How I Built Anomalize Programming Case Study Matt Dancho & David Curry Business Science Learning Lab Special Topics: tidyverse and rlang (tidy eval) 

Learning Lab Structure ● Presentation (20 min) ● Demo’s (15 min) ● Presentation (20 mins) 

Success Story Bryan Clark - Data Scientist at H&M - Took DS4B 201-R - Building Apps that integrate R Shiny - Analyzed Risk Model of… - Wedding!!! (Congrats!) “This is legit a milestone in my development.” #BusinessScienceSuccess 

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Agenda ● Case Study ○ Time Series Anomaly Detection ○ Business Value ● The Solution ○ Anomalize ○ 3 min Demo ● Functional Programming ○ How I made anomalize ○ Tools in my Toolkit ● R Demo ○ Rlang in 15 minutes ● Becoming a Complete Data Scientist ○ Learn the skills that transform you & your organization 

Business Case Study Detecting Time Series Anomalies 

Web Traffic Business Objectives Understand when web traffic was abnormally changing Identify cause-effect relationships Thousands of time series Anomaly Detection 

Step 1: What Software Existed? Twitter AnomalyDetection Pros: ● Open Source R Package ● Innovative method for detecting anomalies ● Piecewise Median for trend removal ● GESD for outlier detection Cons: ● Not scalable to many time series ● User interface was non-tidy ● Growth presented challenge https://github.com/twitter/AnomalyDetection 

Step 2 Improve on Twitter’s Algorithm R Package Goals Scalability to many time series Simple user interface (tidyverse-compliant) Handle growth (trend) in time series 

The Solution anomalize 

Anomalize: Tidy anomaly detection https://business-science.github.io/anomalize/ 

Scalable https://www.kaggle.com/c/web-traffic-time-series-forecasting 

Good at detecting anomalies Game of Thrones (season 6) From Wikipedia, the free encyclopedia The sixth season of the fantasy drama television series Game of Thrones premiered on HBO on April 24, 2016, and concluded on June 26, 2016. GOT Season 6 Kit Harington’s Views on wikipedia spike https://en.wikipedia.org/wiki/Game_of_Thrones_(season_6) 

Many uses Malicious Behavior Is someone (or some organization) attacking our organization? https://www.business-science.io/business/2018/06/10/infosec-anom alize-threat-hunting.html 

Quick Demo (3 min) anomalize 

Functional Programming How I did it 

3 Simple Steps 1 2 3 1. Remove Trend & Seasonality 2. Analyze residuals & detect outliers 3. Recompose for visualization 

Simple Scalability Scaling is the same process. Just replace filter() with group_by() 4 

Tools Needed A tool for developing tidyverse functions Functional Programming Week 5 - DS4B 101-R Course Foundational Data Science Tidyverse Compliance - rlang Week 2 - DS4B 201-R Course Advanced ML & Business Consulting 

Functional Programming Make functions that do things Key Concepts How to program in R Learn the 2 most common design patterns 1. Vector Functions 2. Data Functions Learn how to scale analysis with purrr DS4B 101-R: Week 5 Functional Programming & Iteration 

rlang A tool for developing tidyverse functions Key Concepts Metaprogramming Capture expressions before they are evaluated by R Evaluate when we are ready Make functions that comply with dplyr and ggplot2 API DS4B 201-R: Week 2 Understanding the Business 

Capturing Expressions If R code hits an expression, it’s automatically evaluated Inside tidyverse functions, we need to pass column names (pointers to a column) If R sees them, it evaluates them. This causes an error. User enters some column name R tries to evaluate looking in the Global Environment ERROR: Object “value” not found 

Capturing Expressions Rlang provides tools to enable the tidyverse style of programming enquo(): Captures the expression !! Tells R to evaluate it in the correct context (in relation to the data that the column belongs to) Capture the column before R has a chance to evaluate Evaluate the captured column in the correct context IT WORKS!! 

Demo rlang in 15 minutes 

1,000 Per company My estimate of the number of unique business problems that repeat every day, week, month, or quarter 

Functional Programming Solve unique + recurring business problems 1. Automate repetitive tasks 2. Scale from 1 problem to Many problems 

Employee Churn Report ● Your department is charged with monitoring employee churn ● Every month, you report which departments have the highest churn, rate of change, impact (+/-) of churn prevention tactics 

Calculating Employee Churn Cost 

Calculating Employee Churn Cost Automates the process of doing repetitive tasks 

Becoming a Complete Data Scientist Learn the skills that transform you & your business 

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