Databricks Consulting Services

HP Inc., renowned for its diverse range of printers, PCs, mobile devices, and services, faced significant data management challenges, with data siloed across multiple systems and heavy reliance on outdated warehousing technologies. This resulted in a cumbersome DevOps workload that impeded effective data utilization. To overcome these obstacles, HP Inc. turned to Databricks, seeking a scalable and unified analytics platform that could predict product issues and reveal new customer service opportunities. 

Databricks offered a solution that simplified the management of Apache Spark™, enabling HP Inc.’s data scientists to focus more on data analysis rather than DevOps tasks. This shift to a unified platform allowed for the analysis of high-volume data from over 20 million devices, enhancing their workflow significantly. Not only did Databricks streamline their data analysis processes, but it also fostered better collaboration among business analysts, data scientists, and subject matter experts. 

This strategic implementation of Databricks revolutionized HP Inc.’s approach to real-time IoT device management and process optimization. The unified platform significantly improved team productivity and innovation, as highlighted by John Landry, Distinguished Technologist at HP Inc. The results of adopting Databricks were clear: a more agile, efficient, and collaborative environment that propelled HP Inc. forward in its mission to create technology that amazes its users. 

Burberry, a renowned British luxury brand, revolutionized its marketing strategy by integrating Labelbox with Databricks Data Intelligence Platform. This collaboration allowed rapid image annotation for their extensive marketing assets, transforming a process that once took months into a matter of hours. The integration enabled Burberry’s marketing team to access and analyze high-volume unstructured datasets efficiently, enhancing decision-making for campaigns. 

The implementation significantly reduced manual efforts and time, allowing Burberry to realize a 70% improvement in generating insights. Additionally, the Databricks platform led to continual cost reductions, improving Burberry’s total cost of ownership over four years. This streamlined approach provided Burberry’s stakeholders with advanced tools to predict campaign engagement using data-driven insights, leading to smarter marketing decisions. 

The success of this project demonstrates how Burberry leveraged technology to enhance its marketing capabilities, offering a scalable and customer-centric solution. The partnership with Databricks and Labelbox underpins Burberry’s commitment to innovation, ensuring sustained growth and efficiency in their marketing strategies. 

Michelin, a leader in tire manufacturing, embarked on a journey to become a data-driven organization with Databricks, focusing on democratizing data across the company. This initiative aimed to unlock value in various business aspects, such as supply chain optimization and stock outage predictions, by providing employees with open and flexible access to actionable data. 

The transformation strategy rested on three pillars: creating a platform for secure data access, establishing governance for data accessibility and security, and viewing data as a consumable product. However, Michelin’s legacy on-premises platform was limited in openness and flexibility, leading to data silos and restricted tool access. To address these challenges, Michelin adopted the Databricks Lakehouse, breaking down silos and fostering significant team autonomy. 

An early application of this strategy was using AI to predict stock shortages, leveraging machine learning models on Databricks. This approach enabled real-time data streaming and analytics, supporting numerous use cases across the organization. The shift to Databricks not only facilitated diverse and scalable use cases but also fostered a collaborative community within Michelin, sharing data, code, and best practices. 

This initiative demonstrates Michelin’s commitment to innovation and their progress towards being a data-driven entity, showcasing the power of Databricks in transforming organizational data culture and operations. 

Biogen, a leader in neurological disease research, turned to Databricks for managing extensive genomics data sets. Confronted with the limitations of their on-premises data infrastructure, Biogen embraced Databricks for Genomics on AWS cloud, enabling them to process petabytes of data from the UK Biobank efficiently. This move drastically reduced data processing times, allowing the annotation of millions of genetic variants in just 15 minutes. 

The transition to Databricks simplified Biogen’s data analysis and infrastructure, enhancing their ability to explore genetic data at scale. Utilizing Databricks and Delta Lake, Biogen identified two new drug targets and gained valuable insights into neurodegenerative diseases like Alzheimer’s and Parkinson’s. The platform’s robust data partitioning and security features ensured the integrity of sensitive genetic data. 

Biogen’s adoption of Databricks marked a significant leap in their data-driven approach to medical research. This shift not only streamlined their operational processes but also accelerated the discovery of novel treatments, demonstrating the transformative power of cloud-based data analytics in the life sciences industry. 

Condé Nast, a global media powerhouse with brands like Vogue and The New Yorker, faced challenges in delivering personalized content due to fragmented data silos. Implementing Databricks, they streamlined their data processes, significantly accelerating decision-making and improving operational efficiency.  

This strategic shift enabled them to optimize their infrastructure, saving approximately $6 million in costs. Databricks provided a unified view of their audience, enhancing content personalization across their vast media landscape. 

The adoption of the Databricks Data Intelligence Platform marked a pivotal moment for Condé Nast. It allowed them to centralize and effectively utilize their data, leading to more consistent global reporting and insightful content strategies.  

The platform’s robust analytics and AI capabilities enabled them to tailor content experiences on a global scale, resulting in increased consumer engagement and loyalty. This transformative approach to data not only bolstered Condé Nast’s financial health but also reinforced their commitment to delivering compelling consumer experiences.