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Data quality for analytics using SAS /
| Call Number: | Libro Electrónico |
|---|---|
| Main Author: | |
| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
Cary, N.C. :
SAS Institute,
2012.
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| Subjects: | |
| Online Access: | Texto completo (Requiere registro previo con correo institucional) |
Table of Contents:
- Introductory case studies
- Definition and scope of data quality for analytics
- Data availability
- Data quantity
- Data completeness
- Data correctness
- Predictive modeling
- Analytics for data quality
- Process considerations for data quality
- Profiling and imputation of missing values
- Profiling and replacement of missing data in a time series
- Data quality control across related tables
- Data quality with analytics
- Data quality profiling and improvement with SAS analytic tools
- Introduction to simulation studies
- Simulating the consequences of poor data quality for predictive modeling
- Influence of data quality and data availability on model quality in predictive modeling
- Influence of data completeness on model quality in predictive modeling
- Influence of data correctness on model quality in predictive modeling
- Simulating the consequences of poor data quality in time series forecasting
- Consequences of data quantity and data completeness in time series forecasting
- Consequences of random disturbances in time series data
- Consequences of systematic disturbances in time series data.