Challenge Overview
Applause is a company focused on improving the quality of all our customers mobile apps. We have uniquely defined different attributes on which to measure our customers apps, and attempt to optimize said attribute metrics to increase quality. However, the holy grail of the app quality world lies in the tie between the quality of a customers app and the success of the app and/or business. If we have the ability to join our internal data sources (i.e. app store reviews, crash and device state information, bugs, etc) with trends and/or fluctuations in their business, we may be able to begin quantifying the impact of quality on their businesses.
In addition, the extra insight into Applause customer’s businesses can help with internal priorities for feature work on the Applause products.
For this work, a list of fake customer names are provided to see this work. These names should be used to explore the company namespaces across the multiple entry points below.
Flow should be as follows:
[Company File List] -> [Extraction Process pulls from appropriate entry points] -> [Transformation process aggregates information and maps appropriately to BigQuery schemas] -> Load Process pushes data to GCS] -> Import process loads into BigQuery]
Entry Points
A variety of entry points are requested for aggregating external information about customer companies: For this challenge the entry points will consist of Crunchbase, Glassdoor and Yahoo Finance. Each of these provide APIs to help acquire desired data.
Technologies:
Language: Python
Platform:
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BigQuery (Required)
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AWS, GAE are preferred platforms.