Why do organisations need to improve the way they manage data?
We live in a data economy and as both consumers and businesses we’re all active participants. In the data economy, data is the currency. We exchange it, we transact with it almost every day. It’s dynamic and in the enterprise it flows in and out of our organisations, between departments and cross-functional teams who are tasked with creating value from it. The data economy is about to undergo explosive growth. By 2025, humans will have created almost 180 zettabytes (ZB) of data — that’s up from 18ZB in 2015.
Organisations are in a race to leverage that data to gain a competitive advantage. The winners in this data arms race will be the ones that understand that they need to think about data differently and apply new skill sets and practices to the way data is managed and ultimately monetised. In our recent Rethink Data report, IDC estimates that less than a third (32%) of data being generated is actually being used — meaning more than two-thirds of it is going to waste. That’s a huge untapped opportunity.
What is spurring this growth in data?
Over the past decade, we’ve witnessed the third major IT revolution since the invention of the computer — the emergence of cloud computing, where data is created and captured on billions of endpoint devices and then uploaded to centralised IT infrastructure. This era has been dominated by hyperscale public cloud companies who were able to both help create and capitalise on the growth of the data economy. One of the primary drivers for how these companies were able to do this is the data itself. They figured out the direct correlation between the accuracy of AI and machine learning training models and the size of the datasets with which they are trained.
More data generated means better analytics, which in turn means better business insights and better products for customers. As Google’s research director Peter Norvig once said: “We don’t have better algorithms — we just have more data.”
What will be the next key data trend that organisations need to focus on?
The next step is IT4.0 — the fourth major IT revolution — and the rise of the edge. This is where data is processed and stored as close to the data source as possible and is being driven by the proliferation of internet of things devices and 5G connectivity. No longer does data have to be sent back to a monolithic, centralised storage centre, organisations can process data where it is being generated: in cell phone towers, on roofs of buildings, in autonomous vehicles. This means organisations will have access to new data sources and new, highly complex and unstructured data types to manage. At the same time, new hybrid architectures incorporating multiple public, private and geo-distributed edge clouds are emerging in order to capture the data opportunity as storage shifts to a decentralised model.
What are the main challenges organisations face when storing data?
As the wealth of data grows, it will continue to be evenly distributed across multiple data centre-, edge- and cloud-storage environments. Data growth and data sprawl are just two of the data management challenges that organisations must grapple with as they adjust their businesses to a world of IT4.0.
One of the main reasons data is being underutilised today is that the cost of enterprise storage is prohibitively expensive. More efficient, scalable and affordable solutions are needed for organisations who are being asked to do more and store more with less. Another reason is that most of the 180ZB of data that will have been created by 2025 will be machine-generated, unstructured and geographically dispersed.
Management of data across various locations and multiple clouds and platforms is prohibitively complex, especially for IT organisations whose resources are already constrained. Therefore data risks becoming siloed, stranded and unusable.
How can organisations best solve these issues?
To overcome this complexity, organisations need open architectures and new approaches to data management, and simple, easy-to-deploy solutions so they can mobilise, consolidate and analyse data at their required volume and speed.
With the relentless growth of data and the 24/7 cost implications of storing it, today’s multi-cloud solutions and configurations — where each cloud vendor has its own unique tools, policies, cost models and desire to retain customer data within their own ecosystems — are not the answer to the storage cost and complexity challenges. Organisations are forced to compromise in the data economics equation where the cost of storing more data can seem like it outweighs the value that can be derived from it. To address this issue, we believe there needs to be a shift both in paradigm and operational approach.
Instead of a world where we only store what we can afford and manage, we want to create a world where we can store as much data as we want. In this world, closed-off, proprietary architectures are replaced with open, hybrid architectures where data moves freely and efficiently across an organisation, no longer trapped in silos.
What will this ultimately help organisations to achieve?
In this new world of open, hybrid architectures, data stewardship is not constrained within the boundaries of the IT function but instead democratised across interdepartmental teams. This is enabled by a DataOps model which allows full access to disparate datasets, and an environment for AI-powered innovation, paving the way for predictive insights that drive digital transformation and competitive advantage.
Seagate is uniquely positioned to help solve these operational and architectural data management challenges. We have been a technology company innovation leader for more than four decades. Our entire product roadmap is based around the vision of building a frictionless future for the world’s data through open, edge-to-cloud data management solutions. Partnering with our customers to reduce the cost and complexity of their infrastructure, we enable them to store more data, create more value from it and ultimately win in the data economy.
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