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The annual Data Team Awards showcase how different enterprise data teams are delivering solutions to some of the world’s toughest problems. 

Nearly 300 nominations were submitted by companies from diverse industries and regions across six categories. Each of these organizations have displayed remarkable innovation in their use of data and AI initiatives, and we want to help tell those stories. As we approach the Data and AI Summit, we will highlight each category's finalists in the coming days.

The Data Team Transformation Award honors the data teams who are taking their business to the next level with data-driven transformation, accelerating operations that lead to clear, impactful results.

Below are the finalists for 2023’s Data Team Transformation Award:

 

Albertsons

As the low-margin grocery business grapples with the rise of profitable e-commerce models over traditional brick-and-mortar stores, Albertson's steadfast dedication to putting customers first is reshaping the industry, propelling it into a transformative era of unparalleled shopping experiences. Core to their effort was their decision to migrate real-time workloads to Databricks Lakehouse, streamlining the creation of data pipelines with Delta Lake and Feature Store and unlocking the power of ML to deploy new use cases to improve retail operations, including predicting customer demand, automating supply chain operations, and optimizing e-commerce fulfillment. With Databricks Lakehouse, Albertsons now has the underlying technology to transform how a multitude of other teams — from merchandising and marketing to operations and human resources — are able to apply AI to solve their biggest problems that provide the best possible customer experience.

 

AXA France

With over 6.3 million customers, AXA France's drive to provide innovative, personalized and differentiated financial services has ushered in a massive digital transformation as a top company objective. With Databricks Lakehouse Azure Solutions, AXA France has fundamentally changed the way they operate and use data — unifying 200TB of data from 54 data sources into a single enterprise data platform. Since the migration, 20x more users now have easy access to data (from data teams to analysts and investment managers, and executives), and a new data-driven culture has been born. Service Level Agreement on BI analytics and ML projects have more than doubled thanks to this platform. AXA France has undergone a remarkable transformation with the implementation of the Lakehouse. Not only have they cut TCO in half by migrating to the cloud, but they have also successfully developed a dynamic data strategy that has democratized data across the company — empowering not just the technologist but also end-users to be more productive with their data.

 

Humana

Humana strives to help the 17 million members it serves to achieve their best health. With data-driven insights being the key to better serving those members, Humana looked to improve data-driven initiatives with a collaborative Machine Learning (ML) platform that has been used by over 700 data scientists since it launched in 2019. Today, Databricks Lakehouse supports ML models that optimize marketing campaign performance, predict member readmittance, and accelerate procedure authorizations. The programs these models support generate numerous benefits from higher year-over-year retention, lower fraudulent and wasteful spending, and avoid hospitalizations for its 17 million members. For Humana’s data scientists, the Lakehouse has removed silos and provided a centralized platform to unify diverse member and operational data, leading to significant advancements and improvements across their data-driven initiatives.


IFC/World Bank 

The International Finance Corporation (IFC), a member of the Word Bank Group, is harnessing the power of big data and AI to address development challenges of poverty and climate change while making investment decisions guided by responsible and sustainable principles. IFC successfully scaled its AI-powered MALENA platform using Databricks Lakehouse to accelerate the development of custom machine learning (ML) models. Leveraging faster data processing coupled with GPU computing that scales on-demand, IFC designs, trains, and runs Large Language Models (LLMs) to analyze massive amounts of text using natural language processing (NLP). MALENA can analyze 19,000 sentences per minute compared to human readers who read 15 to 20 sentences per minute — a 950x improvement that can reduce document review times from weeks to days. And by leveraging an architecture built on top of Azure and Databricks Lakehouse, IFC unified a diversity of internal and external data sources for both analytics and ML. As a result, the data team complemented historical ESG unstructured data with external data such as news and company disclosures to develop 10,000 company profiles and expanded insights for 180+ markets. By leaning on the power of Databricks Lakehouse, IFC can expand its support for emerging markets by providing this AI-powered solution to other investors to also extract actionable insights from unstructured ESG data at scale – contributing to building sustainable emerging markets.

 

Unilever

Unilever is one of the world’s largest consumer goods companies with a portfolio of leading, purposeful brands; an unrivaled presence in future growth markets; and a determinedly commercial focus as a sustainable business. As suppliers of Beauty & Well-being, Personal Care, Home Care, Nutrition and Ice Cream products, it has sales in over 190 countries and products used by 3.4 billion people every day. The Unilever Compass, its sustainable business strategy, is set out to help deliver superior performance and drive sustainable and responsible growth while improving the health of the planet; improving people's health, confidence and well-being; and contributing to a fairer and more socially inclusive world. Data and analytics play a pivotal part in strategic delivery. With petabytes of data – including regional and customer data - at Unilever’s disposal, democratization is key to the ability to modernize data strategy and transform operations. Unilever’s European in market Data and Analytics team has undergone an ambitious transformation using Databricks Lakehouse to simplify and standardize European data. The Data Engineering team created a robust data foundation that harmonizes data across all European markets (39+ markets) into a common, integrated and unified data platform. This has enabled cross Europe trade-offs and simplified the decision-making process, making it transparent and uniform across all business units and markets in Europe. Business users are provided with metadata-driven tools that allow them to effortlessly handle or bring in additional data to answer their specific business questions with minimal assistance from the engineering team. These tools were initially tested with 12 projects across different functions in Europe, where hundreds of new objects were created quickly and securely. The established framework today empowers business users throughout the organization to be data-driven in ways not possible before. Harmonized European data foundations, built on top of Unilever’s Data as a Platform data lake, have transformed Unilever's approach to data and its ability to democratize the delivery of value to the business. With a consolidated view into external and internal data sources on a scalable, open platform, 2400 daily users in Europe now have a holistic view of performance across the region. This enables decision-making across every aspect of the business to inform the granular growth opportunities and most valuable actions across Europe.

 

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