Semantic product search on Databricks

Accelerator for customer incentive investment using causal inference techniques

Translating text attributes (like name, address, phone number) into quantifiable numerical representations Training ML models to determine if these numerical labels form a match Scoring the confidence of each match

Ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases

Connect the impact of marketing and your ad spend to sales. Efficiently pinpoint the impact of various revenue-generating marketing activities to understand what works best. Focus on the best-performing channels to optimize media mix and drive revenue.

Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.

Automated Analysis of Product Reviews Using Large Language Models

Holiday recipe recommendation app built with Databricks

Create advanced customer segments to drive better purchasing predictions based on behaviors. Using sales data, campaigns and promotions systems, this solution helps derive a number of features that capture the behavior of various households. Build useful customer clusters to target with different promos and offers.

Use machine learning and the Databricks Lakehouse Platform for product matching that can be used by marketplaces and suppliers for various purposes. Resolve differences between product definitions and descriptions and determine which items are likely pairs and which are distinct across disparate data sets.

Intermittent Demand Forecasting With Nixtla on Databricks

Perform demand forecasting at the part level rather than the aggregate level to minimize disruptions in your supply chain and increase sales. Manage material shortages and predict overplanning

Get started with our Solution Accelerator for Scalable Route Generation to optimize delivery routes and increase profitability

Get started with our Solution Accelerator for Propensity Scoring to build effective propensity scoring pipelines that: Enable the persistence, discovery and sharing of features across various model training exercises Quickly generate models by leveraging industry best practices Track and analyze the various model iterations generated

Build a wide-and-deep recommender with collaborative filters that takes advantage of patterns of repeat purchases to suggest both previously purchased and related products.

Zingg fuzzy matching for products using metadata and images

Survival analysis is a collection of statistical methods used to examine and predict the time until an event of interest occurs. In this Solution Accelerator, learn how to use different survival analysis techniques for predicting churn and calculating lifetime value.

Create fine-grained and viable estimates of buffer stock for raw material, work-in-progress or finished goods inventory items that can be scaled across the supply chain. Free up working capital that would be tied up in inventory and reallocate to more productive uses.

Get started with our Solution Accelerator to rapidly ingesting all data sources and types at scale, build highly scalable streaming data pipelines with Delta Live Tables to obtain a real-time view of operation, and leverage real-time insights to tackle your most pressing in-store information needs

Use personalized images to enhance the output of an image generating model