Empower yourself with data analytics capabilities that combine the functionality of a data warehouse with the flexibility of a data lake, applicable to all your data.
In light of the ongoing expansion of data in terms of volume, diversity, and speed, the demand for a scalable, efficient, and dependable table format has become ever more pressing. Apache Iceberg represents not just an alternative to Hive but rather ...
In response to the need for accelerated data insights, expanded analytic capabilities, and cost containment, NCR opted for Dremio to facilitate the modernization of its data analytics infrastructure.
After implementing Dremio, we observed a remarkable up to 10x acceleration in our queries on petabytes of data," reveals Vishnu Vardhan, TransUnion's Head of Data Science. The most significant advantage is that we no longer need to create duplicates ...
Product analytics presents a transformative opportunity for companies to enhance the customer experience and gain proactive insights into customer behavior. This personalized understanding enables companies to customize their product offerings, deliv...
If you're planning to build your data lakehouse using Apache Iceberg to benefit from its features, performance, and extensive ecosystem of compatible platforms and tools, you'll need to transition your existing Hive tables to Iceberg. Iceberg provide...
The majority of businesses employ Hadoop for handling large-scale data analytics. Nevertheless, on-site Hadoop installations have often fallen short of providing the anticipated business benefits. Over time, the considerable operational expenses and ...
Each organization strives to provide its business users with data and insights, but they often face challenges such as data isolation, difficulties in data discovery, and slow data retrieval. Dremio addresses these issues by enabling data teams to se...
Read this case study to discover why Memorial Sloan Kettering Cancer Center (MSK) chose Dremio’s data lakehouse platform to simplify data access and unify cancer research data for end users.
Read this MIT Technology Review, produced in association with Dremio, to learn more about open data lakehouse architectures and self-service analytics capabilities.
Learn how Amazon's team developed a new analytics architecture with Dremio to simplify ETL processes, accelerate queries, and provide analytics on complete and unified view of the data.
