11/18/2024 | Press release | Distributed by Public on 11/18/2024 08:25
As enterprises explore the potential of generative AI (GenAI), their data management strategies are becoming increasingly crucial. A recent MIT Technology Review Insights poll identified data quality, timeliness, governance and security as key barriers to effectively deploying and scaling AI. It's clear that while data is essential, having the right platform to organize and utilize it is vital.
This is why we're excited to announce the latest enhancements to the Dell Data Lakehouse in partnership with Starburst, as part of our AI-ready Data Platform and infrastructure capability with the Dell AI Factory, designed to empower both data engineers and IT admins.
Our platform seamlessly integrates with over 50 connectors out of the box and now supports custom Trino connectors for unique and proprietary data sources. With a single access point to these sources, the Dell Data Lakehouse facilitates ad-hoc and interactive analysis across distributed data silos, reducing data movement. From databases like Cassandra, MariaDB and Redis, to other sources such as Google Sheets and local files or even a proprietary application within your environment, users can now expand their access further into their distributed data silos.
We have always been committed to an open ecosystem including supporting Iceberg. Now we are extending our commitment by enabling external engines like Spark and Flink to securely access metadata in the Dell Data Lakehouse. This functionality allows for improved data discovery, processing and governance, available with optional security measures such as Transport Layer Security (TLS) and Kerberos.
Our enhanced support features allow admins to easily create and download a pre-compiled bundle of full-stack system logs. This improves the support experience by providing a comprehensive assessment of system state, enabling Dell support teams to quickly analyze and resolve issues.
Our latest update streamlines schema discovery, allowing you to automatically identify and incorporate data schemas with minimal manual intervention. This automation enhances efficiency and reduces the potential for human error in data integration. For example, when a logging process creates a new log file every hour, rolling over from the previous hour's log file, schema discovery locates the newly added files so that users in the Dell Data Lakehouse can query them.
We have developed a resource of articles, papers, and reference architectures to integrate the Dell Data Lakehouse with popular tools. This takes the guesswork out of setup and utilization, with topics ranging from change data capture using Debezium to enhanced data governance with the Privacera Platform. Our newest additions to the library are linked here for reference:
Optimize your Dell Data Lakehouse for improved AI outcomes and strategic insights with our Professional Services. Our experts will help implement your Data Lakehouse, onboard data sources, catalog metadata, and optimize data pipelines for streamlined operations.
For a virtual experience, visit the Dell Demo Center to interactively explore the Dell Data Lakehouse with curated labs. For a hands-on engagement, contact your Dell account executive to visit our Customer Solution Centers in Round Rock, Texas, and Cork, Ireland. Here, you can collaborate with experts for a design session and technical deep dive.
We're thrilled to announce an upcoming integration with Apache Spark, available in early 2025. This integration will enable you to process vast amounts of structured, semi-structured, and unstructured data for AI use cases in a unified environment. We invite you to continue exploring how the Dell Data Lakehouse can meet your specific needs and help you maximize your investment.