Machine Learning to Hybrid Cloud: 6 Key Trends Shaping Data Management

Image sourced from Capacity Media.

Digital transformation and the increase in remote working means that businesses are faced with unparalleled levels of data being generated daily.

Businesses not only have to manage that data, but they also have to address the fact that much of the data created by enterprise systems is ultimately valueless.

In fact, it’s estimated that 90% of data is never accessed again 90 days after it is stored. Not only does this unnecessary data fill already-saturated storage systems, but it also becomes a liability requiring ongoing management.

The increased pace of the generation of new business information means that data management has become a core priority for IT and non-technical executives alike, and the data management decisions that companies make can have sweeping impacts on everything from growth capability, profitability and organisational sustainability.

Here are 6 key trends that are shaping Data Management:

1. The Continued Rise of Digital Transformation

Throughout the pandemic, many businesses have seen how digital transformation has enabled remote work and decentralized offices.

With a large proportion of work now done in virtual environments, the need for companies to digitise their data management processes has accelerated. Organisations face the continued challenge of implementing a cohesive data management system to analyse and process data more efficiently, while still allowing it to be accessible and actionable across all locations.

Data is no longer just highly structured information pulled from a limited number of sources.

Instead, data now comes in a variety of forms, and from a range of sources, placing increased importance on the way it is handled and stored. This has brought increased demand for platforms, tools, and flash array technology to provide secure, flexible and agile data management.

  1. 5G Meets Business

The availability of 5G networking is about to become crucial for many different business operations. With the inherent growth of IoT devices leveraging 5G, the velocity of data being created and analysed only increases the need for high-performance, low-latency storage in edge locations.

5G will act as the catalyst for developing more advanced, data-hungry applications, which will enable enterprise systems to stay connected while handling data at lightning-fast speeds. In turn, enterprise business models will need to adapt with it, especially as it relates to the services delivered to end-users and customers.

Robust, secure and highly efficient data management solutions will therefore be a central component for capitalizing on the enormous potential that a 5G network offers to business operations.

  1. AI Enables Greater Automation and Prediction in Data Management

Storage vendors are increasingly turning to AI and machine learning to build automated capabilities into enterprise data management systems.

This could include anything from greater efficiency when monitoring capacity requirements to using your pre-existing data for predictive analytics, preventing issues from ever materializing.

Going forward, it’s likely that businesses will continue to reduce human involvement throughout data infrastructure management, instead businesses will place added responsibility on intelligent software solutions to handle these issues.

Your data centre should be seen as the heart of your AI data pipeline, and therefore it demands high I/O performance. From pre-processing where the value lies in feeding data to the neural networks for model training, All-Flash Arrays can remove performance bottlenecks and accelerate AI workloads simply.

Through effectively leveraging AI capabilities, businesses can greatly improve the efficiency of their data management, especially in areas such as oversight, performance and security.

With the next generation of applications and digital transformation projects already being enacted, machine learning techniques allow you to analyse ever-increasing data sets to extract even more accurate insights than would have been possible without the support of AI.

  1. The Subscription Economy Extends to Data Infrastructure

Storage-as-a-service was once seen as a cost-effective way for small and mid-size businesses to implement and maintain their own storage infrastructure. Now, it’s a trend that the largest global companies are looking to implement.

This subscription-based, pay-as-you-consume-type model is permeating an increasing number of areas in modern enterprise.

Businesses are opting to store a proportion of their data in the cloud and only invest in systems that will provide tangible value to their data management, saving on hardware investment and maintenance costs.

With this SaaS model, businesses can have complete transparency over pricing and related KPIs without being locked into a service that offers minimal benefits by comparison.

Customers now seek additional support regarding the mundane aspects of their data management systems, which is why storage-as-a-service models are set to become a usual way for businesses to handle their data moving forward.

  1. Hybrid is King

Having hybrid cloud capabilities is no longer an option, it’s a core aspect of your data management strategies. We all want the ability to transfer workloads to the cloud when we need to.

However, given that not all cloud services are public, hybrid offers you the best of both worlds.

Hybrid cloud data management supports growth across an entire storage system meaning businesses ensure they can easily, and transparently, migrate data from on-premises to a cloud providers system and back without any undue complications.

By providing the flexibility to handle and adapt to changing circumstances, something inherently necessary during a time of uncertainty, hybrid cloud systems can be a valuable part of the solution.

On-prem systems will always remain a part of data management strategies to help control costs, reduce latency and tighten security, however having hybrid capabilities in place can help expand workloads to both public and private cloud environments, supporting the specific storage requirements you may have at times of increased demand.

  1. Making Data Management Sustainable

Around 40 million tons of electronic waste is generated each year which now makes up 70% of our overall toxic waste. In fact, it’s estimated that the world’s data centres will likely consume 13% of the world’s electricity by 2030.

All this means that curbing wasteful storage practices, through the cycle of data acquisition, storage and – ultimately – disposal, is a growing issue as more data is collected.

The emergence of cloud-based technologies are now encouraging organisations to reduce their reliance on inefficient legacy server rooms, but more measures will need to be implemented in order to combat the environmental impact that comes from poor data storage.

Business leaders need to place added emphasis on reducing their carbon footprint as it relates to their data, not just through encouraging more sustainable systems, but by focusing on the overall efficiency of their data centre, to reduce e-waste at all stages.

As data storage becomes more efficient year on year, having the ability to repurpose and recycle data can help create more sustainable data management practices moving forward.

By Dr Chris Cooper, Director and General Manager, Lenovo Infrastructure Solutions Group MEA.

Edited by Luis Monzon
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