Logistics LLC Consulting Project (Jan 22 - Apr 22)

Overview:

Engineered a hybrid cloud data solution utilizing Python and GCP including BigQuery, Cloud Storage, Batch Load, and Data Studio (now Looker).

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Problem 1:

The customer had sales associates manually sifting through web pages to find contact information of freight carriers to meet their specific customer needs in an ad-hoc manner.

Solution 1:

Developed Python (Selenium) web scraping code that was cleaned (Pandas, Regex) and uploaded into Google Cloud Storage and queried using BigQuery for Looker interactive dashboards.

Problem 2:

The customer wanted to utilize data for sales to both monitor KPIs internally and reach their key accounts with an end-of-year data-driven Email marketing campaign.

Solution 2:

Retrieved the 2021 data from customer source systems and built internal dashboards and generated an ad-hoc marketing campaign utilizing BigQuery and Looker.

Future considerations:

Parameterizing ports for a more robust code as well as deploying the code using docker and utilizing PRefect/Airflow. Due to the low velocity of change in the source data this consideration was not included in the initial build.

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Tools:

* Programming: Python (Pandas, Selenium, Regex), SQL

* Cloud: GCP, BigQuery, Cloud Storage, Batch Load

* Visualization: Looker