Every enterprise is under a mandate to be a data-first company by leveraging their data to compete on analytics.
As a result, analytics, AI, and machine learning (ML) have become core technologies for any data-first journey. However, many of these initiatives are failing.
I’m sure you know or are experiencing the challenges responsible for these failures as well as the complexity they bring to every organization:
● Exploding data volumes across a variety of types and formats
● Rapid importance and growth in streaming data
● Capturing data from new and emerging technologies then processing it in real-time, i.e., edge
These challenges are hindering data science and analytic teams because each of these locations has become an island of information that requires negotiation with each site owner before data can be accessed. And these information islands are growing in number making data unification and normalization a time-consuming task.
Find, interpret, and use data from anywhere
The answer is data fabric, an integrated layer (fabric) of data and connecting processes. It accelerates insights by automating ingestion, curation, discovery, preparation, and integration across islands of data. Data fabric is not a new technology but one that has become more important as organizations’ look to compete using analytics. Here are some things you should look for in a data fabric. A single solution should:
* Reduce the risk and costs associated with large analytic systems by integrating the components needed to access, land, process, and index data securely across multiple physical locations
* Increase productivity of data engineers and analysts by aggregating different types, formats, and systems into a single logical data store
* Simplify data access by connecting multiple clusters and physical locations through a single global namespace
* Reduce platform risk by replacing multiple tools and unique security integrations with a single enterprise security integration
An example of such a solution is the HPE Ezmeral Data Fabric, which enables customers to deploy a hybrid data backbone to provide frictionless access to their global enterprise. This single platform scales to exabyte levels, is optimized for high performance read/writes of both tiny and jumbo objects and increases productivity of data teams with a single logical data plane accessed globally through a single namespace. The built-in ecosystem provides data engineers and analysts with a choice of the most popular tools from the Apache Spark community. Support for a wide range of industry standard APIs enables data to be integrated into other systems, such as Apache Hadoop systems.
Integrate your islands of information
A data fabric replaces the complexity, risk, and cost associated with managing multiple unique tools and security systems with a single security integration that spans across on premises, multiple clouds, and edge. Industry analysts agree that becoming a data-first organization requires data fabric technology to provide a unified data layer to data science teams. It provides data consumers with consistent, governed, and performance-optimized data views, no matter where the data or user are located. The right data fabric can simplify all the capabilities your business needs to compete using analytics.
About the author
Joann Starke is senior product marketing engineer at HPE Ezmeral Software. 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 and HPE Ezmeral Unified Analytics.
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