Create and manage data sets, Interaction History summaries, and other resources. Make sure that you identify the data that correlates to your business use case and that is aligned with the use problem that you want to solve.
- Creating data sets
You can create a data set for storing data that is important for the business use case that you want to solve. To accommodate various use cases, you can create multiple types of data sets, for example, a Monte Carlo data set that simulates customer records, a social media data set for extracting Facebook posts and so on.
- Creating summaries
You can create an Interaction History summary data set that is based on your input criteria. For example, you can create a summary of all Interaction History records for a customer that shows all accepted offers within the last 30 days. You can use Interaction History summaries to filter out irrelevant offers (for example, do not display this advertisement to a specific customer if that customer has already viewed it within this month).
- Accessing text analytics resources
View and manage the resources that you created or uploaded in the process of building a machine learning model for text analytics, such as taxonomies for topic detection and sentiment lexicons for sentiment analysis and intent detection.