Develop/Managing Data Bases

3 Credits · Level: Undergraduate

A database is nothing more than a set of related information. A telephone book, for example, is a database of the names, phone numbers, and addresses of all people living in a particular region. With the explosion of data, computing power, and cloud data warehouses, SQL has become an even more indispensable tool for the savvy analyst or data scientists. This class reveals new and hidden ways to improve your SQL skills, solve problems, and make the most of SQL as part of your workflow. There are variant relational and non-relational databases. In this class, we will cover MySQL (relational database) and MongoDB (non-relational database). The dynamic nature of MongoDB lends itself quite naturally to working with a dynamic language such as Python. The tradeoffs between a dynamically typed language such as Python and a statically typed language such as Java in many respects mirror the tradeoffs between the flexible, document-oriented model of MongoDB and the up-front and statically typed schema definition of SQL databases. Python allows you to express MongoDB documents and queries natively, through the use of existing language features like nested dictionaries and lists. For these reasons, MongoDB and Python make a powerful combination for rapid, iterative development of horizontally scalable backend applications. For the vast majority of modern web and mobile applications, MongoDB is likely a better fit than RDBMS technology. The focus of this course is more on the NoSQL category.