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

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 DataRobot’s AI Cloud platform solves time series problems
  • DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely – it's almost like magic!
    Omair Tariq
    Omair Tariq

    Data Analyst, Symphony Post Acute Network

  • I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
    Oliver Rees
    Oliver Rees

    General Manager – Torque Data at Virgin Australia

  • At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
    Akshay Tandon
    Akshay Tandon

    VP of Strategy Analytics, LendingTree

  • We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.
    Evariant