

In this article we will look into how could we run both Python and SparkSQL queries in a single notebook workspace under the built-in Apache Spark Pools to transform the data in a single window.

We are going to see a real-time scenario on how to extract the file names from a source path and then use them for any subsequent activity based on its output.

Introduction: In this post we will discuss on how to create an external table and to store the data inside your specified azure storage parallelly using TSQL statements.

Introduction: In continuation to our previous article, we will look at how could we use parameterization into datasets and pipelines.

Today we will check how to create an external data source to access data stored in other resources.

In continuation to our previous article on Azure Synapse Analytics, we will deep dive into the sharding patterns(distributions) that are used in the Dedicated SQL Pool.

**This is a continuation of part one, I suggest you to check that first to get a clear understanding** Once the first condition is completed let’s check the second which I named as ValidRows as it is going to capture only the non-error values.

Azure Data Factory is a tool with tremendous capabilities when it comes to ETL operations.

Azure Synapse SQL is a technology which resides inside the Synapse workspace.