What is data sparsity and how to handle it ? How to avoid dollar tables creation in a loading in ODI

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Data sparsity refers to the situation where a large portion of data is missing or empty. To handle it, techniques like data imputation or interpolation can be used. Dollar tables can be avoided in ODI loading by using appropriate mappings and transformations.

Data sparsity occurs when there are missing or empty values in a dataset.
To handle data sparsity, techniques like data imputation or interpolation can be used to fill in the missing values.
Data imputation involves estimating missing values based on available data, while interpolation involves estimating values between existing data points.
In ODI loading, dollar tables can be avoided by using appropriate mappings and transformations.
Instead of creating separate tables for each currency, a single table can be used with a currency column to store the currency information.

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What is data sparsity and how to handle it ? How to avoid dollar tables creation in a loading in ODI

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