Data and Analytics Exercise

Overview

Here at ShootProof, we prefer to have a good idea of a candidate's technical experience and analysis skills before proceeding with portions of our recruiting process. We believe that the exercise below will illustrate a candidate's approach to working with technologies and methodologies that may be commonly used in our data and analytics engineering team here at ShootProof.

Guidelines

• This exercise should not take you more than two hours to complete. If your solution is taking longer, that's okay—be honest and let us know how long it took and why you think it took that long.
• Be as thorough as you wish.
• All exercises are to be performed as if you were on the job.
• You may submit your response in one of the following ways:
  • Package an archive (ZIP, tarball, etc.) of your files and deliver it to your contact.
    • If working with a recruiter, deliver it to them.
    • If working with ShootProof directly, deliver to careers+dae@shootproof.com.
  • Fork our repository and open a pull request.

There are no right or wrong answers. We are deliberately offering creative freedom and interpretation to all candidates who are completing this exercise. You would receive similar tasks on the job and would be given similar latitude with how you approach the problem and deliver business insights.

Exercise: Communicate business insights from raw data

First, let's talk about our domain models:

• Order: an order represents a set of prints, digital downloads, etc. placed by a customer's end client. An order always contains one or more order items.
• Order Item: an order item is a single item in an order. It has metadata such as a name, price, and quantity.

In this repository, you'll find a order-item-data.csv file. It contains a data set with one row per order item. You will find order_id and order_item_id values, along with additional values on the order and order items.

Your task

This is a data set that represents real world cases you would find at ShootProof. Using this data set, provide some business insights that you are able to glean from this data.

For example, you may consider activities such as:

• Loading the data into a relational database.
• Writing SQL queries against the relational database to extract information.
• Use a tool like Gnuplot, matplotlib, Pandas or similar to present interesting visualizations or relationships you observe in the data.

The business insights you provide are solely up to you; be as insightful and creative as you would like.

Please provide your insights in any of the following forms:

• Paragraph-form explaining your insights
• Data visualizations

Provide outline of steps you would use to ingest this data set

You may illustrate your approach to working with this data by including actual command-line output, shell commands, etc. Your data ingestion steps may be replayable by the reviewer, but this is not required.

Describe why you would approach the ingestion of this data in the manner you chose.