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
2,258 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
9,717 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
3,898 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 Chris Yates
For decades, enterprises have approached data management with the same mindset as someone stuffing...
Truncate Table Pitfalls Truncating a table can be gloriously fast—and spectacularly dangerous when used carelessly....
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Hi, our peer who owns a remote mysql server from which we extract warehouse...
Dear Folks, Restore jobs in my SQL2022 Standard edition replication were failing on a...
hi, just to get this part out of the way, if my intended target...
The new vector datatype in SQL Server 2025 requires a number dimension parameter. What is the maximum number of dimensions supported?
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