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 Disruptor Award celebrates the data teams who are using data and AI to disrupt an industry and challenge the status quo, deploying cutting-edge use cases that others will soon adopt.
Meet the five finalists for the Data Team Disruptor Award category:
Grammarly has changed the world of digital writing, helping 30 million people write more clearly and effectively every day. The Data Platform team at Grammarly made it their mission to create a data ecosystem that would strengthen the engineering and analytical excellence embodied by the product. No compromises. With a small but mighty team, they were able to successfully migrate to the Databricks Lakehouse architecture. Grammarly now makes 5 billion daily events available for analytics in under 15 minutes. Engineering teams have a tailored and centralized platform to ensure product and feature releases bring joy and value to users. Efficiencies are realized for both engineering and analytics without the risk of compromising the high data security and compliance standards at Grammarly. With the Databricks Lakehouse in place, Grammarly has been able to rapidly establish a genuinely data-driven culture, empowering all teams to make more intelligent decisions for the business autonomously.
Ophelos is using Databricks Lakehouse Platform to power its AI and machine learning efforts to disrupt the traditionally antiquated and hostile debt collection industry and turn it into one that’s compassionate, flexible, automated and preventative, via the Ophelos Debt Resolution Platform. The company created OLIVE (Ophelos Linguistic Identification of Vulnerability), a cutting-edge natural language processing (NLP) model that predicts the likelihood that a customer is vulnerable and identifies the possible causes. Ophelos is also addressing customer service efficiency and customer experience through the Ophelos Decision Engine, an ML-powered solution that automatically calculates the long-term effects of each action, and then creates bespoke communication strategies for each individual customer. All of this data is collected anonymously in a real-time analytics dashboard to ensure businesses truly understand their customers and how they can help.
PicPay is a Brazilian technology company that facilitates the payments of more than 30 million active users, who transacted more than 91 billion reais in 2021. But the company doesn’t want to stop there, aiming to resolve the entire financial life of its clients in one app. The resources cover a digital wallet, P2P payments, financial marketplace, electronic commerce, social features and much more. To manage the complexity and scale of data quantity and processing in real time, PicPay’s data team uses the Databricks Lakehouse Platform to process and unify large volumes of data, including transaction success rates, transaction types, fraudulent activities, and much more. It makes it easier for teams across organizations to use ML to improve customer engagement and margins, analyze and automate rebate incentives, segment customers based on usage patterns, and predict how customers will use rewards by enabling more targeted programs. Now, the team can expand its capabilities in areas such as transportation and games and provide thousands of Brazilians with a single platform for all their needs.
As the Sports & Entertainment businesses are rapidly transforming into Direct-to Consumer markets, a new world of opportunity is opening up for rights holders to redefine the commercial value of their business by gaining a better understanding of their fanbase. But it’s not always easy for organizations to optimize their myriad of fan touch points and engagement into a monetizable asset. Pumpjack Dataworks is changing the game by building an analytics platform on top of Databricks Lakehouse, leveraging key features such as Delta Sharing and Unity Catalog, to provide clients with a scalable, unified view of all their data to help create a better fan experience, drive new sponsorship and OTT opportunities, and securely exchange data between business partners to realize new revenue streams. Currently, the company is providing data solutions for Major League Rugby, Real Madrid, Inter Miami CF, Dallas Mavericks, and others throughout the world. Fan data is undervalued, and the product solutions powered through Pumpjack and Databricks empower clients to seize control of their data and grow its asset value.
While electric cars in the consumer market have been gaining in popularity in recent years, they still make up a small percentage of vehicles on the road. Rivian Automotive sees them as key to a more sustainable future. The company is redefining the driving experience and optimizing vehicle performance for a safer and greener world. With the Databricks Lakehouse Platform, Rivian’s data team is building a next-generation platform for software-defined vehicles that uses advanced analytics, BI dashboards, and ML to gain a deep understanding of vehicle performance in the real world. For instance, they can now access vehicle data on charging efficiency, vehicle dynamics and airbag activity to help provide predictive diagnostics and inform the development of software updates. With these broad insights, they can identify and solve potential issues related to reliability, automated driving functionality, and battery management. As a result, the company can innovate faster, reduce costs, and ultimately, deliver a better and more sustainable driving experience to customers.
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.