ETM3800 · Monash University
Text analytics for business
- Credit points
- 6
- Level
- 3
- Workload
- ≈ 12 h / week
- Faculty
- Business and Economics
What it covers
In the era of big data, the business world is deluged by huge amounts of data, of which more than 80% of the data is unstructured. In particular, unstructured text is one of the most common forms of unstructured data. Hence, knowing how to uncover business values from unstructured text is essential for a business analyst. This unit provides a solid foundation of text analytics for you to uncover insights hidden within unstructured textual data. You will learn the five essential components of text analytics: text parsing, concept derivation, topic derivation, text categorization, and sentiment analysis. Then, you will integrate text data with structured data to enhance predictive modelling procedures. You will be exposed to real-world business applications using a computer software.
Assessment
| Task | Type | Weight |
|---|---|---|
| 2 - Project | Project | 80% |
| 1 - Written | Written | 20% |
When and where
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Malaysia | On-campus |
| First semester | Malaysia | On-campus |