Businesses generate massive amounts of data every second in today’s fast-paced digital environment. This massive accumulation of data, which includes consumer information and product insights, is critical to a company’s growth and success. Nonetheless, organizations may need help managing this volume of data. Enter HPE DMF, the ultimate data management solution that enables businesses to manage their data infrastructure most straightforwardly and comprehensively as possible. Regardless of the size of your company, HPE DMF is designed to manage your data lifecycle and provide you with the skills and resources you need to compete in a data-driven future.
HPE DMF, a cutting-edge data management tool, is changing how businesses value their data assets. It boosts productivity and efficiency in all industries by intelligently automating workflow operations and improving access to critical data.
What is a Data Management Framework?
Organizations use the Data Management Framework, a comprehensive framework or structure, to manage and organize large amounts of data. It comprises procedures, regulations, technologies, and tools designed to assure secure data management, integration, and storage throughout its lifecycle.
A data management framework’s primary goal is to provide a logical plan for managing data that matches an organization’s goals and objectives. Businesses can improve the use of their data assets and speed up their data management operations by employing a framework.
Data governance must be included in a data management framework. To manage data entities, maintain regulatory compliance, explain data ownership, and create responsibility, rules, policies, and procedures must be established. Data governance creates a framework for data-related decision-making and maintains company-wide data standard compliance.
Data quality management is also part of a data management framework. The data’s authenticity, completeness, consistency, timeliness, and relevancy must be examined, improved, and maintained.
Migrating Data Between Systems for HPC
Controlling Data Storage and Protection Costs
The HPE Data Management Framework (HPE DMF) solution manages metadata and migrates data between storage assets based on workflow and administrator-defined criteria, allowing users to accept changing data values without limiting user access. Only the most critical or timely data is stored on higher performance, more expensive storage systems co-located with HPC/AI computing clusters, while less often accessed data is automatically transferred to more cost-effective, capacity-optimized storage media.
Designed for HPC
HPE DMF allows just-in-time data access for compute workloads and applications by integrating workflow management systems, HPC job schedulers, and other workflow tools. DMF can use these features to significantly boost storage utilization, decrease capital expenditures, and maintain the security and safety of critical data assets.
Built for Exascale but Deploys at Any Scale
The DMF v7 platform is built on a web-scale architecture designed to manage Exascale systems and the data volumes, and object counts that go with it. We have built it on a feature set that has grown over 20+ years of client production deployment. HPE DMF can help customers manage and protect data that exceeds 1 petabyte, and customers can scale the solution to meet their evolving data needs.
Streamlining Administrator Workloads
HPE DMF integrates into administrator and user workflows as a tool that streamlines data-related tasks and ensures adequate safeguarding of data, preventing loss due to silent data corruption, system failure, or operator error.
Native Filesystem Integration
The HPE DMF architecture integrates deeply with target filesystem ecosystems such as Lustre, IBM Spectrum Scale (GPFS), and HPE XFS. This integration notifies HPE DMF of events such as file and directory creation, deletion, modification, and storage space utilization, allowing the HPE DMF policy engine to perform any required data movement operations to protect, secure, and move data by administrator-defined rules.
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Continuous Backup and File Versioning
You can configure policies in HPE DMF v7 to migrate and store copies of new and updated files in the capacity tier at predetermined intervals or after predetermined intervals of file change inactivity. So it effectively implements a high-quality, granular backup strategy for a large disk. So using policy settings administrators can establish, DMF will automatically produce backup copies of files and metadata on a rolling basis. HPE DMF preserves both metadata and file data from previous versions of files for administrators to have a comprehensive history of the creation and content of filesystems and to be able to recover any or all of them. Administrators can restage entire filesystems or particular filesystem parts during staging using a point-in-time designation. For example, it can make it easier to repeat the results of specific job runs or confirm the correct operation of changed HPC algorithms.
Scalable and Extensible Metadata in Near Real Time
One of HPE DMF v7’s primary differentiators is scalable metadata management. DMF collects filesystem metadata changes from IBM Spectrum Scale, Lustre filesystems, and HPE XFS Linux® filesystems using the changelog stream. So it stores them as a collection of Apache Cassandra database tables. The filesystem reflection database contains the metadata about a specific filesystem and distributes across a cluster of DMF database nodes.
HPE DMF v7 collects and maintains all POSIX file and directory metadata, including extended attributes. Users can incorporate extra attributes into DMF metadata searches by directly adding them to files and directories. You can insert attributes as simple key-value pairs using standard POSIX tools like setfattr or setfacl. There is no need for any other databases. The system supports multiple characteristics, with key names that can be up to 250 characters long and values that can be up to 64 KB in size. Queries may employ and supply any user-defined extended attributes, SELinux labels and capabilities (security namespace), POSIX access control lists (system namespace), and trusted attributes.
To Conclude
We examined the world of data management frameworks and their importance in today’s data-driven culture. We now recognize that a data management framework is essential for businesses to handle massive amounts of data.
Data management frameworks provide organizations with a standardized approach to data management, making it simple to organize, store, retrieve, and analyze data. Because of the ever-increasing volume, diversity, and velocity of data generated, it is critical to have a solid structure in place.
Organizations may ensure data quality, integrity, security, and compliance by implementing a data management strategy. It enables them to set consistent data governance policies and procedures, ensuring that all firm personnel follows best practices.
Furthermore, a well-designed data management system supports firms in making data-driven decisions. They may use it to gain meaningful insights from their data, improving operational efficiency, customer satisfaction, and commercial success. In a world that is becoming increasingly digital, access to dependable and efficient ICT products is crucial. HPE’s servers, storage systems, and networking equipment are among the best available. ICT Distribution is the best option if you’re looking for a dependable distributor of HPE products in Cambodia.
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