In this article, we will be identifying the 4 most common ways of sharing big data files today and discussing the advantages and disadvantages that each method possesses. For each method of data sharing, the users will evaluate and choose one over the other due to its flexibility, scalability, and ease of use. We will also be introducing you to a method of data sharing that ensures data security and efficiency.
Why do we share big data files?
There are a few reasons to share big data files, as the users can keep these data in accessible locations until it is ready to be used for data analysis. As data analysis is being performed on the shared big data files, updates and modifications can be easily done without the need to re-register or publish the datasets. Its flexibility and scalability appeals to users that have the constant need of accessing datasets. In addition, big data sharing is more efficient because it allows researchers to share resources that encourage team collaboration and improve time spent on projects.
Method 1: Online data sharing platforms
Many users will share or store big data files on the web for either personal, business, or professional uses of online file sharing services. This data sharing method works well when the users upload or import media content, documents, spreadsheets with data points, or any other type of files to online platforms that allow others to download and access these files on the same platform. Many of these online data sharing platforms also allow the users to set the status of accessibility of data. For example, if the users share data through Google Drive, they can set the accessibility to read only, edit only, or both. This allows users to be flexible in the way that they share data with others.
Method 2: Removable storage media
Removable storage media is one of the original and traditional ways to share data files, which can be anything that can be removed from a device or a computer. Examples of removable storage media include memory sticks, memory cards, floppy disks, and removable USB hard drives. Once data files are transferred onto the removable storage media from their devices, it can be handed over to others physically to load the data files onto other devices for data sharing, storage, and collaboration.
Method 3: Peer to peer network
Another method that average daily users come across for data sharing is using peer to peer network data sharing. Examples of such data sharing methods can include instant messaging services or social media applications, like Slack or Facebook Messenger. Other than these, sending and sharing files as attachments in emails also falls under this type of file sharing. To share a file using peer-to-peer networks, you’ll need to have computer hardware and software to communicate without the need for a central server. Essentially, files are located on one’s computer and then shared with someone else, who can be on an entirely different server.
Method 4: Cloud Database management platforms
The last method that we wanted to mention is the use of cloud database management platforms to store and share data. An example of such a platform would be Acho. These platforms are built on cloud, so they can utilize cloud computing to process big data very fast. In addition to storing and sharing data, these platforms allow recipients to open and analyze the large data files. Although the previous three methods can send big data files to someone effectively, their recipients need to find other tools to open the file if the size of the file exceeds the limit that spreadsheet programs can support. However, cloud DB management platforms support viewing and analyzing large datasets, and allow multiple users to collaborate on the same data as well.
Comparing the 4 methods of data sharing
After introducing and comparing the 4 different methods of data sharing, although users will choose the method that is suitable for them based on their criteria and preferences, the option of using cloud database management platforms presents more advantages than disadvantages.
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