Proceso ETL
-
Updated
Apr 15, 2024 - Jupyter Notebook
Proceso ETL
Build a lakehouse for all your gamer data and use natural language processing techniques to flag questionable comments for moderation.
Get started with our Solution Accelerator for Order Picking to apply optimization logic to each order to: Avoid unexpected delivery outcomes and assess the impact of small variations on order picking Minimize total store travel time to increase profitability
In this solution accelerator, we demonstrate how generative AI, retrieval augmented generation (RAG) and multi stage reasoning can be used to better navigate through the complexities of regulatory filings, bringing more transparency for companies to disclose their societal and environmental impacts.
Increase viewer retention through data-driven engagement strategies: analyze both streaming and batch data sets to ensure a performant streaming content experience that drives engagement and loyalty.
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.
We demonstrate how FSI can leverage geospatial and graph analytics to anonymize card transaction data and monetize their assets to potential clients securely via delta sharing capability
By applying transfer learning on pre-trained neural networks, we demonstrate how Databricks helps insurance companies kickstart their AI/Computer Vision journey towards claim assessment and damage estimation.
Ship-to-Ship Transfer Identification using Geospatial Analytics
Develop an understanding of how a customer lifetime should progress and examine where in that lifetime journey customers are likely to churn so you can effectively manage retention and reduce your churn rate.
In this solution accelerator, we demonstrate a novel approach to consumer analytics by combining core mathematical concepts with engineering best practices and state of the art optimizations techniques to better model customers' behaviors and provide millions of customers with personalized insights
Identifying Campaign Effectiveness For Forecasting Foot Traffic
Equity Beta Calculation and CAPM
Increase conversion with personalized recommendations: Build a recommender that leverages product affinities to suggest additional items
In this regulatory reporting solution accelerator, we demonstrate how Delta Live Tables can guarantee the acquisition and processing of regulatory data in real time to accommodate regulatory SLAs. With Delta Sharing and Delta Live Tables combined, analysts gain real-time confidence in the quality of regulatory data being transmitted.
In this solution accelerator, we build a data asset that captures a full picture of the consumer and goes beyond traditional demographics, income, product and services (who you are) and extends to transactional behavior and shopping preferences (how you bank)
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.
Add a description, image, and links to the databricks-industry-solutions topic page so that developers can more easily learn about it.
To associate your repository with the databricks-industry-solutions topic, visit your repo's landing page and select "manage topics."