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CXO Survey

Potentials are far from exhausted

"Digital Readiness" is more than just a buzzword used by analysts and industry experts. It describes the decisive success factor in a dynamic business world. Together with Statista, we asked CIOs and CTOs about their transformation progress and the use of their data potential.

German companies continue to work full steam ahead on their digital transformation. This is characterised above all by the exemplary platform architecture, focused innovations, and new technologies (e.g., IoT, artificial intelligence, machine learning).

 

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Survey
Digital Transformation
Data & KI

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Transformation initiatives in the german market

When looking at the given need for transformation, the infrastructure goals, and the current drivers of digital transformation, one thing becomes clear: CIOs and CTOs will have to make several major strategic decisions in the foreseeable future on how digital business models can remain fully competitive.

This is always accompanied by the need to renew or expand digital services or services. The central challenge here is how focused these investments are on building helpful ecosystems and partnerships as smartly as possible.

Want to learn more about digital transformation?

Dennis Klemme, director data architecture & data engineering at diconium, answers questions about opportunities and challenges in the market in a short interview.

Read more in our blog >

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Evaluating data along the value chain

In addition to the status quo of digital transformation, our CIO / CTO survey took a close look at the current challenges and opportunities in exploiting the potential of data. Because data can provide important insights and findings to drive the digital growth of companies.

Digitisation generates data - through everyday business processes, contacts with suppliers, partners, customers or IoT. Companies have plenty of data that creates great potential for digital growth strategies.

Evaluating and analysing this data with the help of technology is crucial. It requires an adequate data management organisation, an optimal organisational structure, and corresponding data expertise in the teams.

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