About Me


CAREER PROFILE


A seasoned professional with several years of experience in advanced data visualization, analytics, modeling, and storytelling. Skilled in implementing business strategies from large-scale data models by using multiple data sources and large data sets. Passionate developer of custom-built visualizations and analytical solutions which utilize advanced modeling and statistics enabling all levels of the organization to drive performance.

A driven leader who has spearheaded multiple enterprise projects and initiatives by identifying opportunities to make improvements in efficiency and producing data driven results. Ability to apply unique experiences in data science, data analytics, finance, technology, and operations resulting in creative solutions to significant challenges.

CORE KNOWLEDGE & SKILLS


Tableau Desktop | Tableau Server | Tableau Prep | Power BI Desktop | R | R Shiny Apps | Alteryx | PostgreSQL | Microsoft SQL Server Management Studio (SSMS) | Excel | VBA | IBM Cognos TM1 | Essbase | OLAP | Data visualization | Advanced dashboarding | Data storytelling | Complex data modeling | Optimization | Classification | Regression | Explainable machine learning | Anomaly detection | Clustering | Predictive modeling

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MySQL Part 1: Getting MySQL Set Up in goormIDE

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Do Popular Market Index Returns Follow a Normal Distribution?

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Introduction Many statistical tests assume normality within the data set.  In other words, before you perform any type of parametric test, one should first view the data sets and run experiments to test this assumption.  This article will show you how to pull several market indices’ historical returns and see if they follow a normal distribution using the Shapiro-Wilk test. The main reason this article is testing the normal distribution validity of portfolio returns is to set up Monte Carlo simulations to project future retirement balances and their respective probabilities in Tableau.   To view the interactive application and estimate your own retirement savings, click here .   Sources:  Normality Test in R Analyzing Performance with tidyquant Market Index Background We were able to pull the following historical index information using a convenient package in R called tidyquant .  We will test the normality of the various benchmarks listed below...
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