Data, Big and Small
ZZEN9313 20H4
Author: Hayden Smith
As we move to more structured data, it becomes easier to manipulate and work with, but often comes with a larger overhead of maintenance.
For example, JSON creates a structured standard of data storage that allows it to be used somewhat universally, however, this comes at the expense of it being very restrictive in data types being able to be used.
Unstructured
Semi-Structured
Structured
ZZEN9313 20H4
Author: Hayden Smith
Understanding data volume helps you understand the relative size of stored data.
Data can either be:
From these we can have kilo, mega, giga, tera, peta, or even more bits or bytes.
Example: Be careful when internet companies say 10mb connections! That's only (10/8)mB!
ZZEN9313 20H4
Author: Hayden Smith
ZZEN9313 20H4
Author: Hayden Smith
It's important we get on the same page around terminology to use with different types of data. There are 3 common dimensions of data that we can look at:
Ed has some good detail around databases. In this course we explore a couple of key types of databases:
We use relational databases for highly structured data. Operational relational databases tend to be even more structured (reducing redundant data), whereas data warehouses that use relational databases tend to be more "flat" and used for offline analytics
ZZEN9313 20H4
Author: Hayden Smith
No further reading is required beyond the watching of the documentary to answer the question. If you want to include further material, you are welcome to and will not be penalised, but you are not required to.
ZZEN9313 20H4
Author: Hayden Smith