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Companies use databases to store data as it is being recorded. The method of storage tends to be optimized for storing it, as opposed to retrieving it.

Therefore, companies usually have a separate place to store data that's been partially processed, making it faster for retrieval for business reporting. In a practical sense, sometimes this is an OLAP Cube, or more recently circa 2010, it was in-memory data stores. Often, it's just plain old Excel.

The third stage is to do some final processing on the data, usually to arrive at a certain computation. This could either be a column of numbers, or a count of things. The numbers might be the difference from a previous reporting period, a percentage, the growth calculation, or even acceleration (which is growth of growth).

Sometimes the comparison is made between the same number from two different periods of time, but at other times, it's a ratio of two numbers that have different meaning e.g. currency divided by quantity.

Modern analytics struggles with a lack of tools. Big companies can afford to have expensive projects that take these three stages of processing. But mid to small size companies often end up in Excel.

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