▮ Data
The growth of data volume has been exponentially fast, especially these past few years. The plot below by Statista shows that the data volume this year(2023) has nearly doubled compared to 2020.
However, despite the abundance of data volume, real-world data is often noisy and high-dimension. The more data volume there is the harder it is to transform data into analyzable data. This is why Topological Data Analysis (TDA) is becoming a growing field.
Topological Data Analysis (TDA) is a collection of approaches to study the shape of the raw data by extracting the underlying structure. It is expected to be more robust to noisy and high-dimension data because it is boiling down the data to its core structures.
▮ Workflow
The workflow for doing TDA is introduced in 2. The figure below illustrates the visual version of that workflow.
- Gather Data
- Generate underlying structure
- Characterize features of the structure
- Use the previously generated features for analysis
