Historically, Snowflake customers in the healthcare and life sciences space have faced something of an ultimatum when it came to how they stored and utilized their large volumes of data.
These organizations had to choose between, on one hand, storing their data in the Snowflake AI Data Cloud and benefitting from its compression, or, on the other hand, using cloud storage where they could define tiering and optimize their storage pricing.
Apache Iceberg, with its high-performance table format, is transforming how healthcare and other life sciences fields manage—or even think about—this kind of large-scale datasets. By blending the cost-effectiveness of an external table with the performance you’d expect from data stored within Snowflake proper, Iceberg tables are cutting a path toward a future where organizations no longer need to compromise.
Because Iceberg tables exist outside of any given cloud platform and its proprietary ecosystem, meanwhile, these tables are also opening a new path to vendor-agnostic multi-cloud data architectures.
Health Tech Firms at the Forefront of Adoption
Health tech companies are leading the change in adopting Apache Iceberg due to their unique data management needs and the massive volumes of data they handle. These organizations deal with a diverse range of data types from numerous sources, making efficient data management crucial, but also cause this task to be complicated and expensive.
Apache Iceberg provides a solution by enabling effective handling of large datasets while maintaining data integrity and performance. Since they support cost-effective storage strategies, Iceberg gives health tech firms the chance to optimize cloud storage expenses through tiered storage options.
This optimization is vital for companies managing large datasets, as it can lead to a significant amount of cost savings. Yet, cutting the cost of data management is only a factor in why health tech companies are leveraging Apache Iceberg. Thanks to their ability to facilitate seamless data integration across different storage systems and platforms, Iceberg is able to address the complexity of managing diverse data types.
This ensures that health tech companies can maintain high standards of data security and compliance while streamlining their data management processes. By adopting Apache Iceberg, these firms can enhance their data architectures, support their data-driven initiatives, and remain at the forefront of innovation in the healthcare sector.
How Iceberg Supports Multi-Cloud Data Management
In the modern cloud technology landscape, vendor lock-in is a significant concern for organizations looking to future-proof their data strategies, and within the health sector, where providers often rely on different cloud services for specialized functions, multi-cloud storage is an essential tool for any company to have under their belt.
Apache Iceberg is central to this strategy by offering a consistent data format that is accessible across multiple cloud environments. This flexibility allows healthcare organizations to select the best tools and services from different providers without data compatibility issues. For instance, they might use Azure for electronic health records (EHRs), AWS for machine learning applications, and Google Cloud for research. However, integrating these disparate systems has traditionally required complex and costly ETL (extract, transform, load) processes.
Apache Iceberg eliminates these barriers that could be costing healthcare organizations time and money by creating a consistent, universally supported table format. This enables providers to seamlessly integrate data across multiple cloud platforms, as well as mixing and matching the best tools each cloud provider offers, all without being tied to any single provider.
Thanks to their flexible, vendor-neutral data systems optimizing resource utilization and enhancing overall data management capabilities, Iceberg allows healthcare organizations to create robust and scalable data architectures tailored to their specific needs. Moreover, Iceberg’s ability to support data integration across cloud platforms ensures that healthcare data remains cohesive and secure. This is particularly important for maintaining data integrity and compliance with healthcare regulations.
Tackling Healthcare Data Management Challenges
Healthcare organizations frequently contend with data silos, where vital information is fragmented across various departments or platforms, obstructing the comprehensive analysis needed for informed decision-making and coming to reliable conclusions. Apache Iceberg mitigates these issues by serving as a unified data layer in order to facilitate seamless data integration across various platforms, ensuring accessibility to consistent and accurate data.
Iceberg’s reliability is crucial for enhancing data accuracy, particularly in applications such as medical image classification, or integrating pharmacy supply chain data with patient records to identify trends for when certain medications should be in surplus. By improving the accuracy and efficiency of organizations’ data management processes, Apache Iceberg enables healthcare organizations to boost their operational effectiveness, leading to better resource utilization and improved patient care outcomes.
By adopting Apache Iceberg into their multi-cloud data management programs, healthcare organizations can effectively address challenges with their current data management systems, streamline operations, and enhance their data-driven capabilities.
The Metadata Quandery
This new era in multi-cloud data strategies is not without its challenges, of course. While Iceberg provides greater flexibility in terms of where and how data is stored, it also introduces complexities in cataloging and metadata management.
Unlike proprietary platforms like Snowflake, where data and metadata are tightly integrated and managed within the platform, Iceberg’s metadata needs to be tracked and maintained through a separate metadata catalog. Organizations subsequently face a critical decision: which tool will they use to handle that cataloging?
For organizations moving to a multi-cloud architecture, this becomes something of a wild west scenario. While there is no shortage of cataloging options available from the major cloud platforms, this plethora of options means that there is also no one-size-fits-all solution to be had. In other words, the flexibility of Iceberg opens a door to a proliferation of catalogs and patterns that will need to be stress-tested in real time as enterprises weigh their options.
Rethinking Cloud Data Architecture with Apache Iceberg and Hakkōda
By overcoming the long-standing challenges of performance, cost, and data silos, Apache Iceberg is enabling healthcare and life sciences organizations to fully harness the power of multi-cloud architectures, optimize storage costs, and maintain high standards of security and compliance. Whether through its seamless integration with Snowflake, its ability to support complex multi-cloud environments, or its role in ensuring data integrity, Iceberg is paving the way for more agile, future-proof data strategies in the healthcare sector.
At Hakkoda, we understand the complexities of healthcare data management and the critical need for solutions that deliver both performance and cost savings. Our team of data experts is ready to help you navigate the evolving landscape of cloud storage and analytics with advanced strategies tailored to your unique needs. From implementing Apache Iceberg to optimizing your multi-cloud architecture, we are committed to helping you streamline operations, improve decision-making, and unlock the full potential of your data.
Ready to break free of vendor lock-ins and build the data architecture that will propel your enterprise toward its next innovation? Talk to one of our experts today.
