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

### Table of Contents

## 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.

## Articles Related

## 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

### Microsoft Report (SSRS)

## 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.