The DatabaseMail feature in SQL Server and Managed Instance is widely used by many professionals. But what if you want similar functionality in Azure SQL Database? There are options, but it requires a bit of tinkering. Tinkering that we gladly explain in this blog.
The data landscape has changed dramatically over recent years, the world of data is evolving. In the past, we mainly heard that we needed to do as much as possible “cloud-only”—but this trend has become more nuanced now.
Azure Data Factory (ADF) is a cloud-based Extract-Transform-Load (ETL) and data integration service. It allows you to create data-driven workflows for orchestrating data movement and transforming data at scale.
Since its announcement as a first-party service on Microsoft Azure at the end of 2017, Databricks has seen a remarkable growth in usage. However, the service and its success were around long before Microsoft came into play. Going by the fact that you are reading this blog at this very moment, I’ll assume that you have used Databricks before, or at least have heard that Databricks is in the data business. And cousin, business is a-boomin’! One aspect that may have left users of the service frazzled, is the steady stream of updates it receives.
The first thing that comes to mind when you think of Infrastructure-as-Code (IaC) in Azure is Azure Resource Manager (ARM) templates. After all, for every service – regardless of how you deploy it – an ARM template is created in the background. However, when you think of ARM, you probably also think of JSON files that are difficult to maintain and read. At least that’s what I think. Microsoft had the same thought as I did. So they launched Project Bicep, a domain specific language (DLS) or mini language. This means that Bicep is designed specifically for declarative development of Azure resources.
Bam, exactly what I was looking for! In this blog post, I will show how you can create a container which reads a text file from an Azure file share on storage account A, and writes the content to an Azure blob on storage account B.
Microsoft has recently taken us on a word lingo with the launch of Azure Synapse Analytics. At Kohera, we’ve experienced some confusion in the market between Azure Synapse as a standalone product and Azure Synapse Analytics as a SaaS platform.
A client asked if we could provide a simple form of monitoring on a part of a provided solution. The data platform we developed for them ingested a source that was afterwards used by a business team and our client’s clients.
Sometimes, Databricks can be a bit sluggish. Especially when working with many small parquet files on Azure Data Lake. This sluggishness is often due to the security and read/write access requests that the Databricks cluster needs to maintain.
For a client project I was recently asked how to efficiently handle translations in SQL Server. As, in this particular case, the client application was very proficient in processing XML data I chose in cooperation with the development team to use XML as the datatype to handle this specific case.