Cloud Database

Big data are often defined in terms of the three Vs: the extreme volume of data, the variety of the data types, and the velocity at which the data must be processed. (data science) Big data is very valuable to some extent. If we utilize bid data in the right way, it is able to provide us with predictive pattern to help us make better decision and strategy. The key to success is getting the right data and finding the right attributes. (data science)

Because of these traits of big data, it is difficult for both individuals and organizations to keep and process their all data on in-house computer servers. Therefore, we need stronger data management system for us to store and process data–cloud database.

A cloud database is a collection of content, either structured or unstructured, that resides on a private, public or hybrid cloud computing infrastructure platform. The examples of cloud database are Amazon Relational Database, Microsoft Azure SQL Database etc. Actually, cloud computing is very commonplace in our ordinary lives. Most people use many cloud computing applications without realizing they are Gmail, google drive and even our Facebook and Instagram.

Cloud databases can be divided into two broad categories: relational and non-relational. A relational database, typically written in structured query language (SQL), is composed of a set of interrelated tables that are organized into rows and columns. Non-relational databases, sometimes called NoSQL, do not employ a table model. Instead, they store content, regardless of its structure, as a single document, which often used for social media.

For example, I once helped a company manage their CRM database. It is a kind of relational cloud database. I can access customer information via cloud-based CRM software from my computer or while traveling, and can quickly share that information with other authorized parties anywhere and anytime.

The video below shows how one of the cloud relational database–Amazon RDS works:

John D. Kelleher and Brendan Tierney, Data Science (Cambridge, Massachusetts: The MIT Press, 2018).

Michael Buckland, Information and Society (Cambridge, MA: MIT Press, 2017).