Equipping all Teams with Data & AI: Announcing the Finalists for the 2022 Databricks Data Team Democratization Award

The annual Databricks Data Team Awards recognize data teams who are harnessing the power of data and AI to deliver solutions for some of the world’s toughest problems.

Nearly 250 teams were nominated across six categories from all industries, regions, and companies – all with impressive stories about the work they are doing with data and AI. As we lead up to Data and AI Summit, we will be showcasing the finalists in each of the categories over the coming days.

The Data Team Democratization Award recognizes data teams who are driving the CoEs that are delivering data into the hands of empowered users across the organization — making every team a data team.

Meet the five finalists for the Data Team Democratization Award category:

Centers for Disease Control and Prevention
The Centers for Disease Control (CDC) has been on the frontlines guiding communities, governments and healthcare workers in response to the COVID-19 pandemic. Throughout this time, data and AI has played a critical role in helping to deliver fast insights across the U.S., helping to save lives. The Databricks Lakehouse has empowered the CDC to democratize data at massive scale — ingesting high volumes of all kinds of data on CDC’s Enterprise Analytics and Visualization (EDAV) platform. The lakehouse paradigm was implemented at CDC for COVID-19 vaccines data coming in from states and federal agencies (at a pace of 5+ million new records per day) and sharing vaccination and mortality rate metrics with cities, states, the White House and the general public so that they can make more informed decisions at local, regional and national level. These decisions included when to reopen businesses, enforce mask mandates, school closures, and more. Through the democratization of data and unification with analytics, they’ve been able to deliver on many more use cases to inform the people within the US of current health situations and provide the government and general public with actionable insights needed to ensure the highest levels of health within the US.

コンデナスト(Condé Nast)
Condé Nast is at the forefront of the publishing industry’s digital revolution, delivering engaging online content to millions of readers of iconic titles like Vogue, The New Yorker, Vanity Fair, and Wired. To do so, the data team at Condé Nast has harnessed data and AI to improve content performance and enrichment, fuel process innovation, and increase market revenue, all built upon Databricks Lakehouse. The Lakehouse supports “Evergreen,” a unified platform — from data teams to data consumers —using ML and analytics to derive faster insights that expand the reach and impact of their content, and enable data-driven decision-making to steer operations at a global level. As a result, Condé Nast has been able to increase revenue across multiple networks through predictive ad optimization; use SQL to power dashboards and reports to help teams improve syndication volume and performance; unify performance insights across its global brands; and enabled their video division to report on a global scale with a single source of truth for analysis. With the help of Databricks, Condé Nast has fostered a culture where data is the common language and core of everything they do, helping to enhance the reach and impact of the distinctive content that the company is renowned for.

Corning Incorporated
Corning, a leading innovator in materials science, develops products that transform industries and enhance people’s lives. As data and AI continue to play a critical role for Corning to advance its leadership position, they’ve been focused on the use of data across all business units. Corning has created an Emerging Technologies team within in the IT function that is leveraging the Databricks Lakehouse. The data lakehouse enables Corning scientists, engineers and business knowledge workers to access vast amounts of data supporting many use cases across all of Corning’s businesses. The lakehouse enables teams to use data and AI for predictive maintenance, predictive demand planning, image recognition, and advanced supply chain analytics to explore and identify business value metrics. Whether it’s data scientists looking to build advanced machine learning and deep learning models or analysts using SQL to explore data and build BI reports for business stakeholders, Corning continues to look for new opportunities to advance data consumption/use and empower users across the organization.

Gap Inc.
Gap Inc. is a collection of purpose-led lifestyle brands including Old Navy, Gap, Banana Republic, and Athleta, and the largest American specialty apparel company. We use omni-channel capabilities to bridge the digital world and physical stores to further enhance the shopping experience for our customers. To enable this at scale, Gap Inc. fundamentally redesigned its data architecture to make it simple, secure and accessible. With principles of federated data ownership, kappa architecture, and powered by Databricks Lakehouse, they have eliminated data silos and brought consistency across data science models, analytics and BI. With the Gap Data Platform COE driving data governance, federation and self-service, teams across Gap Inc. can qualify and publish data, search data and request access, comment and collaborate with SMEs and peers, and get a common understanding of shared datasets. With a petabyte of customer and foundational data in the Lakehouse, and other domains in progress, they continue to lower the time and cost of insights and innovation across Gap Inc. and their partners. Case in point: The Gap Inc. Data Sciences teams now have easy access to qualified, granular, near-real-time data and metadata – plus a 40x decrease in query times and a 5x decrease in data latency. Along with a migration to the Databricks ML Platform (feature stores, MLflow, distributed training/scoring, integration with Lakehouse), the teams got to a 95% decrease in end-to-end for the largest production models, and substantially reduced complexity and time to market overall.

Sam’s Club
Sam’s Club provides superior products and savings to millions of members with its highly curated assortment of items. It’s a huge undertaking that requires exemplary demand forecasting, supply chain optimization, and overall member experience. As an early adopter of the lakehouse architecture, Sam’s Club has built the Common Data Platform — an internal analytics service that has put the power of all their data in the hands of over 1,600 monthly active users. With Databricks Lakehouse powering its data platform, teams have been able to transform data from billions of transactions and events into actionable insights and predictive ML models. These models can yield more accurate financial forecasts, optimize pricing, boost engagement with home delivery, curbside pickup, Scan & Go™, fight credit card fraud and forecast supply which has helped reduce food waste.

Check out the award finalists in the other five categories and come raise a glass and celebrate these amazing data teams during an award ceremony at the Data and AI Summit on June 29.

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