Data Infrastructure
What is Data Infrastructure?
Data infrastructure refers to the various components—including hardware, software, networking, services, policies, and more—that enable data consumption, storage, and sharing. Having the right data infrastructure strategy is critical for organizations seeking to undertake data-driven digital transformation.
What role does data infrastructure play in an organization?
Data infrastructure provides the foundation for an organization to create, manage, use, and secure its data. One of its most critical roles is to ensure that the right data can get to the right users or systems at the right time to make effective data-driven decisions. To meet this goal, an organization must have a solid data infrastructure strategy in place to maintain data flows, protect data quality, minimize redundant data, and prevent crucial data from being isolated into silos.
Why has data infrastructure gotten more complicated?
Recent technology advances have added complexity to data infrastructures. Where previously enterprises may have only needed to concern themselves with their on-premises data center infrastructure, the development of the Internet of Things (IoT), growth at the edge, and the introduction of various cloud computing platforms have extended the data infrastructure landscape and increased the amount of data such infrastructure must support.
How can tools help manage data infrastructure?
As the landscape has expanded, a growing number of tools and platforms have been introduced into the market to oversee various aspects of data infrastructure. While these tools may address specific elements of data infrastructure, having to oversee and manage multiple solutions can also create additional complexity and place additional burdens on IT teams. Consolidation and standardization throughout the data infrastructure stack provides enterprises with scalable access to data across teams and functions.
What are the elements of data infrastructure?
Data infrastructure includes the physical infrastructure of the data center facility, the information infrastructure that encompasses the systems and environments that create and support data, and the business infrastructure of high-level business systems.
Exactly what elements are considered part of the data infrastructure can differ from organization to organization, and even from person to person within an organization. Some of the possibilities include:
Physical infrastructure
- Storage hardware
- Processing hardware
- I/O networks
- Data center facilities (including power, rack space, and network connectivity)
Information infrastructure
- Business applications
- Data repositories (including databases, data warehouses, data lakes, data marts, and data lakehouses)
- Virtualization systems
- Cloud resources and services [including Software as a Service (SaaS) applications, virtual services]
Business infrastructure
- Business intelligence (BI) systems
- Analytics tools [including Big Data, artificial intelligence (AI), and machine learning (ML) systems]
Across these elements are all the personnel, services, policies, and processes involved in creating, moving, protecting, processing, securing, and serving data throughout the organization, from core to edge to cloud.
Why does data infrastructure matter?
Organizations realize that data is a key competitive advantage, and they are increasingly seeking to unlock the value of their data. As the amount of data available within the enterprise is skyrocketing, from edge to cloud, having a well-thought-out data infrastructure strategy is vital to manage costs while meeting the needs of the business.
One of the fundamental issues in any digital transformation project is making sure the organization’s data infrastructure is properly aligned with their desired future state. Balancing storage and analytics demands with the costs of each possible solution is a significant consideration. Getting the infrastructure strategy wrong can inhibit business agility, preventing the organization from being able to capitalize on newly emerging business opportunities and meet new customer demands. If data is trapped in silos and inaccessible to the users or systems that need it, the ability to make effective decisions is hindered, increasing risk and costs. And if the correct security and governance controls are not applied consistently enterprise-wide, it opens the organization up to potential regulatory actions and damage to its corporate reputation.
Traditional infrastructure
Traditional infrastructure has each element of the overall solution individually selected and purchased. While this option offers the greatest degree of choice and customization to an organization’s specific needs, purchasing and managing this type of infrastructure is often complex.
Converged infrastructure
Converged infrastructure is a model in which the infrastructure is purchased as a complete system from a single vendor, with all the hardware and software components validated to work together.
Hyperconverged infrastructure
Hyperconverged infrastructure (HCI) is a software-defined approach designed to make the infrastructure more flexible and manageable. It combines all of an organization’s storage, compute, networking, and virtualization into a single integrated solution.
The cloud
The cloud makes many elements of data infrastructure available to users over the Internet. It provides access to on-demand system resources without the need to maintain the physical infrastructure elements directly.
HPE solutions for data infrastructure
HPE storage has long been a proven leader in enterprise storage; we have now reimagined data and infrastructure management for a new data experience called Unified DataOps.
This approach creates value for everyone from IT managers to data innovators. Instead of tuning and maintaining infrastructure, IT managers can deploy cloud services with instant application provisioning. Developers and data scientists get streamlined access on demand rather than having to wait to access the data they need. And data managers can set protection policies with a single click wherever data lives, from edge to cloud.
The Unified DataOps approach embraces data, cloud, and AI to reimagine the data experience through data-centric policies and automation, cloud-native control and operations, and AI-driven insights and intelligence. Holistic data-centric policies and automation collapse silos and unify workflows across the data lifecycle. By abstracting data and infrastructure control away from physical infrastructure, organizations can manage their workflows from the cloud and orchestrate them wherever data lives—and gain faster access to features through cloud services. And with AI deeply embedded into data operations, disruptions can be avoided and app performance can be improved.
Unified DataOps with the Intelligent Data Platform delivers a single data platform that connects applications to infrastructure, innovators to data, and automation to policies in a seamless, unified cloud experience wherever data lives.
Bringing together the Data Services Cloud Console, HPE Alletra, and HPE InfoSight—delivered as a service via the HPE GreenLake edge-to-cloud platform—the Intelligent Data Platform uniquely powers a new data experience that collapses silos across people, process, and technology to unleash data, agility, and innovation for organizations.