The time has come for intelligent data management
New and emerging technologies open up new insights from data, but the volume and complexity of data being generated creates challenges for IT leaders. How can organisations begin using AI and automation for intelligent data management?
In an uncertain and dynamic business landscape, success increasingly hinges on your organisation’s ability to extract value from data. Buried within your data are the insights required to:
- reach new customers
- develop and deliver new products
- operate more efficiently and effectively
- innovate within new business models
There is, however, another dynamic at play which is the rapid growth in hybrid cloud environments. These ecosystems of workloads deployed across public/private clouds and on-premises infrastructure are now creating the computing platform of the future.
Yet managing the flow of data across these hybrid cloud environments is an entirely new proposition for many IT leaders. It requires an intelligent data strategy that:
- accelerates application development and deployment
- harnesses the agility and innovation of clouds
- empowers innovators to unlock insights in real time
Harnessing the complexity of AI and automation
While AI and automation are certainly exciting technologies that have spread their tendrils into every aspect of our digital environment, the sheer volume of data these new capabilities are creating is also adding to the complexity of data management.
Traditional storage solutions simply haven’t kept up with this onslaught of AI and automation-driven data. Designed in a different era, legacy storage solutions slow your business down by forcing IT to spend most of their time reacting and troubleshooting performance issues and outages.
The problem will only compound exponentially when we begin to harness more data from IoT devices, social media platforms, and new applications. None of these workloads were designed with the traditional data centre in mind, and they each end up creating their own data silo in disparate parts of your hybrid cloud estate.
To begin operating effectively in this new environment, data management needs to do more than simply store and protect data. Intelligent data management should be using AI to manage itself while also:
- learning how you use data
- showing you where in your hybrid cloud data should be placed for best access and optimum efficiency
- helping your business direct digital investments
- enabling you to manage, secure, govern, and control data throughout its lifecycle
HPE’s Intelligent Data Platform collects data not just from storage devices, but from servers, VMs, network interfaces, and other infrastructure elements across the stack. It uses machine learning to develop models that constantly spot issues as they arise across the infrastructure stack. It also learns where data is created, stored, and accessed, so it can position it where it’s needed when it’s needed.
HPE’s Intelligent Data Platform streamlines data management to deliver incredible benefits such as:
- 79% lower storage operational expenses
- 30% savings in infrastructure costs to free up capital
- 20x reduction in cloud storage and transfer costs
- 86% of problems resolved before IT knows there’s an issue
- 75% performance improvement
- 40% reduction in power consumption
HPE is a trusted partner here to help you every step of the way and we understand the importance of data as the lifeblood of your business. As you address your data challenges to accelerate business recovery through these unprecedented times and speed business transformation, we’re here to help you solve the new challenges of a complex data-driven era.
Hewlett Packard Enterprise
Hewlett Packard Enterprise is the global edge-to-cloud Platform-as-a-Service company that helps organisations accelerate outcomes by unlocking value from all of their data, everywhere. At HPE, we advance the way you live and work by engineering experiences that unlock your full potential.
Data, AI, BI & ML
Artificial Intelligence and Machine Learning are the terms of computer science. Artificial Intelligence : The word Artificial Intelligence comprises of two words “Artificial” and “Intelligence”. Artificial refers to something which is made by human or non natural thing and Intelligence means ability to understand or think. There is a misconception that Artificial Intelligence is a system, but it is not a system. AI is implemented in the system. There can be so many definition of AI, one definition can be “It is the study of how to train the computers so that computers can do things which at present human can do better.” Therefore it is an intelligence where we want to add all the capabilities to machine that human contain. Machine Learning : Machine Learning is the learning in which machine can learn by its own without being explicitly programmed. It is an application of AI that provide system the ability to automatically learn and improve from experience. Here we can generate a program by integrating input and output of that program. One of the simple definition of the Machine Learning is “Machine Learning is said to learn from experience E w.r.t some class of task T and a performance measure P if learners performance at the task in the class as measured by P improves with experiences.”