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
2,116 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
9,700 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
3,790 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
Let's build a real data dashboard. This guide will walk you through the entire...
Hello everyone! Just a quick note. I’ve removed all my slide decks from SlideShare....
Following on from my previous post about hitting the Kubernetes API from SQL Server...
Good morning everyone. I am starting to learn SQL. For this purpose I have...
Comments posted to this topic are about the item Connect Cloud Power BI to...
Good afternoon, I had a 7.8 TB database that needed some work. I removed...
You're tasked with planning capacity for a new SQL Server database workload. Which of the following is the most accurate way to determine how much CPU, memory, and I/O throughput your workload requires? What single or multiple tools would you use to answer the questions around resource needs?
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