According to TechTarget, a recent IDC forecast revealed enterprises will create and capture an estimated 6.4 zettabytes of new data in 2020. This firehose of data is coming into the enterprise from a variety of sources: servers, smartphones, websites, social media networks, e-commerce platforms, and Internet of Things (IoT) devices. And the spigot is growing larger by the day.\nCan the typical enterprise handle this flood of data\u2014and if so, can they analyse it well enough to reap its benefits? Dana Gardner, Principal Analyst at Interarbor Solutions, discussed this issue with me in a recent BriefingsDirect podcast, How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-Cloud Data Fabric.\nBelow, I\u2019ve summarized key issues from the podcast.\nFlooded with data \nTwenty years ago, businesses were concerned about storing petabytes of data associated with their applications. Now with IoT, devices are generating zettabytes of data and sending this information back to the company. And all this data needs to be stored, managed, and analyzed.\nBusinesses need to get a handle on where the data is generated and how it will be stored and accessed\u2014a challenge that gets more urgent by the day. Complicating this process is the proliferation of data silos. Data is all over the place\u2014residing between multiple cloud providers as well as on-premise locations, creating data silo sprawl.\nLogjams hindering data access and management\nEnterprises face a huge challenge when it comes to data access\u2014in particular, ensuring secure data access at the edge, in a multitude of cloud, and at the core. And each cloud provider typically has their own access methodologies and software development kids (SDKs), contributing to the complexity of accessing the data.\nThe enterprise also needs to consider how a variety of different data types will be authorized and accessed. For example, an enterprise may have an object-based system with its own authorization and authentication techniques. Add to that an SQL database, a file-based workload, or a block-based workload\u2014each with different access requirements. Gaining a common, secure access layer that can access different types of data is essential to eliminating data sprawl.\nPart of solving the security access problem involves having a common application programming interface (API) across all data types. That\u2019s because standardized APIs let a variety of applications with multiple data types securely talk to each other. As businesses attempt to access and manage the tsunami of unstructured data from all corners of the enterprise, APIs are helping. A variety of business and development tools come into the enterprise via an API, cutting down on access methodologies, security domains, and data management.\nHaving commonality in an API layer lets the enterprise deploy anywhere\u2014providing the capability to go from the edge to dispersed data centers or the cloud. But it can also create challenges in terms of where the data lives, due to data gravity issues. And without portability of the APIs and data, enterprises will always see some lock in.\nThe bad news is that APIs only solve part of the problem. The enterprise has many challenges to consider when attempting end-to-end data management. The good news is that a platform and standards approach with a data fabric is the single best way to satisfy all the requirements an enterprise needs to store, manage, and analyze all data types from any source.\nHPE Ezmeral Data Fabric: A bridge across troubled waters\nHPE Ezmeral Data Fabric is such a solution, providing enterprise-wide, global access to data, bridging seamlessly from on-premises to the edge, or to one or more clouds. This unified platform supports a variety of data from large to small, structured and unstructured, as well as time series and sensor data\u2014essentially every data type from any data source. This capability is a big driver for businesses. They want a common, secure access layer that can access different types of data.\nAs covered previously, another factor is having a common API access layer, which helps reduce management and security costs with a distributed site for your application data needs. The HPE Ezmeral Data Fabric provides the same security domain across all deployments. That means enterprises can have one web-based UI (or one REST API call) to manage different data types and their associated security controls.\nAnother key benefit is that the HPE Ezmeral Data Fabric can be deployed across any x86 system, which protects you from data lock-in with a particular cloud vendor. Also, with more than 10 different API access points, HPE Ezmeral Data Fabric allows for multi-data access based on the applications needs. The platform includes everything from storing data into files to storing data in blocks. It also helps run diverse computational tools and open source frameworks, without requiring multiple clusters or silos.\nOne of the greatest features in the platform, Global Namespace, helps reduce the time it takes someone to find the data they need for the project they are working on. For example, a lawyer preparing a case for discovery can merely double click on a data fabric drive and can see all the data globally using the same security model. Another feature is multi-temperature storage, which decreases deployment costs by allowing you to tier data off to a cheaper and deeper storage solution, all while still managing the data in one location.\nThese features make the HPE Ezmeral Data Fabric simple for everyone in the enterprise to use. They gain a common data fabric, common security layer, and common API layer.\nThe unique capabilities in the HPE Ezmeral Data Fabric also make it ideal as the persistent storage layer of the recently announced\u00a0HPE Container Platform. Enterprises can enjoy full end-to-end management of their containers, and built-in enterprise grade persistent storage, resulting in management and data portability for containerized workloads.\nOpening the floodgates: It\u2019s all about the data\nThe first step in discovering insights from data is being able to access and use the data. When an enterprise can improve automating data management across multiple deployments\u2014managing it, monitoring it, keeping it secure\u2014then they\u2019ve opened the floodgates. Software developers and data scientists can now focus on actual use cases.\nA detailed report published by IDC demonstrates how impactful this process can be. Analysts interviewed long-time users of HPE Ezmeral Data Fabric (formerly called MapR) to discover the impact of this technology on business outcomes. The enterprise organizations interviewed are substantial businesses across a range of sectors with multi-billion-dollar revenues. The HPE Ezmeral Data Fabric (formerly called MapR), had a substantial positive impact on several aspects of large-scale data usage and related business processes. The report says users achieved an estimated\u00a0567% five-year ROI\u00a0with an eleven-month payback period.\nListen to the complete podcast, How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-Cloud Data Fabric.\n____________________________________\nAbout Chad Smykay\n\nChad Smykay, Field CTO, HPE Ezmeral Data Fabric, has extensive background in operations with his time at USAA as well as helping to build many shared services solutions at Rackspace, a world class support organization. He has helped implement many production big data\/data lake solutions. As an earlier adopter of Kubernetes in the application space coupled with data analytics use cases, he brings a breadth of background in the application modernization space for business use cases.