Event Summary 7.14.2016

The Data Warehousing Institute: Introduction to Statistical Analysis Event

Minneapolis, MN

The Minneapolis chapter of The Data Warehousing Institute (TDWI) met on June 21st for an Introduction to Statistical Analysis using the R programming language for statistical computing and graphics. The event aimed to expose participants to the software through demonstration and use cases.

The first speaker’s presentation was called Scaling up Data Science Teams. It focused on the efficiencies created by statistical programs that are augmented by cloud services. The speaker was particularly keen on the ease of use, compatibility, and low cost of using Amazon Web Services. He demonstrated using R and AWS with the crowd-pleasing use case of ‘Football’s Statistical MVP.’ Multiple factors and data sources were brought in to determine the MVP, and R was also used to visualize the outcomes. While ‘Football’s Statistical MVP’ wouldn’t be a shock to anyone who watches football, the use case did show the software’s ability to aggregate multiple data sources, analyze using advanced statistical methods, and visualize the outcomes.

The second speaker furthered the conversation by putting R’s efficiencies in context. He demonstrated the process he used to answer a broad question: What is impacting Hospital A’s revenue? This included incorporating multiple data sources, analysis in R, and cloud computing. He was able to refine his approach throughout, depending on his initial findings. Overall, he was able to generate a key insight for his client in four hours with minimal technology cost. This supported his argument that data science teams, supported by cloud computing and R (more so than other statistical software), can help us help clients cheaper, faster, and more agilely.

The event’s topics and messaging compliments Trexin’s use of advanced analytics software. Trexin’s data science team leverages both R and AWS (among other tools) with similar aims: to generate actionable insights for our clients using low-cost technologies, experienced programmers, and a proprietary agile methodology for exploratory analysis.

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