Answer:
It seems like you're asking about "data states," but the term could refer to various concepts depending on the context. Here are a few interpretations:
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Data States in Computing: This could refer to the different states that data can be in during processing, such as:
- Raw Data: Unprocessed data collected from various sources.
- Processed Data: Data that has been cleaned and transformed for analysis.
- Stored Data: Data that is saved in databases or data warehouses.
- Transmitted Data: Data that is being sent over a network.
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Data States in Statistics: This might refer to the different conditions or categories of data in a statistical analysis, such as:
- Nominal Data: Categorical data without a specific order.
- Ordinal Data: Categorical data with a defined order.
- Interval Data: Numeric data with meaningful intervals but no true zero.
- Ratio Data: Numeric data with meaningful intervals and a true zero.
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Data States in Data Governance: This could refer to the various stages of data management, including:
- Data Creation: The initial generation of data.
- Data Storage: Where and how data is stored.
- Data Usage: How data is accessed and utilized.
- Data Archiving: Long-term storage of data that is not actively used.
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Data States in Machine Learning: This could refer to the different phases of data in a machine learning pipeline, such as:
- Training Data: Data used to train a model.
- Validation Data: Data used to tune model parameters.
- Test Data: Data used to evaluate the model's performance.
If you have a specific context or area in mind regarding "data states," please provide more details, and I can give you a more tailored response!