D211 - Advanced Data Acquisition

Advanced Data Acquisition enhances theoretical and SQL skills in furthering the data analytics life cycle. This course covers advanced SQL operations, aggregating data, and acquiring data from various sources in support of core organizational needs.

Course Analysis

This course operates in tandem with D210 - Representation and Reporting#, utilizing Tableau Desktop to create dashboards for the churn/medical datasets, supplemented by an external dataset you select. The primary distinction in this course is the method of data importation; instead of a single CSV file, you’re tasked with uploading your data into a PostgreSQL database via a virtual machine using pgAdmin, then connecting Tableau to that database. This course proved to be more intricate than D210, largely due to the virtual machine work and several ambiguously written rubric components. Ambiguity in rubrics has been a recurring theme in this program, but this course exacerbated that issue.

For the external dataset, I continued with the Telco customer churn data I mentioned in D210. I bypassed the DataCamp courses, feeling confident in my pgAdmin skills from a previous course D205 - Data Acquisition# and my familiarity with Tableau from D210. The performance assessment in this course doesn’t necessitate a complete Story in Tableau as D210 did, but rather a few dashboards. I simply replicated two dashboards from my D210 Story, using the same merged dataset I had compiled in D210.

Final Thoughts

The process of creating and preparing the combined dataset involves using pgAdmin and PostgreSQL, shifting away from Python or R. This wasn’t overly difficult, essentially translating the Python commands from my D210 project into PostgreSQL for D211. The virtual machine posed more of a hurdle than the coding itself.

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