Blog and Resources

Zip code-level data reveals critical insights into economic, social, and environmental patterns. This post explores why controlling for location in prediction models is essential and how self-selection influences outcomes.
Seasonality refers to recurring data patterns driven by factors like weather or holidays. Learn how understanding these fluctuations can improve business forecasting and strategy.
Learn how automating data aggregation and normalization can enhance your data pipeline, freeing up valuable time for data scientists and driving better insights.
This article discusses the importance of lagged variables in predictive modeling, illustrating how they improve the accuracy of economic forecasts and analysis.
The labor market, through indicators like non-farm payrolls and the unemployment rate, is a key measure of economic health. Sectors such as manufacturing, construction, retail, financial services, and professional services provide valuable insights into economic conditions. By analyzing these trends, macroeconomists and business leaders can better assess economic growth and anticipate changes. However, looking beyond broad employment categories can yield more precise economic insights. One sector worth considering is truck transportation employment.
Starbucks released its Pumpkin Spice Latte (PSL) early this year on August 22nd, beating last year's launch and competitors. The decision aims to extend sales, stay ahead in the market, and leverage new leadership for heightened visibility.
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