Data Quality for Analytics Using SAS

Chapter 4: Data Quantity

4.1 Introduction

Quantity versus quality

Overview

4.2 Too Little or Too Much Data

Having not enough data

Having too much data

Having too many observations

Having too many variables

4.3 Dimension of Analytical Data

General

Number of observations

Number of events

Distribution of categorical values (rare classes)

The number of variables

Length of the time history

Level of detail in forecast hierarchies

Panel data sets and repeated measurement data sets

4.4 Sample Size Planning

Application of sample size planning

Sample size calculation for data mining?

4.5 Effect of Missing Values on Data Quantity

General

Problem description

Calculation

Summary

4.6 Conclusion

4.1 Introduction

Quantity versus quality

It seems to be cumbersome ...