Pipelines Features

This is where IVP.ai enables data transformations to clean datasets and prepare them for analysis. Typically, data transformation is the most complex step in any data analysis process, so depending on your use case, saving a pipeline may be a good idea if you are wanting to run the same type of analysis again and again.

Pipelines features a drag & drop interface where we can transform an original dataset through any of the following actions (these will be explored in more detail on the Pipelines help centre tab): 

• Join
• Append
• Aggregate
• Calculate
• Filter
• Tag
• Remove columns
• Rename columns
• Date time extraction
• Convert 0 to null
• Convert null to 0
• Pivot

Pipelines also offer the option to harness industry-leading AI models. IVP currently offers four types of AI model including:

• Forecasting (predicting future values)
• Grouping (clustering variables with other similar variables)
• Missing values (predicting values by learning from training data with known values)
• Reduce complexity (a form of dimensionality reduction, to reduce noise from your dataset to account for outliers)