Implications of the App Economy, Big Data and server workloads…

These days it seems there is an app for everything. It is easy to forget that the Apple App Store - which revolutionised how we consume software - was opened on July 10, 2008, with an initial 500 applications available. As of 2018, between Google, Apple, Amazon and Microsoft there are now in excess of 5 million apps to choose from. App Annie predicts the App Economy will be worth $6 trillion by 2021.

Apps are becoming the software delivery mechanism for all types of interaction, not just from Business to Consumer, but also from Business to Workforce. App’s are becoming increasingly important to an ever more mobile and empowered workforce.

These same apps are generating an unprecedented amount of data – currently 2.5 quintillion bytes are generated according to Domo. This amount of data is both boon and burden. It is a boon when you can turn that data into an asset and uncover not only insights but also to create entirely new business models from it. It is a burden considering the processing power that will be required to mine and reap rewards.

Take Uber – it did not exist 10 years ago – yet each day it is generating insight from more than 15,000,000 rides. With 1.6 billion swipes each day on Tinder, we are getting to know each other in ways previously hidden from view.

IBM Power and Cognitive Workloads

Each of the 2.5 quintillion bytes is offering up insight not yet fully realised with systems of intelligence. Built on systems of record and systems of engagement, systems of intelligence or cognitive workloads are fast becoming the key to unlocking the real potential of your data. Consequently the right workload architecture is necessary to handle AI. As this recent Forbes article argues…

By leveraging these leading foundries, IBM has the flexibility to leverage the highest density and most cost-effective process technology. In addition, IBM has focused the design of the Power architecture on overall system performance and leveraging software, such as PowerAI, for improved data flows. The area that is critical in both AI training and inference is bandwidth to memory, to accelerators and to the network.

So, the new normal in our everyday life has become using apps like Uber, Tinder, Instagram and Amazon, or workforce apps that collect and analyse plant condition photos, or customer engagement apps that enable you to size a client for a bespoke suit. These will drive the new normal for workloads – which means you need server infrastructure that is reliable, scalable and secure – all of which you get with IBM Power.

I’d be interested in hearing your comments – let me know and join the debate below..

Likewise, I’m always up for a chat if you have any questions on how you can optimise your investment in SAP by reducing infrastructure costs or reach me via linkedin.

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