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Unified Data Analytics | Databricks Webinar Series

Available on-demand

Performing fine-grained forecasts on day-store-SKU is beyond the ability of legacy, data warehousing based forecasting tools. Demand for products varies by product, store and day, and yet traditional demand forecasting solutions perform their forecasts at the aggregate market, week and promo group levels.

With the introduction of the Azure Databricks Unified Data Analytics Platform, retailers are able to see double-digit improvements in their forecast accuracy. They can perform fine-grained forecasts at the SKU, store and day as well as include hundreds of additional features to improve the accuracy of models. They can further enhance their forecasts with localization and the easy inclusion of additional data sets. And they’re running these forecasts daily, providing their planners and retail operations team with timely data for better execution.

In this session, we will look at how Databricks enables forecasters to scale the level of processing required and predict demand at a finer level of temporal and location granularity.

In this webinar:

  • Learn generate a large number of fine-grained forecasts at the store-item level in an efficient manner leveraging the distributed computational power of Databricks Unified Data Analytics Platform
  • We’ll show how to forecast time series data precisely using Facebook’s Prophet
  • Tips on how to gather insights in general trends and seasonality when performing demand forecasting
  • How to train a large number of models using the defacto distributed data processing engine, Apache SparkTM.
  • Finally, we can then present this data to analysts and managers using BI tools to enable the decision making required to drive the required business outcomes.