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    Newsletter Aug 18

    by Ian Hight
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    Welcome to the SASIT August newsletter

    In this issue

    Taking a different approach to disruption
    Legacy application modernisation
    SASIT creates a new website
    SASIT’s Ajay Nabh recognised internationally for thought leadership
    A large delegation to attend TechU
    Artificial Intelligence’s (AI) new use case: Integration?


    SASIT – Taking a different approach to disruption

    There is growing press on the topic of digital disruption, and in our view it’s often over hyped. Our perspective is that business disruption is occurring at a faster rate, but that digital technology is simply just one enabling factor. Outside of the technology itself, the other major drivers of business disruption that we see impacting the landscape are:

    1. Greater competition. The continuation of globalisation, the blurring of market boundaries, and decreasing barriers to entry.
    2. Cultural changes: Managers are placing greater importance on organisational agility including spending more time on research and experimentation. Old business models and more cumbersome traditional approaches, just don’t cut it anymore; for customers or staff.
    3. Decreased tolerance for what’s not working. Linked to the two points above; the competition for customers, and for retaining and acquiring new staff means that poor systems and processes can no longer be tolerated.
    4. A growing number of highly skilled technology architects. Cloud has enabled anyone connected to the internet to have immediate access to much the worlds most advanced technology. But like a DIY novice standing in a Mitre 10 Mega having access to all those products doesn’t mean you will have a great house. Success often starts by engaging an architect.
    5. A greater number of inter-organisational alliances/partnerships. Building products and developing services increasingly involves cross boundary collaborations. Organisations taking this approach are bringing better products to market far faster than their competitors.
    To let our customers know how we are responding these disruptive factors we created a video

    Legacy application modernisation

    Deciding what to do with your older IT systems is seldom straightforward: Replace? Modernise? Migrate to the cloud? It can quickly become complicated. 

    For decades, SASIT has been working with customers across Australasia to manage, support, and differentiate themselves using technology, as well as providing operational management of business critical applications and infrastructure.

    To help organisations navigate the path ahead, we have produced a white paper, we hope you find it useful.

    To download the whitepaper click here: Modernisation Whitepaper (*.pdf)


    SASIT creates a new website

    We recently unveiled a new website to ensure that the wider market is kept informed of our evolution and growth as a Managed Service Provider. The homepage banner presents an animated cloud graphic which highlights the company’s increased focus on managing cloud environments, and more specifically managing hybrid environments which are now the norm of Australasian businesses.

    The new look is more modern, has less pages, but we hope has all the information you’re looking for. The website is of course complimented by our LinkedIn site and YouTube channel.


    SASIT’s Ajay Nabh recognised internationally for thought leadership

    Many SASIT customers will be aware that our Senior Solutions Consultant Ajay Nabh is a member of NatApp’s elite “A Team” a distinguished group of 25 NetApp technical experts from around the world.

    In June these internationally recognised experts met in Sunnyvale California to discuss and develop recommendations for consideration by NetApp’s executive management group. 
    Ajay commented “It’s very encouraging to see the scale of resources that NetApp has focused on new, cutting edge, cloud offerings. The company continues to do an amazing job of reinventing itself to stay at the forefront of data management”.

    NetApp is clearly focused on enabling organisations to easily and securely unite and manage data across the widest variety of environments. The company has established a leading position in hybrid cloud management using a data fabric based approach.

    NetApp’s products and services align very well with SASIT’s broadening offerings to assist customers derive value from better management of their own and third part data; said Ajay.


    A large delegation attendED IBM TechU

    TechU - which was held in Sydney this month, is IBM’s most comprehensive technical training event in A/NZ. TechU involved more than 100 focused lectures and labs, on-site certification sessions, a solution centre expo, and networking opportunities.

    Sessions were delivered by some of IBM’s leading engineers, developers and product experts on AI, Cloud, Data, Security, and Systems.
    SASIT was well represented at the event this year with a five person delegation.


    Artificial Intelligence’s (AI) new use case: Integration?

    In the last year or so we have seen a great deal of increased publicity about AI. AI is an umbrella term that includes multiples technologies such as computer vision, machine learning, natural language processing, and others. It’s useful to think of AI as software that has the ability to see, hear, reason, and learn.

    Recent publicity has typically been focused on use cases such as fraud detection, voice enabled assistants, data security, image recognition, and driverless cars; but what about systems integration?

    Integration is becoming increasingly important for organisations wanting to stay competitive by leveraging data and capabilities provided by third parties. Currently integration is mostly the domain of technical specialists, undertaking their work cautiously and slowly. But therein lies a problem; businesses now want integrated capabilities on demand. AI has the potential to turn these wants into reality.

    At the device level automated integration is already here; the challenge is to provide complete systems that will automatically connect together. So how can you design for integration between ecosystems, platforms and things you cannot predict? The answer is using AI.

    Lets’ consider a practical example: A bank needs to transfer funds to a new trading partner. The banks AI will know which API's to connect to, and just the right information to exchange and complete the transaction, in a secure manner. No integration project, no technical team, and no big cost.

    Evolution of Integration

    Up until very recently integration has mostly been something businesses have either outsourced, or used in house technical teams for. The problem, however, is that the demand to connect to things digitally is out stripping the ability for human integrators to deliver; whether they are specialist in-house teams, or outsourcers.

    To meet this demand, integration delivery needs to be re-balanced in other ways. Enter the digital integrator. The digital integrator uses meta data analysis for improved data mapping, and provides process analysis to suggest better integration, all packaged as part of a product. This approach reduces the need for integration specialists and opens up integration to a process of human initiated needs fulfilled by AI enabled systems.

    AI can therefore enable a greater number of people to perform integration. Humans can drive integration by using AI services to request digital outcomes. The AI engine listens to requests, then connects them together with the data and systems needed to support the requirement. AI based integration potentially shortens the learning curve of both specialist and less / non-technical integrators to manage data and business flows, enabling almost anyone to perform integration tasks.

    In many business ecosystems we now have the following actors:

    • Integration specialists - The traditional integration people who generally focus on enterprise projects, bulk data processing and governance.
    • Ad-hoc Integrator's - Tend to be in line of business roles and use fit for purpose tools for Mobile and API development
    • Citizen Integrator's - Are focused on personal projects, want instant gratification and integrate using data sync SaaS apps often on mobile devices
    • Digital Integrator's - Are AI and ML (Machine Learning) driven, support digital business projects and deliver automation using deep learning
    Challenges

    This new and rapidly evolving environment is not without its challenges. The first challenge, obvious to the technically minded, is the need for common standards for AI/ML integration, as without a common standard for interconnection AI/ML will struggle. The challenge of standards, however, is a challenge in decline as increasingly the world is creating API's which in turn fuel the development of standards. 

    The next challenges relate to change management, security and data privacy. With the rapidly increasing use of productised API management systems these areas are also becoming less of a challenge. Change management is enforced by API management platforms ensuring the integration actors work to guidelines and processes enforced by the API owner. Security and data privacy are also managed by policy ensuring that API consumers are not only authorised but also mandated to control access to data at a very granular level. So the technology provides the policy makers with the tools they need to enforce policy.

    How does a digital integrator know which API to connect to, to deliver on the task the business owner has directed them to fulfil? For a long time API's have operated with levels of discover-able meta data. Meta data is like digital sign posts that direct data consumers to APIs. With the right systems and processes in place the API owner retains full control over what data, and services, are made available.

    The most controversial challenge is; how much do we trust an AI? Most of what has been described so far is current technology, and some product vendors are actually starting to incorporate AI into their API management and integration products. So why is this whole area a candidate for wallowing in a trough of disillusionment? Basically it’s us humans and our inherent distrust of AI. However AI and ML, driven by citizen integrators, is now gaining momentum in terms of social acceptability.

    Key enablers
    • AI and machine learning techniques applied to integration are emerging as digital integrator technologies.
    • Growing criticality for a business to leverage AI to support automation, insight and engagement.
    • Emerging technology innovations in AI for reduced time to integration and enabling citizen and ad-hoc integrators.
    Inhibitors
    • Organisations lack awareness for these emerging offerings of AI in integration platforms and the benefits of applying such new technologies.
    • Business is cautious about exposure caused by high-value application and data flows used by AI.
    • Concerns about how to bring AI systems into the realm of reliable mission critical systems.

    We suggest it is now time to investigate the benefits of AI by experimenting with integration platforms. However, temper that with a good dose of scepticism and be directed by integration specialists. Even with new AI technology integration specialists still have a key part to play. 

     

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