HPE Ezmeral: Uncut
JoannStarke

EMA names HPE Ezmeral software Value Leader

HPE-Ezmeral-Receives-3-EMA-Awards.pngDigital transformation has completely changed data because it has proven that unstructured data is as important as transactional, structured data. When big data emerged in the late 2000s, analytic solutions revolved around two categories: data warehouses and data lakes. As data types began to change, the design center of the data warehouse made it necessary to restructure data ingestion before the data warehouse could analyze unstructured data. Data lakes suffered from poor performance along with databases that lacked enterprise-grade features and functions.[i]

Data continues to change, which means delivering on the promise of business insights requires a different solution: a solution that ingests and analyzes both structured and unstructured data on a single platform. 

The unified analytics warehouse

Enter a relatively new category in the data and analytics industry: the unified analytics warehouse. It’s unified because the single platform handles both structured and unstructured data. It’s a warehouse because it stores this multi-structured data in an organized and accessible way. 

For the past two years, Enterprise Management Associates has produced the EMA Radar Report,TM  which evaluates vendors across the three use cases driving the unification of data warehouses and data lakes. The 2021 version of the EMA Radar Report was just released and HPE Ezmeral has won Value Leader across the three use cases driving the unification of data warehouses and data lakes.

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For a proven and complete set of high-performance analytics and enterprise capabilities

 

 

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Multiple analytical use cases including multi-structured data and multi-latency analytics

 

 

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Maximum scalability and seamless leverage of existing and low-cost data storage options

 

 

HPE Overall Award Winner for Unified Analytics Warehouse

HPE is the overall winner for enterprise ready data lakes “because of its history delivering the most enterprise-ready, open-source data lake and analytics platform in the market.”[i]

To understand the significance of this award, it is important to understand the requirements of modern analytic solutions.  

Data Requirements

The modern enterprise captures unstructured web stream data, mobile app data, raw text from email, location data, and structured data from marketing and sales automation systems. Customers expect a unified analytics warehouse to ingest, combine, and analyze these data sets and streams.  

Based on an open platform, HPE Ezmeral Data Fabric ingests any data type and source (core, edge, cloud) utilizing a broad range of APIs, tools, and multiple ingest mechanisms. This allows traditional apps, analytic tools, and AI/ML apps to directly access data sets located on the same system.

Enterprise Requirements
Digital-first companies need to adhere to specific corporate and regulatory requirements.  

Built-in to HPE Ezmeral is platform-level orchestration and management, security, privacy, and data protection. It supports a broad ecosystem of open-source and independent software vendors to enable the developer and data scientist community.

Infrastructure Requirements
Unified analytics warehouses must be able to provide a rich and consistent set of analytical capabilities across all storage tiers.

HPE Ezmeral uncouples compute and storage to allow data movement across core, edge, cloud, and even cloud-to-cloud deployments. The single software-defined infrastructure delivers a consistent foundation for any workload or application. It can automate movement of data in and out of the file system and across storage tiers including object-based storage.

Cloud Requirements
EMA research indicates that 53% of all data is now in the cloud, making support for hybrid and multi-cloud support essential for a unified data analytics warehouse.

HPE Ezmeral provides hybrid and multi-cloud support. Built-in data management and security ensures that traditional, analytics, and AI workloads live under the same data management and security model, even if they are using different interfaces or protocols.

The unified analytics platform of HPE Ezmeral comes with a global data fabric and complete set of machine learning and analytic tools that support modern agile architectures from sandbox to production. The goal is to democratize data by eliminating data silos, enable hybrid/multi-cloud deployments, and simplify the lifecycle journey for data scientists and developers.

Data analytics have become core to any digital enterprise. Isn’t it time to unify your analytics program with “HPE’s unique combination of data fabric, open container platform and support for MLOps to add superior modern cloud capabilities to enterprise analytics and machine learning.”[ii]

Download the solution brief to get better acquainted with HPE Ezmeral Data Fabric. If your focus is Kubernetes, take HPE Ezmeral Container Platform for a test drive.  If machine learning is your focus right now, see how HPE Ezmeral MLOps can add DevOps speed and agility to your machine learning workflows.  

[i] Enterprise Management Associates, 2020

[ii] Enterprise Management Associates Radar Report, May 2021

[iii] Enterprise Management Associates Radar Report, May 2021

Joann Starke

Hewlett Packard Enterprise

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About the Author

JoannStarke

Joann’s domain knowledge and technical expertise have contributed to the development and marketing of cloud, analytics, and automation solutions. She holds a B.S. in marketing and computer science. Currently she is the subject matter expert for HPE Ezmeral Data Fabric.