Difference between revisions of "Data Scaling"
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set so that it conforms with a set of requirements. | set so that it conforms with a set of requirements. | ||
− | Data Scaling will typically be required when the [[Measurement]] process generating the data sets is using a temporal, spatial or other scope boundary that is not aligned with the usage requirements (e.g., different time interval). The scaling adjustment, while a mathematically simple operation may imply [[Model Assumptions]] that may or may not be true. | + | Data Scaling will typically be required when the [[Measurement]] process generating the data sets is using a temporal, spatial or other scope boundary that is not aligned with the usage requirements (e.g., different time interval). |
+ | |||
+ | == Issues and Challenges == | ||
+ | The scaling adjustment, while a mathematically simple operation may imply [[Model Assumptions]] that may or may not be true. Data derived from scaling should ideally be cross-checked with historically available local data or data derived from other means of estimation such as extrapolation or interpolation based on historical local data, or modelling. | ||
== See Also == | == See Also == |
Latest revision as of 10:44, 5 January 2022
Definition
Data Scaling is a loose term that refers to data transformation activities that aim to improve the informational content of the data by adjusting an existing data set so that it conforms with a set of requirements.
Data Scaling will typically be required when the Measurement process generating the data sets is using a temporal, spatial or other scope boundary that is not aligned with the usage requirements (e.g., different time interval).
Issues and Challenges
The scaling adjustment, while a mathematically simple operation may imply Model Assumptions that may or may not be true. Data derived from scaling should ideally be cross-checked with historically available local data or data derived from other means of estimation such as extrapolation or interpolation based on historical local data, or modelling.