Taming the data beast from Edge to Core to Cloud

Main visual : Taming the data beast from Edge to Core to Cloud

Just like many styles of clothes, IT trends often return – and currently, distributed IT is having a comeback.

In the 1990s, IT infrastructures were centralized around PCs and mainframes but became more distributed with the adoption of the Internet around the year 2000.

The next decade saw the pendulum swing back the other way as organizations embraced the cloud and adopted software-as-a-service models.

Now, after almost 20 years, it is swinging back again as the proliferation of Internet of Things (IoT) data accumulated by businesses has made it necessary to push IT back out to the edge – bringing with it a new set of opportunities and challenges.

In fact, the advent of Industry 4.0 has given rise to an exponential increase in networked machines and hyper-connected manufacturing.

The resulting real-time data and visibility over systems has improved efficiency, predictability and innovation for organizations from all industry sectors and has even led to the creation of entirely new business models.

There are traditional product manufacturers that have moved to a managed service model thanks to the data they now have access to.

For example, jet engine manufacturers no longer sell engines, instead they sell operating hours, or the manufacturers of excavators that now charge by the volume of dirt moved – a practice you could say is results-driven pricing.

Addressing the opportunities and challenges of computing at the edge, the core and the cloud

All these transformational companies have a characteristic in common: they collect a great deal of data across the whole lifecycle of their products and convert it into valuable information and insights that drive these new business approaches.

  • IIoT drives Edge computing

Much of this deluge of new IoT data is moving to the edge – with analyst firm IDC predicting that, by 2022, 40 percent of enterprises will have doubled their IT asset spending in edge locations.

 This move to embrace edge computing allows businesses to process their data nearer to the “things” that collect the data, addressing the latency, bandwidth, data privacy, and autonomy issues associated with centralized computing.

It also reduces response times, enabling near real-time decisions and minimizes network load.

  • The A team Edge & Cloud Computing

That’s not to say that edge computing will replace the cloud – these are complementary, rather than competitive or mutually exclusive technologies.

Cloud computing offers attractive speed, agility and cost advantages, leading to it becoming an integral part of IT architectures. However, businesses rarely find a single cloud that optimizes all workloads.

As a result, enterprises tend to mix and match options, blending several external cloud services with their own on-premise and/or private clouds to run each workload on the most appropriate platform.

Unfortunately this approach creates new management complexities and can lead to data silos.

  • Datacenters are here to stay

At the same time, many businesses prefer to retain mission-critical systems, such as enterprise resource planning, on-premise.

Additionally, the emergence of machine/ deep learning and related artificial intelligence technologies are poised to take business analytics to the next level – their increasing deployments are transforming enterprise data centers into centers for business intelligence.

But to be effective, AI-technologies need access to all corporate data, regardless of where it is created, processed and/ or stored – at the edge, the core or in the cloud.

As Enterprise IT architectures are growing increasingly complex and the data spreads out across multiple locations, the key to taming the data beast is eliminating silos and complexity.

This means creating a single seamless architecture from their distributed networks and ensuring data is kept under control, preventing data loss, fulfilling compliance requirements and making it available for iterative business analytics.

Fujitsu’s holistic approach to data management

Fujitsu’s holistic approach helps customers create a distributed IT environment that spans all data regardless of its location at the edge, the core or in the cloud.

The key component that enables customers to centrally manage and control all data regardless of its location is based on Fujitsu’s strategic partnership with NetApp and implementing the Data Fabric.

The Data Fabric enables organizations to seamlessly blend data from private and public cloud, on-premise/core IT and edge locations while maintaining complete control and access to valuable data, regardless of where it was created, processed or stored.

It allows enterprises to extract lightning-fast business insights from IoT data with analytics located close to the edge, while also making it available to be leveraged from anywhere within the broader IT architecture, for instance, machine learning applications located in more traditional data centers or the cloud.

Transforming into a data-centric organization

While data is becoming a business’ most valuable asset, its value can only be accessed by opening it up to be leveraged by all applications and applying it to create new value across the entire organization.

Implementing a cohesive Data Fabric means that it is possible to ensure that this valuable data is both secure and readily available to all applications, from edge to the core to the cloud.

But no single solution fits all businesses, they need an individual approach to defining the balance that exactly meets their needs.

For more information about how to plan your individual journey that seamlessly combines hybrid IT and edge computing, visit Fujitsu.com/netapp