The data you need – anytime, anywhere, anyhow

[EIC_Alliances]

By Brian Ng

Data is the life blood of today’s organizations. Businesses rely on data to drive top-line growth, reduce operating costs, improve customer experience, and ensure regulatory compliance, just to name a few. At the same time, the business data landscape has become more disparate and complex driven by the emerging trends of big data, IoT, cloud computing, machine learning and Artificial intelligence.

You know you have the data. The challenge is accessing it quickly and predictably across an increasingly complex data landscape. Multiple deployment models including on-premise and a variety of clouds, plus diverse geographic locations often translate to less than ideal retrieval of the data you need - when, where and how you need it.

That’s where a new solution from HPE – Hybrid Data Platform can make an impressive difference. Our new Big Data solution unifies your data landscape by offering a seamless global data fabric for all your application data needs – both analytical and operational. In the process, it delivers the performance, scalability, resiliency and cost-effectiveness that are paramount in today’s enterprise-grade data platforms.  

Anything goes

Hybrid Data Platform solution combines HPE’s Elastic Platform for Analytics infrastructure and MapR’s Converged Data Platform. The result is an enterprise data platform that bridges any organization’s data silos and enables modern data management with support for real-time streaming, NoSQL database, multi-tenancy, multi-temperature data tiering, high availability, all delivered with scalability, agility and flexibility that are unique in the industry.  Specific solution components include:

• MapR Converged Data Platform solves the crisis of data complexity resulting from workload-specific silos. Within a single platform, it converges the key technologies that make up a modern data architecture into a unified data landscape to deliver real-time insights.
• HPE Enterprise-Grade Big Data Solution independently scales compute and storage to allow superior performance, agility and manageability, thanks to its jointly-engineered density optimized infrastructure
• Proven services and solution methodology from HPE Pointnext and MapR ensure risk mitigation through a proven “advise-implement-support” approach

Any and every capability you need to unify your data landscape

Here’s how the Hybrid Data Platform achieves such impressive results:

• Simplified converged data landscape – MapR Converged Data Platform drastically simplifies data access and data management by presenting a single data landscape from disparate data via a unified global namespace construct.
• Higher performance Infrastructure optimized for Big Data – The solution offers two versions:  Standard Edition for a balanced compute and storage ratio; and Elastic Edition  that offers flexible compute and storage ratios to meet specific mixed-workload requirements.
• Density optimized infrastructure lowers TCO for large deployments, delivers better performance and reduces power and cooling cost by 50%.
• Multi-temperature data tiering – MapR storage rules and storage policy engine automatically move data to the most appropriate tier of storage to meet your performance and cost objectives.
• Services to ensure success – with Big Data Transformation Advisory Roadmap service, Enterprise design service, Installation and support services from HPE Pointnext, MapR and other partners, we ensure that solution delivers the ultimate business outcomes.

What’s in it for me?

Our Hybrid Data Platform offers capabilities available only from HPE and MapR, including:

• Analytics-ready data fabric Converged Data Platform provides a unified and fast access layer to any type of data—natively—all in a single global namespace. For example, an application running on the Converged Data Platform has native access to data stored as files, tables, documents, or event streams. MapR can manage data distributed across multiple private or public cloud data centers.  Data is efficiently tiered, mirrored, or streamed between physical locations using our patented real-time synchronous and asynchronous replication technologies.  The result is that analytical processing can be applied to distributed data in real-time regardless of where it physically lives.
• Support legacy and next-gen applications - The Hybrid Data Platform solution bridges the legacy and next-gen application data divide. Next-gen applications, ranging from machine learning, artificial intelligence to streaming analytics, are qualitatively different from traditional enterprise computing solutions. Unlike legacy business intelligence or batch reporting paradigms, next-gen applications go beyond the scope of generating insights into actions. Applying analytics to an operational process in real time requires the tight integration of different processing engines working together on a single platform.
• Enterprise-grade flexibility & resiliency - HPE Elastic Platform for Analytics infrastructure offers unmatched agility and scalability by strategically separating compute and storage in the asymmetric architecture. This offers the unique capability for organizations to optimize big data infrastructure for multi-tenant mixed-workload requirements. In additional, the Hybrid Data Platform is designed to support enterprise requirements for resiliency, security, and business continuity. The platform incorporates many self-tuning and self-healing capabilities for minimal administration.
• Intelligent edge computing - In addition to managing data in the data center, this solution also expands to encompass processing on edge devices. By applying analytics to data streams as they are being generated at the edge, organizations have real-time insight into a business processes as they happen.

Want to know anything else?

HPE will be attending and presenting at NY Strata this week. Our booth number is 551. The HPE presentation is titled “A comprehensive, enterprise-grade, open Hadoop solution from Hewlett Packard Enterprise” and will be presented on Thursday, September 28 at 2:05 p.m. Please join us. I look forward to seeing you there.