Next Generation Time Series Forecasting for the Real World Not the Ideal World BKG V2

Next-Generation Time Series: Forecasting for the Real World, Not the Ideal World

Time series models make forecasts by learning from history, using data that ranges from individual transactions to data collected daily, weekly, or over a longer term. But turning that data into accurate predictions can be a very complicated process, involving a balance between finding the best data sources and creating the best features from them. It also means incorporating a deep understanding of your business.

Knowing how to approach time series projects is crucial for organizations in their quest to become AI-driven. Our ebook, Next-Generation Time Series: Forecasting for the Real-World, Not the Ideal World, looks at the many ways organizations are tackling some of the most valuable, yet difficult, time series problems.

Download this ebook to learn about:

  • The current state of time series analysis
  • Specific time series applications, such as demand forecasting and anomaly detection
  • How to choose the right time series use cases
  • How the DataRobot AI Platform solves time series problems
DataRobot is an indispensable partner helping us maintain our reputation both internally and externally by deploying, monitoring, and governing generative AI responsibly and effectively.
Tom Thomas
Tom Thomas

Vice President of Data & Analytics, FordDirect

The generative AI space is changing quickly, and the flexibility, safety and security of DataRobot helps us stay on the cutting edge with a HIPAA-compliant environment we trust to uphold critical health data protection standards. We’re harnessing innovation for real-world applications, giving us the ability to transform patient care and improve operations and efficiency with confidence
Rosalia Tungaraza
Rosalia Tungaraza

Ph.D, AVP, Artificial Intelligence, Baptist Health South Florida

DataRobot provides us with innovative ways to test new ideas. Given a problem and a dataset, DataRobot allows us to generate multiple prototypes 20% faster. And the process facilitates the learning evolution of our data scientists.
Diego J. Bodas
Diego J. Bodas

Director of Advanced Analytics, MAPFRE ESPAÑA

The value of having a single platform that pulls all the components together can’t be underestimated. Then there’s the combination of the technology and the collaborative DataRobot team. If either one of those wasn’t there, I would have looked elsewhere.
Craig Civil
Craig Civil

Director of Data Science & AI

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