What usually happens is that when we move SQL Server to a virtual machine, we become constrained by a maximum or limited amount of resources (CPU/ memory/ IO) that is significantly different to that of the physical machine.
Before uploading all our data to the cloud, we must be well aware of GDPR (General Data Protection Regulation), a European regulation aiming to protect individuals in regards to how their personal details are processed and the free movement of data.
Gradually, as storage gets faster and local SSD storage becomes more popular, etc. disk access times are significantly decreasing. In these regards, perhaps the best example are the SSDs Optane systems, notable for their much lower read/ write latencies than with traditional SSD’s, in addition to being directly connected through the PCIe bus:
In the last few years, we are increasingly finding more hybrid environments where some SQL Servers are being migrated to the Cloud. In these cases, other applications, services, ERPs or even SQL Server instances continue to be based OnPremise in the initial data center. This means that in the event of any connections between both environments, these will be restricted by bandwidth and higher latencies, as opposed to other connections that do not go across both environments.
One of the issues that many of our customers face when attempting to migrate OnPremise instances to the Cloud is the lack of a simple “shared storage”. Although there are some alternatives supported by third-party software or SDS solutions that allow us to configure a Failover Cluster instance in Azure, these are highly complex, therefore adding significant further costs to the solution’s TCO.
In many scenarios, we face the need to use integrated authentication in order to gain access to the required data sources to feed our analytical system. In view of Azure’s increasingly widespread use, as is the case with at least part of our infrastructure, some of these sources are hosted in Azure databases. In this case, we will discuss an actual error that we have come across when configuring and using integrated authentication in Azure databases with SSIS.
In this entry, we will show you how to create bookmarks and different scenarios where they may be useful. Bookmarks are basically used to store the status of a specific report page including the filter selection and the visibility of the different objects, allowing the user to return to that same status by simply selecting the saved bookmark.
In this blog post, we will show you some information regarding the new Power BI functionality known as Dataflow, that already exists in services such as Office 365. We must highlight that this new service is still in the Beta stages, so it is currently subject to modifications and updates.
I’m sure that the most “senior” readers will remember the possibilities available in old SQL Server versions to do backups using named pipes. And by older versions, I mean “really old”, since this functionality was marked as obsolete in SQL Server 7 and, although it remained in SQL 2000, it was completely removed from SQL Server 2005 and later versions.
Although SQL Server Integration Services, hereinafter SSIS, is capable of uploading Excel files, in most cases it can be time consuming because any small modifications to the Excel files can make the SSIS crash. For that reason, the best option is usually to transform those Excel files into .csv format, since uploading text files will cause you significantly less issues than the Excel files.