It is a capital mistake to theorize before one has data.
Sherlock Holmes in “A study in Scarlet”
Welcome to Introduction to Big Data
Data is being continuously generated as the global population, currently at 8 billion, continues to grow.
Big data refers to extremely large sets of structured and unstructured data that are too complex to be processed using traditional data processing methods. The term "big" in big data is not just about the size of the data, but also the velocity, variety, and veracity of the data.
- Velocity refers to the speed at which data is generated, collected, and processed.
- Variety refers to the different types of data that are available, including structured data (e.g. data in tables or databases) and unstructured data (e.g. text, images, video).
- Veracity refers to the accuracy and reliability of the data.
How would you utilise big data technologies and tools to help organizations?
In this course you will learn how to collect, store, process, analyze, and visualize large and complex data sets.
You will need to set aside a regular learning time and go through the following learning activities:
- reading, watching, and completing the activities on the learning platform,
- completing assessments,
- and self-directed theory (researching areas of interest or where you need more support).
The two modules you will be undertaking as a part of this course are:
| 1. Test Big Data Samples | This topic will cover the basics of testing and provide an overview of how to validate and optimize data samples. |
| 2. Analyse Big Data | This topic will cover the basics of data analysis, including scoping and determining the purpose, as well as analyzing trends and relationships. |