If there are technical issues on site, your data will be safe in the cloud. The data is also stored remotely and never stored on your computer, meaning it is not occupying space unnecessarily. So, you are just paying for the amount you need. It is also easy to up or downscale the amount of space in the cloud. This means you have one less thing to worry about.
#Create your own local cloud pro
The first pro of using a cloud is that the cloud provider handles all of the maintenance and upgrades. Accessible wherever there is internet access.You are already using several cloud-based tools including email providers (Gmail, Outlook, etc…), storage/backup Softwares (iCloud, Dropbox, Box, etc…) and all social media platforms that you might have an account in. A local (regular) server is one that you do buy and own physically, as well as have on site with you. You are renting the server space, rather than owning the server. This data, whether it is raw data or in your lab notebook, needs to be securely stored somewhere and two options are available: Cloud or local Servers.Ī cloud is a type of a server, which is remote (usually in Data Centers), meaning you access it via the internet. The constant digitization of the laboratory ecosystem translates into a tremendous increase in data generation at a digital level.
Cloud vs local servers – where should you store your data? In a time, where topics like data integrity, data quality, and data open access are becoming more and more popular, we write this article to assure that you can make the correct decision when it comes to storing your scientific data.Įveryone often talks about data integrity, management, and protection, but what about where to put the data itself? Well, here we can give you some insight into the pros and cons of using a cloud vs local server to store your scientific data.
Good data allows us to advance in our careers and bad data can quickly put an end to it. Cloud vs local Server – Where should you store your data?Īs scientists, data is the most precious tool that we have in our research.
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