82: How to Get Started with Advanced Analytics R-Python w/ Ryan Wade

Ryan Wade joins us on AOF today to talk about how to use advanced analytics in your organization! Ryan has been in the analytics game for the last 20 years and is now a Senior Solution Consultant at Blue Granite, based in Indianapolis, Indiana. He recently authored the amazing must-read book, Advanced Analytics in Power BI with R and Python, and in today's chat, we get to hear all about why he wrote the book, who it is for and how you can use it to accelerate your data journey!

I met Ryan while speaking at a few conferences and was always impressed with his knowledge and great sense of humor! A professional football player turned data scientist, Ryan has a passion for breaking down advanced analytics in a way anyone can understand. Whether you’re already using advance analytics or researching how to get started Ryan’s knowledge on the topic will help you. Tune in with a pencil and paper in hand!

 

In this episode, you'll learn:

  • [0:09:22] The rise of the R and Python programming languages in the data world.
  • [0:13:25] Wide applicability of the advanced analytics frameworks and how it fits into organizations.
  • [0:16:44] The necessary, well-thought-out preparatory steps for a project utilizing advanced analytics.
  • [0:19:39] Why attention-grabbing visuals are not the most important part of data storytelling!
  • [0:22:31] The obstacles during the processes of identifying business questions, data extraction, and building repeatable models.
  • [0:23:13] Creating a sufficient team for data analytics and the vital roles of database administrator, active directory administrator, and more!
  • [0:27:15] The process of translating collected and manipulated data into data visualizations, models, and dashboards.
  • [0:29:30] Moving from the spreadsheet to advanced analytics; setting expectations, defining the business question, and securing the data.
  • [0:34:24] Challenges that data scientists face; issues around collecting the appropriate quantity and quality of data. 
  • [0:39:07] Client conversations around shortcomings and hurdles in advanced analytics. 
  • [0:41:26] Looking at the efficacy and popularity of R and Python right now in the data science world!
  • For full show notes, and the links mentioned visit: https://bibrainz.com/podcast/82

 

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