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Data Science

  • Filled Under: BI, Data Visualization, Machine Learning

Becoming better acquainted with data science and graph databases is my latest skill development focus. I've found that simple B2C or B2B applications are no longer enough to differentiate your product. Additional algorithms focused on content curation, recommendations, and complex problem solving are needed to continue simplifying our world's business problems.

I started my discovery into data science by mastering Neo4j and developing relationship hierarchies to better understand how company data is connected. The latter can represent anything from reported platform errors  to police brutality incidents within the United States - only your creativity limits your ability to optimize available data sets.  

In addition to my analysis and backend development with graph databases, I have developed a comfortable familiarity with Tableau and Qlik Sense when it comes to data visualization. Backend skills and tooling with distributed data systems is all good and well, but if you lack the ability to infer insights from that data - well then what you have becomes useless.

Here's a quick 5-minute dashboard that I spun up to give you an example of how easy I find creating insightful data visualizations in interactive ways: 

Overall, I have great confidence in the following data-science related skill-sets:

  • Data Visualization via Tableau 
  • Data Visualization via Qlik
  • Macro Automation in Excel 
  • Data Analysis and Visualization via R-Studio 
  • R Programming Language
  • Hadoop Configuration 
  • R Studio Machine Learning Algos

If you are interested in doing a data science collaboration, or what to learn more about my experience, feel free to reach out to me @