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Data Engineering Template:

Understand Data Better by Creating Combination Pairs from Correlation Analysis

Stock portfolio analysis Flow The flow view of this template

Transformations:
correl, deduplicate, join, pivot, $filepath

This template flow shows how you can create combination pairs for correlation analysis from example stock performance data (that you can obtain by using one of the Yahoo Finance APIs). It makes use of Trifacta’s cross join capabilities as well as the correl transform.

The flow reads from a set of files in a specific folder that are parameterized. Each file represents performance data for a particular stock, the ticker of the stock is accessed via the $filepath variable. It then creates combination pairs of stocks for correlation analysis by cross joining against itself as well as date of the performance data. Finally to get to the correlation, it makes use of the correl transform function. You can use the techniques in this example flow for many other similar use cases.

For more information, please see transformation function documentation for correl.

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