Business Transformation

Serverless Computing – Revolutionise Application Architecture

The key to unlocking the power of serverless computing lies in implementing better practices. It’s important to start with a solid foundation, careful design and strategic choice of the Cloud provider. Are you ready to revolutionise application architecture? Let’s embark on this exciting journey together.

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Know the Serverless Computing Model

Executing the organisation’s digital strategy to move from on-premise to the Cloud entails choosing and adopting a specific Cloud computing approach. IBRS investigates the concept of serverless computing, which allows developers to concentrate on functionality instead of infrastructure.

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Hopes and Dreams for When Data Mesh Meets Reality

The notion of data mesh is highly appealing, as business stakeholders desire ready access to data for analytics. In their eyes, they own the data and should have easy access in a manner that avoids the delays of a centralised data management approach. However, many organisations are buying into a simplistic and unworkable definition of data mesh, often treating the concept as a technology solution, rather than a governance philosophy. IBRS discusses the role of data mesh in organisations and how data analytics teams must function.

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The Collaboration Paradox: Fragmented and Siloed Knowledge

Organisations that employ digital collaboration tools in an uncontrolled manner find that the very tools intended to streamline communications throughout the organisation result in the opposite: increasingly siloed departmental group thinking and, worse, silos of information hidden from the organisation at large. How can enterprises avoid the tsunami of fragmented knowledge?

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Generative AI for Enterprise Use – An Overview of the State-of-the-Art

With more vendors such as Microsoft, Amazon Web Services (AWS), Google, and SalesForce embedding AI technology into their products for enterprise use, organisations will soon have more tools with AI capabilities. However, more solutions do not always mean producing meaningful outcomes, since most of these products will still fall short of expectations due to the current limitations of language models, and some types of work that still cannot be easily replicated by AI.

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