Alteryx is helping airlines embrace a data-driven culture. One major North American airline has saved almost $100m in fuel efficiency by adding a data-driven mindset to its business decision-making. It was able to do this by dramatically increasing its fuel forecasting efficiency. Employing more than 24,000 pilots and flight attendants, the company has also improved the accuracy of its crew scheduling forecasts, enabling it to save hundreds of thousands of dollars in extra costs that previously arose from the failure to anticipate daily changes.

When it comes to the world of aviation, Alteryx allows airlines to look at operational analytics and automation, optimize pricing, and analyze customer data. Alteryx has worked with many aviation groups and airports across the globe, including Copa Airlines, Virgin Atlantic, Dubai Airport, Munich Airport, and Southwest Airlines.


Simple + powerful analytics accelerates decision-making and  transforms business outcomes for thousands of companies worldwide.

Cluster Analysis is a method used to classify objects into groups where those similar in characteristics are grouped together in a cluster. It is also known as segmentation analysis or taxonomy analysis. Clustering helps us look at the data as a whole so we can classify the points and logical structures based on the groupings we choose to create. Clustering has several uses, including in marketing, where it is used to identify homogenous groups of buyers; in medical science, where it is used for disease classification; in geology it is used to identify the weaknesses of earthquake-prone regions. In Alteryx, it is built in. 

k-means Clustering

Spatial Analysis

Spatial data, also known as “Geospatial Data” refers to records in the dataset that have a geographic aspect. It can be the location of a store, the distance between two bus stops, or the boundaries of a state. Alteryx offers the spatial toolset to help users derive meaningful insights and information from spatial data.  

Alteryx has built-in Decision Trees capabilities. These are some of the easiest models to understand and illustrate as they are straightforward and don't require complex interpretation. Decision Tree models are good for handling complex, non-linear relationships, and outliers on the data, but it also has its disadvantages. Some of its predictions tend to be weak since it is prone to overfitting. They are not very robust, because small changes in the training data can give a larger change in the output. However, they are one of the most commonly used analytical models around. 

Decision Trees

Logistic Regression

Logistic Regression is a binary classification algorithm. Meaning, it predicts either true or false, churn or not, pass or fail and other binary categorical values. This algorithm also uses a regression function which classifies the target variable based on probability. Logistic regression fits the data to an “S” shaped logistic function also known as the Sigmoid Curve. It curves from 0 to 1, where 0 is the least probable or false, while 1 is the most probable or True. This splits the data into one of the two categories and each row of data is classified by comparing the probability to a threshold between categories. With Alteryx, it's included.


Intellligencia is a Hong Kong- and Macau-based software consulting company that works specifically in the hospitality, gaming, fintech, esports, manufacturing, retail, sports betting, and travel industries. Although located in Asia, we work with clients as far away as North America, Mexico, India, Armenia, Australia, and the Philippines.


Address: 505 Hennessy Road, #613, Causeway Bay, Hong Kong

Phone: +852 5196 1277




Sign up to receive email for the latest information.
© Intelligencia Limited. All Rights Reserved. 2023