Blending Fine Wine with Alteryx: An Optimization Tutorial

This article is by Dan Putler and originally appeared on the Alteryx Data Science Blog here: https://community.alteryx.com/t5/Data-Science-Blog/Blending-Fine-Wine-with-Alteryx-An-Optimization-Tutorial/ba-p/517428

 

The Optimization Tool has been a part of the Alteryx predictive tool suite for a few years now, but there has been a fairly limited discussion of how it works under the hood, the types of problems it can address, and the different ways the tool can be configured and used (exceptions to this are excellent articles by Philip Mannering, SydneyF, and JoeM).

 

There are actually numerous types of optimization methods.

What’s New in Alteryx 2020.1?

2020.1 WHAT'S NEW?

Take your thrill of solving to a whole new level and make a resolution to turn more actionable insights into business outcomes with the 2020.1 Re.Solve release. Start your decade off on the right foot by experiencing new updates that will change the way you solve, interpret your data, and break down barriers within your organization.

Getting to Know Optimization: Linear Programming

This article is by Dan Putler and originally appeared on the Alteryx Data Science Blog here: https://community.alteryx.com/t5/Data-Science-Blog/Getting-to-Know-Optimization-Linear-Programming/ba-p/513793

 

Linear programming is the oldest of the mathematical programming algorithms, dating to the late 1930s. The method can either minimize or maximize a linear function of one or more variables subject to a set of inequality constraints.

Beyond Single-Pass Analytics – What Changes With Scale

This article is by Sean Adams and originally appeared on the Alteryx Engine Works Blog here: https://community.alteryx.com/t5/Engine-Works-Blog/Beyond-Single-Pass-Analytics-What-Changes-With-Scale/ba-p/513519

 

When we begin with analytics, either as a new practice within your firm, or starting a team in a new area–much of your work may initially be what I call "single-pass analytics," where the data goes from source, to prep, straight to the end-point.

Enriching Tax Data with Location Information

This article is by Robert Lenius and originally appeared on the Alteryx Engine Works Blog here: https://community.alteryx.com/t5/Engine-Works-Blog/Enriching-Tax-Data-with-Location-Information/ba-p/509848

 

Working in finance, I’m somewhat bummed that I don’t often get to explore the possibilities within location-based data.

Expand Your Predictive Palette III.I: Sales Forecast with Prophet Tool

This article is by Timothy Lam and originally appeared on the Alteryx Data Science Blog here: https://community.alteryx.com/t5/Data-Science-Blog/Expand-Your-Predictive-Palette-III-I-Sales-Forecast-with-Prophet/ba-p/504651

 

At a high-level, forecasting techniques can be broken down into three main categories:

Historical Average with Sliding Windows

Examples: Seasonal Decomposition, Exponential Smoothing (ETS)
Pros: Simplicity: any tool can integrate like Excel & Tableau;
Cons: Laggardly reaction to changes & overly responsive with outliers, only works with simple structure

Linear Models

Examples: ARIMA, VAR(Good for multiple time series)
Pros: Works with consistent variation, such as established seasonality trends
Cons: Proper assumption on stationarity and homoscedasticity (statistics term for consistent variance/error). Careful predictor selection to prevent multicollinearity (statistics term when predictors are linearly correlated).

Non-Linear Models

Examples: Prophet, GARCH (generalized autoregressive conditional heteroskedasticity), Deep Learning
Pros: Discovering non-linear relationship & data drift in your data.