Wikibon Predictions for 2017 and Beyond

Peter Burris, chief research officer and GM at Wikibon, SiliconANGLE, Inc.’s research arm, published his predictions in this article dated November 23, 2016

What’s in store for 2017 and beyond?
We’ve huddled with our community and come up with a list of questions that need answering and answers in the form of predictions. The overall theme: Put more data to work.

Our research shows consistently that this current period of digital transformation needs to be understood not in terms of management bromides, but simple prescriptions: If, to paraphrase Peter Drucker, business exists to create and sustain customers, then digital business is the application of data to differentially create and sustain customers.

From that perspective, 10 questions emerge that will guide tech behavior over the next 10 years. They are:

2017 questions:
    •    What’s driving technology architecture?
    •    Do microprocessor options matter?
    •    Whither HDDs?
    •    Code in the cloud?
    •    Amazon momentum?
    •    Big data complexity?

2022 questions:
    •    New IT mandate?
    •    IoT + augmented reality = ?
    •    Is this all there is to digital engagement?

2027 question:
    •    Will we all work for AI?

2017: What’s driving technology architecture?
Data movement isn’t free. Physics insists that it costs time and fidelity, and WAN providers insist on getting paid. As digital technology moves closer to mechanical or knowledge work, it will drag system requirements with it, and physics and WAN providers will have their say.
Wikibon 2017 Prediction: IoT edge use cases begin shaping decisions in system and application architecture.

2017: Do Microprocessor Options Matter?
As more computing moves closer to the device or person performing the work – generating new types of systems requirements – the factors that made Intel Corp.’s x86 architecture dominant start to lose potency.
Wikibon 2017 Prediction: Evolution in workloads creates an opening for new microprocessor technologies, which grab 2-3 points of x86 server market share.

2017: Whither HDDs?
Increasingly real-time-like applications operating on broadly distributed microprocessors generates enormous volumes of data, but also consumes huge data. Disk-based storage systems, the ‘John Henry’ of computing for the past 40 years, no longer can keep up – at least not in performance-focused settings. HDD Drive units will continue to grow, but in capacity-oriented settings, replacing tape. The new top dog in storage is flash.
Wikibon 2017 Prediction: Anything in a data center that physically moves gets less useful and loses share of wallet.

2017: Code In The Cloud?
Developers have a whole new toolkit to play with, which is comprised of container-based technology. The promise of these new tools are significant: better performing applications, simpler deployment, faster change cycle times, lower exit barriers, greater reuse, among many others. But we’ve heard this before: distributed computing architectures, service-oriented architectures and other technologies were supposed to save business from monolithic applications, but it didn’t turn out that way. Conway’s Law, which states that a system’s final design reflects the communication structure of the organization that built it, is alive and well.
Wikibon 2017 Prediction: The new cloud development stack, centering on containers and APIs, matures rapidly, but institutional habits in development constrain change.

2017: Amazon Momentum?
It seemed like a good idea when officially launched in 2006, but most doubted its effectiveness and impact. No longer. Today, Amazon Web Services has emerged as a force in the technology industry by offering simple, cost-effective (at most scales) and highly elastic cloud-based computing. A overwhelming number of tech start-ups are built on AWS. What about new digital business infrastructures of less tech-oriented companies? AWS needs to maintain its simplicity roots if it’s going to attract less sophisticated enterprises to its cloud options.
Wikibon 2017 Prediction: Amazon has another banner year, but customers start demanding a ‘simplicity reset.’

2017: Big Data Complexity?
Our research shows conclusively that the promise of big data isn’t being achieved in most businesses, and complexity is the problem. Unless tooling and integration are made simpler, enterprises won’t be able to amass the experience required to establish crucial big data business capabilities. And if business can’t establish the capabilities required to better fashion use cases and sustainably operate analytic pipelines, the potential advantages of machine learning, AI, cognitive and other big data-related patterns will remain well out of reach. We think bigger, more established companies sense an opening.