Moving Beyond Spreadsheets
The course is part of this learning path
This course discusses some of the fundamental concepts of data management and looks at the differences between spreadsheets and databases for managing data. We'll look at some specific examples to understand when spreadsheets makes sense and when it makes sense to switch over to a database, which is sometimes a much better option for more complex datasets.
Specifically, this course aims to give students a practical hands-on introduction to database concepts. In addition, we'll gain an understanding of how to select the right database and we'll go through the basics of setting up an RDS instance on Amazon. This course includes a practical example of a company that is looking to choose a database, to give you an understanding of how databases work in the real world.
If you have any feedback relating to this course, please contact us at firstname.lastname@example.org.
- Understand the difference between spreadsheets and databases and when to use one or the other
- Learn about the different types of database available and the various features and characteristics to consider
- Learn how to choose the right database
- Learn how to deploy an Amazon Aurora instance
This course is designed for anyone who wants to improve their knowledge of databases and understand when it makes sense to use them as opposed to a spreadsheet.
To get the most out of this course, you should already have a basic understanding of simple data structures such as comma-separated values, as well as an understanding of cloud concepts in general.
Now it's important to know that there's not really a right or wrong answer to any of these questions. Your application is going to have specific requirements that could maybe even be up to interpretation. People are gonna need to set requirements and maybe they shift over time. Different databases are gonna have different strengths and weaknesses. And honestly, with the number of databases out there, you might find multiple databases fit your needs.
The important thing here is if you start to think that multiple databases fit your needs, maybe just consider which is the easiest to use or what you've used before. You don't always need to fully optimize your database selection. But if you answer the five questions posed by the graph previously, you're gonna get a pretty good answer.
Now to tie it back to our coffee bean delivery service, we have a moderate amount of information coming in in a predictable structure. Although it's from different sources, we can enforce structure to it. We have moderately complex reporting requirements where we need to display it to a couple of users simultaneously. And importantly, though, it needs to be easy to maintain and not drag our resources down. Furthermore, snapshot prevention data loss is acceptable, which really guides us towards something like Amazon Aurora.
Aurora is basically a MySQL and also as a Postgres interface, but importantly, MySQL compliant data structure base that can store this type of data with minimal administration effort.
Calculated Systems was founded by experts in Hadoop, Google Cloud and AWS. Calculated Systems enables code-free capture, mapping and transformation of data in the cloud based on Apache NiFi, an open source project originally developed within the NSA. Calculated Systems accelerates time to market for new innovations while maintaining data integrity. With cloud automation tools, deep industry expertise, and experience productionalizing workloads development cycles are cut down to a fraction of their normal time. The ability to quickly develop large scale data ingestion and processing decreases the risk companies face in long development cycles. Calculated Systems is one of the industry leaders in Big Data transformation and education of these complex technologies.