In this blog series we’ll be experimenting with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source devops on the cloud with protected internal legacy tools, SQL with noSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT sensor data with idle chatting, we’re curious to find out: will they blend? Want to find out what happens when IBM Watson meets Google News, Hadoop Hive meets Excel, R meets Python, or MS Word meets MongoDB?
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Today: Google Big Query meets SQLite. The Business of Baseball Games
Author: Dorottya Kiss, EPAM
They say if you want to know American society, first you have to learn baseball. As reported in a New York Times article, America had baseball even in times of war and depression, and it still reflects American society. Whether it is playing, watching, or betting on the games, baseball is in some way always connected to the lives of Americans.
According to Accuweather, different weather conditions play a significant role in determining the outcome of a baseball game. Air temperature influences the trajectory of the baseball; air density has an impact on the distance covered by the ball; temperature influences the pitcher’s grip; cloud coverage affects the visibility of the ball; and wind conditions - and weather in general - have various degrees of influence on the physical wellbeing of the players.
Another interesting article on Crowdhitter describes the fans’ attendance of the games and how this affects the home team’s success. Fan attendance at baseball games is indeed a key factor, in terms of both emotional and monetary support. So, what are the key factors determining attendance? On a pleasant day are they more likely to show up in the evening or during the day, or does it all just depend on the opposing team?
Some time ago we downloaded the data about attendance at baseball games for the 2016 season from Google’s Big Query Public data set and stored them on our own Google Big Query database. For the purpose of this blending experiment we also downloaded data about the weather during games from Weather Underground and stored these data on a SQLite database.
The goal of this blending experiment is to merge attendance data at baseball games from Google Big Query with weather data from SQLite. Since we have only data about one baseball season, it will be hard to train a model for reliable predictions of attendance. However, we have enough data for a multivariate visualization of the various factors influencing attendance.
Topic. Multivariate visual investigation of weather influence on attendance of baseball games.
Challenge. Blend attendance data from Google Big Query and weather data from SQLite.
Access Mode. Database Connector node with Simba 4.2 JDBC driver compatible with access to Google Big Query and dedicated SQLite Connector node.