When I was little, my Dad used to keep a fuel logbook in his car. He would religiously write up his mileage and fuel purchase every time he would fill up. I inherited this habit, and I still have a collection of logbooks filed away. For tax purposes, of course. And nostalgia. 

Transcribe the data from one of these logbooks into a spreadsheet and it would only take up a few kilobytes on a computer. Compare this with the roughly 40 terabytes of data automated vehicles will generate and consume for every eight hours of driving, according to Intel CEO Brian Krzanich, speaking at the auto show’s technology pavilion, Automobility. Once there are millions of these vehicles on the road, we’re talking astronomical amounts of precision information, taken from sensors, cameras, GPS and other IoT devices. 

This is just one example of how data has grown exponentially – streams of data have become lakes, and lakes of data have become oceans.  

HPE has developed AI-powered systems to handle many of the challenges and problems that face large organisations in their digital transformation journey. The data centre and the cloud as it now exists have evolved from legacy storage requirements, but that is all about to change, with intelligent storage. 

What are these challenges? 

1. Space

Your organisation’s data is a resource that must be stored, and you have two choices: buy ever-increasing numbers of servers and storage devices, which occupy space and consume energy, or rent space on cloud-based servers.  

Most large organisations these days choose a hybrid approach, keeping certain data on-premises and using public and private cloud for large datasets, edge data, backup, disaster recovery and so on. This is not as simple as it sounds, because “most organisations don't really know what data they have, where it is or how much of it there is,” according to ESG senior analyst Christophe Bertrand, in an interview with TechTarget’s Alan R. Earls. 

HPE Intelligent Storage uses AI to actively manage and respond to its environment on premises and in the cloud, enabling resources to be appropriately available, optimised, and cost effective. We are not going to get away from needing to invest in hardware and cloud, but we can use it more effectively, and benefit from always-on availability of data. The cost advantage: HPE’s pay-per-use models minimise up-front costs, creating an on-demand experience in your own data centre. 

2. Legislation

Storage administration has become further complicated by legislation like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Legislation that is aimed at protecting the privacy of individuals puts the onus on organisations both to ensure that data can be made available and that it is kept secure.  

Organisations now need to invest in cyber insurance in case of damages arising out of malware and cyber-attacks or physical disaster. One of the provisions of the CCPA is the right of the individual to have their personal information deleted (with certain exceptions). This means specific data will need to be scraped, not only from the server but also the backups. 

The AI built into HPE Intelligent Storage handles privacy issues and can be updated to comply as legislation changes.

3. Complexity

Legacy data centres required specialised technical know-how to handle inescapably complex tasks, and to keep systems tuned and optimised. But this created opportunities for human error, which led to increasingly rigid infrastructure that prevented businesses from responding to IT needs that spanned disciplines.  

Modern systems with intelligent storage, built for digitally transformed organisations, allow developers to self-provision in minutes, using automated, policy-based infrastructure. DevOps can now use familiar tools to gain instant access to data and focus on innovation. 

4. Redundancy and Resiliency

Legacy systems of 'spinning rust' were not designed to handle AI. Yesterday, useful data was overlooked, simply because it was hidden. In the IoT era, it is estimated that 90% of data will be used only once. So, infrastructure requires intelligence built in to classify and organise data. 

At the mission-critical end of the scale, data has evolved to feature extreme redundancy, to minimise impacts when storage problems occur. At the same time, improvements in technology result in complex systems that capture increasing volumes of mission-critical data, meaning storage needs increase.  

A simple example: a medical practice that previously used digitally scanned X-rays invests in a high-resolution magnetic resonance scanner. These images give the doctors better insight, but the patient data now takes up incrementally more storage—data that needs to be available without delay, so cannot be archived. 

The new generation of mission-critical storage not only delivers 100% availability, but it also has the intelligence to predict and prevent problems in the stack before they occur. 

5. Speed of Access

Data is useful when it is stored, but most useful when speedily retrieved, organised and analysed. 

The challenge of storing increasing amounts of data puts a strain on conventional data centres, which become a growing problem for data centre managers. What is needed, and what HPE has developed, is an intelligent storage system that uses AI to analyse and organise data, learning from workflows and understanding what workloads need, adapting to changes in real time, and simplifying management and support.  

HPE Intelligent Data Platform uses AI to continuously learn and adapt to its hybrid cloud environment to better manage and serve data. It can be deployed as hardware on-premises, as a virtual appliance, or as a cloud service. HPE Intelligent Storage can move data where it needs to be and proactively optimise data through its lifecycle. It provides data protection and encryption to eliminate potential security threats and is sold in a pay-as-you-go model. 

In Conclusion 

For the enterprise that needs to develop AI- and ML-powered applications to analyse customer buying behaviour, predict supply and demand flows, and manage increased aspects of the business from purchase orders and logistics, to finance and even HR, access to the company’s data—and external sources of data—is critical. 

If we are to benefit from the innovative power of AI and ML, we need to embrace a fresh approach to storage, one that is future-proof, simple, agile, reliable, and saves time and money. 

And, by the way, I still have the habit of keeping a logbook—only now I also make notes in it about what I’ve been thinking about lately; a mini-journal, if you like. It’s been helpful to remain mindful, but also to remind myself of the exponential pace of change. 

Read more: 

www.cio.com/article/3600894/upgrading-mission-critical-storage-steer-clear-of-4-common-mistakes.html 

https://psnow.ext.hpe.com/ebook/dac6789f-2726-41b9-ab84-cbf40e64739c?section=multimedia 

Oreste Majeli - HPE Business Development Manager at CDW

For any enquiries contact: info@uk.cdw.com | 020 7791 6000