Rwazi Databricks data previews
Data teams open five Rwazi real-world datasets as Delta tables inside their own workspace.
- Five previews
- Delta Sharing
- 190+ countries
Each preview lands as Delta tables in a Unity Catalog workspace.
Five Rwazi previews on Databricks Marketplace cover audio, consumer, insurance, and retail data.
Consumers and verified contributors supply the records as zero-party data.
Models stop at the business
Data teams build models on records their own business produces. Consumers, stores, and conversations outside the business sit beyond that data. Teams then model the wider market on assumptions.
Rwazi supplies real-world records from consumers and stores across markets. Each preview opens as Delta tables beside existing data. Data scientists test the fit in a notebook first.
What data teams gain
The previews give data teams three advantages.
Why use the Databricks listings?
Databricks Marketplace brings Rwazi data into the lakehouse a team already runs.
Delta Sharing delivery
Delta Sharing places the Rwazi tables straight into the workspace.
Familiar workspace
Teams work on Rwazi data inside the workspace they already run.
Preview first
Each preview opens from its listing before any commercial step.
Five previews, three packs
The Rwazi Databricks listings group into AI Datasets, Consumer Activity, and Vision.
Open a preview
Each listing adds its preview to a Databricks workspace as its own catalog.
Commissioned sets start with the scoping form.
Four jobs for the previews
Each job starts in a Databricks notebook.
Speech model training
Speech teams need natural conversation across accents and everyday settings. Studio recordings sound cleaner than real life.
Rwazi supplies unscripted multi-speaker conversations recorded in homes, cafes, and markets. Engineers load the preview to check audio quality and labels. The team then scopes the languages and hours a full order needs.
AI-assisted shopping
Consumer goods and retail teams want to know how often shoppers ask AI assistants before buying. Web analytics shows only the final click.
Rwazi records which categories consumers research with AI assistants and how often. Analysts split that use by market, age, and category. Marketing teams then plan content for the questions shoppers ask.
Store execution checks
Commercial teams need to see which outlets stock their products and at what price tier. Distributor reports describe shipments more than shelves.
Rwazi supplies outlet records with products stocked, price tier, and availability. Analysts compare that coverage with planned distribution. Sales teams then target the outlets where the gap runs widest.
Insurance propensity
Insurance data scientists score which consumers will buy a given cover. Internal features describe current policyholders only. Prospects outside the book get weak scores.
The insurance preview adds holdings, purchase channels, and decision factors by market. Engineers turn those fields into segment-level features. The propensity model then scores prospects across the wider market.
Who works with the previews?
Four Databricks roles use the previews.
Data scientists
Data scientists test Rwazi fields as model inputs.
Speech and machine learning engineers
Engineers evaluate the audio preview for training and testing sets.
Analytics leads
Analytics leads compare store and consumer data with internal results.
Data engineers
Data engineers wire the Rwazi tables into scheduled jobs.
From listing to features
Get a preview
Accepting a listing creates a Unity Catalog catalog with the Rwazi tables.
Grant access
The platform team grants that catalog to the right users and groups.
Build features
Data scientists query the tables in notebooks and derive model features.
Previews and commissioned data
Commissioned sets extend each preview in three ways.
Commissioned sets cover one country or a footprint across 190+ countries.
Refresh options span one-time, monthly, quarterly, and continuous delivery.
Buyers add extra fields to a commissioned set.
Control of the share
The platform team decides who reads each Rwazi catalog.
Scope a commissioned set
Data teams describe the target markets and the model the data will feed. Rwazi returns a proposed scope by email.
Databricks listings → marketplace.databricks.com · Existing customers → /book-a-demo