In today’s competitive business landscape, organizations are constantly seeking ways to optimize their data infrastructure while reducing costs. For many Fortune 500 companies, the migration from traditional cloud platforms like Azure and Google Cloud Platform (GCP) to Databricks has emerged as a strategic move that delivers substantial cost savings, improved performance, and enhanced AI capabilities. This article explores how leading enterprises are achieving remarkable returns on investment by transitioning to the Databricks Data Intelligence Platform.
Databricks has positioned itself as more than just another data platform. It offers a unified approach to data engineering, analytics, and AI that addresses the fundamental challenges faced by large enterprises:
According to a Forrester Consulting study , organizations deploying Databricks realize nearly $29 million in total economic benefits and a return on investment of 417% over a three-year period. Even more impressive, the Databricks platform typically pays for itself in less than six months.
Alinta Energy, a major electricity generator and retailer, provides a compelling example of the benefits of migrating from Azure to Databricks. The company had been using Azure Synapse, Microsoft’s all-in-one data platform and analytics services package, to run data transformation, querying, and processing, as well as to serve data to users.
Under the leadership of Lead Data Engineer Jake Roussis, Alinta Energy implemented a concerted re-platforming effort that aligned with their engineering strategy to improve cost, observability, reliability, and performance. The results were impressive:
Beyond cost savings, Alinta Energy experienced significant performance improvements. A calculator used for electricity “pricing variation events” now requires “less than 15 minutes” runtime, compared to over an hour previously. The company also noted better alerting capabilities in Databricks compared to Azure, with alerts routed to their PagerDuty IT operations platform.
“There’s only a small portion [of our data architecture] that’s not [Databricks], and we’re doing everything that we can to move it into [Databricks],” Roussis stated, highlighting the company’s commitment to the platform.1
Alinta Energy is not alone in realizing substantial benefits from migrating to Databricks. Numerous Fortune 500 companies have reported similar success stories:
Block standardized its data infrastructure using the Databricks Data Intelligence Platform, paving the way for GenAI innovations. By leveraging Databricks’ capabilities, new businesses can now onboard faster to the Square platform using AI-powered setup and data import automation.
The financial impact has been substantial: Block achieved a 12x reduction in computing costs, allowing the company to continue redefining financial services in the 21st century while maintaining cost efficiency.2
The popular gaming platform reduced processing time by 66% with the move to Databricks, enabling the company to use data and AI to enhance the gaming experience. This performance improvement translates directly to better user experiences and more efficient operations.3
The retail giant built a self-service data platform on Databricks to allow its engineers to build pipelines that support data science and AI/ML applications. With the Data Intelligence Platform as a unified data and analytics foundation, the company can analyze promotions and sales performance at scale, across different customer segments, in real-time to make more informed decisions.
Ahold Delhaize USA also uses the platform to support customer personalization, loyalty programs, food waste reduction, environmental initiatives, logistics, forecasting, and inventory management.4
A multinational engineering and technology company with over 130 years of market presence and 400,000+ employees migrated from MS SQL Server repositories to Azure Synapse, and then to Databricks to ensure efficient resource utilization and reduce overall costs.
The migration resulted in:
The energy giant shared their experiences in overcoming initial hurdles in data strategy and governance by using Unity Catalog and a business-owned data product approach. Shell leveraged Databricks for analytics, PowerBI, ML models, and AI for Data Governance, delivering innovative energy solutions for a cleaner world.6
The telecommunications leader uses Databricks to streamline and accelerate new data products, from automated pipelining with Delta Live Tables to serverless Databricks SQL warehouses and AI/ML use cases. AT&T described how it met stringent security and regulatory requirements while adopting the Databricks serverless platform, starting with serverless SQL warehouses.7
While direct cost savings are significant, the financial benefits of migrating to Databricks extend far beyond reduced infrastructure expenses. According to Nucleus Research , Databricks Lakehouse customers achieve an average ROI of 482% over a three-year period, with an average payback period of just 4.1 months.
The Forrester Total Economic Impact study identified several key areas where organizations realize financial benefits:
Databricks customers achieved a 5% increase in revenues by enabling data science teams to build more—and better—ML models, faster. Additionally, Databricks democratized data access across organizations, leading to new users creating diverse sets of analytics products such as recommendation engines, pricing optimizations, and predictive maintenance models.
As Bryn Clark, Data Scientist at Nationwide, noted: “With Databricks, we are able to train models against all our data more quickly, resulting in more accurate pricing predictions that have had a material impact on revenue.”8
Organizations reported improved productivity of data scientists and data engineers by 25% and 20%, respectively. The improved data management capabilities enabled data teams to spend less time searching for and cleaning data, less time creating and maintaining ETL pipelines, and more time building analytics and ML models to drive meaningful business outcomes.
“Being on the Databricks platform has allowed our team of data scientists to make huge strides in setting aside all those configuration headaches that we were faced with. It’s dramatically improved our productivity,” said Josh McNutt, SVP of Data Strategy and Consumer Analytics at Showtime.9
By migrating to Databricks, organizations were able to retire on-premises infrastructure and cancel legacy software licenses, resulting in millions of dollars of savings. Additionally, the management of the Databricks platform proved substantially easier than legacy environments, enabling companies to reallocate IT resources to higher-value projects and reduce operational costs.
Comcast reported that “Databricks has enabled Comcast to process petabytes of data while reducing compute costs by 10x. Teams can spend more time on analytics and less time on infrastructure management.”10
Beyond cost savings and performance improvements, Databricks provides Fortune 500 companies with advanced AI capabilities that drive innovation and competitive advantage:
Alinta Energy implemented AI/BI Genie, Databricks’ generative AI feature, to enable business teams to interact with data using natural language. This capability has been used to present information about retail customers to call center agents, helping them understand what customers might be calling about.11
Northwestern Mutual implemented a RAG system to enhance customer service efficiency. The insurance provider built a robust data pipeline using Databricks for indexing content and collecting user feedback.12
Doordash and Databricks collaborated to accelerate the adoption of Databricks for ML and streaming use cases, helping accelerate the adoption of Databricks for workloads that perform more optimally with Delta and Spark compute.13
For C-level executives considering a migration to Databricks, several strategic considerations should guide the decision-making process:
While the upfront costs of migration require investment, the long-term TCO reduction typically justifies the transition. CFOs should consider:
CIOs should evaluate current performance bottlenecks and determine how Databricks’ architecture can address these challenges:
The migration strategy should account for:
Most successful migrations follow a phased approach:
The migration from traditional cloud platforms to Databricks represents more than a technical decision—it’s a strategic business move that can significantly impact an organization’s bottom line and competitive positioning. The documented success of Fortune 500 companies across industries demonstrates that the benefits extend beyond simple cost reduction to encompass improved performance, enhanced productivity, and new AI-driven capabilities.
For CIOs and CFOs evaluating their data infrastructure strategies, the compelling ROI metrics—417% return over three years, payback periods of less than six months, and cost reductions of up to 12x—make a strong case for considering Databricks as a cornerstone of their data and AI strategy.
As data volumes continue to grow exponentially and AI becomes increasingly central to business operations, the advantages of a unified, cost-efficient, and high-performance data platform like Databricks will likely become even more pronounced. The question for Fortune 500 executives is no longer whether to optimize their data infrastructure, but how quickly they can implement a solution that delivers both immediate cost savings and long-term strategic value.
