Migrating to the cloud has many advantages … until you’re the one tasked with making it happen. For many data professionals, this will be a first step from the traditional, predictable challenges of managing on-premises servers to the many and varied databases and platforms in the cloud.
2023-08-25
This article covers tips on establishing, enhancing, and empowering collaboration, communication, and governance on Cloud Transformation projects.
2022-10-05
Learn about high availability in the cloud at a conceptual level.
2022-03-28
2,394 reads
Introduction I recently passed the Google Cloud Professional Data Engineer certification exam, Professional Data Engineer Certification. It took me about five month to prepare for this, and I would like to share my thoughts of why I decided to take it on and how I prepared for it. At the moment, Google cloud (GCP) is […]
2021-03-15
9,765 reads
No matter what you need, Azure probably has a solution. In this article Diogo Souza demonstrates how to host a static web page in Azure in just a few steps with Azure Blob Storage and Azure CDN.
2020-11-03
Moving resources from one location to another in Azure has been possible but not easy to do. In this article, Dennes Torres introduces an exiting new Azure feature: Azure Resource Mover.
2020-10-26
Learn how you can create a SQL Server instance in the Google Cloud Platform.
2019-09-26
3,918 reads
Your databases are hosted in the cloud – either in VMs or in a database-as-a-service – and you’re having a performance emergency that’s lasted for more than a day. Queries are slow, customers are getting frustrated, and you’re just not able to get a fix in quickly. Just ask management if they want to throw hardware at it.
2019-05-10
While architecting cloud native applications, you need to ensure that your system is highly available, performant, scalable, fault tolerant, and has the capability to recover from a disaster scenario. In this article, Samir Behara discusses the options available when designing the database architecture to achieve scalability.
2019-05-03
Data analytics has become one of the powerful domains in the world of data science. An enormous amount of data is being generated by each organization in every sector. Computer science has found solutions to store and process this data in a smart way through a distributed file system. One such example is Azure Data Lake. It uses the Hadoop Distributed File System, and to perform analytics on this data, Azure Data Lake storage is integrated with Azure Data Analytics Service and HDInsight. In this article, Suhas Pande will explain how to store data using Azure Data Lake and how to perform data analysis on it using U-SQL, a big data SQL and C# language.
2019-04-29
By Steve Jones
I’m not sure I knew identity column values could not be updated. I ran...
By Steve Jones
We had an interesting discussion about deployments in databases and how you go forward...
By ChrisJenkins
You could be tolerating limited reporting because there isn’t an off the shelf solution...
I have mentioned this several times over several years. Can someone please help me...
SELECT COUNT(DISTINCT Component) AS Found FROM tblComponents WHERE(Component NOT LIKE '%[a-z]%') AND(LTRIM(RTRIM(Component)) = 'GM13622')...
Comments posted to this topic are about the item Remotely Engineer Fabric Lakehouse objects:...
In a SQL Server 2025 table, called Beer, I have this data:
BeerIDBeerName 1Becks 2Fat Tire 3Mac n Jacks 4Alaskan Amber 8KirinI run this code:
SELECT JSON_OBJECTAGG(
BeerID: BeerName )
FROM beer;
What are the results? See possible answers