Dimensional Data Operation - (Pivot|Transpose|Cross-tab|Matrix)

About

The pivot is an dimensional data operation where rows and columns are interchanged.

Pivot is also known as:

• Transpose in the linear algebra word
• Matrix in the Microsoft world
• Cross-tab

This operation is typically performed by the visualization tool.

Statistics

Cross tabulation (or crosstabs for short) is a statistical process that summarises categorical data to create a contingency table. Some entries may be weighted, unweighted tables are commonly known as pivot tables.

Analytics Client

SQL

``````select cust_id,
max(decode(day,trunc(sysdate-0)),sales)) day1,
max(decode(day,trunc(sysdate-1)),sales)) day2,
.....
max(decode(day,trunc(sysdate-6)),sales)) day7
from fact,dim
where <join>
and day >= sysdate minus whatever....
group by cust_id;```
```

Excel

Copy > Paste Special > Transpose

Disadvantage as a storage structure

Disadvantage of this structure as a storage structure, if a pivot is used to represent different possible values of a column.

If you want:

• to add a category, you need to add a category column for each column
• to do an update on one of this fields, you end up with a list of “IF THEN ELSE”.
• to do an aggregation on one of this fields, you end up with a list of “UNION”.
• to add an audit function on it, you need to add an audit on each column
• to set a value that is dependent of others dimensions, you end up adding a lot of column.
• If you have 1 metrics column with 2 dimensions, you add 2 columns
• If you have 2 metrics column with 2 dimensions, you add 4 columns

Furthermore, it's not a third normal form. Then if the data is sparse, you cannot save it in a parse form and you end ups using a lot of storage for nothing and can degrade seriously then the performance.

Documentation / Reference

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