Innovative solutions driving your business forward.
Discover our insights & resources.
Explore your career opportunities.
Learn more about Sogeti.
Start typing keywords to search the site. Press enter to submit.
Generative AI
Cloud
Testing
Artificial intelligence
Security
January 05, 2024
Let’s cut right to the chase: Data and AI-powered organizations are more profitable and generate more revenue on average per employee. One obvious thing is that data represents value, and the companies that can exploit this value have a competitive advantage. So, every CEO, CFO, or CIO should have plans to develop and roll out a first-division data strategy to use this richness and make his company a data powerhouse.
So far, so good, nothing complicated, nothing new, all logical. But how to do this? This question gives many managers sleepless nights, wondering how they will choose between different architectures, tools, and governance methods, how they will transform the organization culture, and change their collaborator’s thinking. And what is even more important: where to find the budget and resources to deliver? It is like standing before the gates of a big labyrinth, with no beautiful Crete princess in sight that can help the Data Hero with a golden thread to find his way to the data treasure (no minotaur, this is a mythological beast-friendly article).
Creating a data philosophy that makes an organization data-driven is not an easy task. Any existing data architecture is mainly due to the consequences of answering short-term business demands, emergency solutions, and strategy changes made by the management. In plenty of cases, this leads to data silos, spiderwebs of interfaces, crooked governance, and a large catalog of IT tools. And, of course, there is no documentation in sight! To change all this into a mean and streamlined data machine can look frightening.
So, what makes an organization data-powered?Data-powered organizations have a certain degree of maturity in each of the sectors in the visual below:
Where to start? The next episode of this blog will explain how one can navigate the data evolution and the steps a data-modernization plan should contain.
Data Solution Architect, Sogeti Luxembourg
We use cookies to improve your experience on our website. They help us to improve site performance, present you relevant advertising and enable you to share content in social media.
You may accept all cookies, or choose to manage them individually. You can change your settings at any time by clicking Cookie Settings available in the footer of every page.
For more information related to the cookies, please visit our cookie policy.