Data / Technology / Sponsored / Contributed

7 Ways a Data Fabric Helps Unify Data Management

2 Jun 2021 9:00am, by

Everything about data has changed. A few years ago, data was structured and resided within your data center. Now it’s distributed, diverse and growing 26% each year. The tools and technologies used to engineer, govern, protect and consume data are also changing. The roles consuming data are just as diverse, ranging from front office to the back office, from the assembly line to the boardroom. In response to these changes, organizations are looking for a modern approach to data management, particularly one that includes a modern data fabric.

What Is a Data Fabric? 

Joann Starke
Joann is a senior product marketing engineer at HPE. She holds a B.S. degree in marketing and computer science, having graduated with honors in the field.

Just as a loom weaves multiple threads to form fabric, a data fabric weaves data into a single repository, enabling end-to-end access and management of data activities. Creating a single source of data truth is important to developers, data scientists and business teams to increase their confidence in the data’s accuracy, which in turn allows for clearer business decisions.

As enterprises grow, so do the number of applications that collect and place data into individual silos, making it stagnant and inaccessible. Technology, such as data centers and cloud, contribute to this isolation. If data is important to your organization, then you already know that siloing results in a fragmented network that is far from unified.

Data management teams are under constant pressure to provide faster access to integrated data across an increasingly distributed landscape. The popularity of data fabric technology as a data management concept is in direct response to the longstanding data integration challenges that data and analytics leaders face in today’s highly diverse data landscape. These challenges include:

  • Multiple data sources and types
  • Soaring number of data silos that inhibit data integration
  • Rising demand for real-time or event-driven data-sharing for business-led data modeling
  • A real need to inform and automate data integration and management

Seven Ways Data Fabric Enables DataOps 

Data fabrics enable processing, analysis, global management and storage across any data type or source. Then they enable applications and tools to access common datasets through a broad set of interfaces such as REST, NFS and HDFS, languages and tools. When evaluating solutions, look for the following seven key features identified by Forrester to support DataOps initiatives:

  1. Global data management that integrates various data sources such as log files, streams, and CRM to deliver a comprehensive view and consistent access, configuration, security, data security, protection and monitoring across all cluster deployments.
  2. Delivers an identical infrastructure through a global namespace, allowing applications to use the same processes, tools and techniques.
  3. Allows legacy applications to work directly with modern analytics and AI apps, through standard interfaces and APIs, to enable safe sharing of common datasets on the same system.
  4. Automated mirroring an exact copy of the source data to a remote cluster without first having to copy data before it can be accessed.
  5. Object tiering to reduce storage costs, by compressing infrequently used data before moving it to other storage, such as cloud object storage.
  6. Built-in security that contains the four pillars of security — authentication, authorization, auditing and data encryption — both at rest and in flight.
  7. A data fabric that learns and automatically identifies data patterns and connects data to support adaptive intelligence, drives actionable insights and provides automatic recommendations and alerts

Delivering Value Today 

For over four years the product I work on, HPE Ezmeral Data Fabric, has enabled data scientists, developers and administrators within organizations to apply DataOps techniques through a software-defined platform and global namespace. This solution ingests data from anywhere, then automates key processes to increase confidence in analytic data.

Check out our eBook, Simplify Real-Time Data Access, for insights on how to unify and simplify data management. It includes two customer case studies, outlining how they have accelerated their digital initiatives.

Feature image via Pixabay.

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