Alain De Maertelaere
Needless to say that DATA is the most important driver for data-driven digital transformation. In one of its latest reports Gartner indicates that the number of AI projects will double in 2020. Where today we have 4 to 5 AI projects per company, we go to 35 projects in 2022. The biggest challenges for the implementation of AI are the lack of specialists and, the concerns and the lack of a clear and effective framework about data quality and defining the scope.
Data-driven decision making is about decisions that are made based on insights gained from (historical) company data by applying data analytics and AI. We forget about intuition, observation or "informed guesswork": no more shooting in the dark! We say that data is the oil of the 21st century, analytics and AI is the combustion engine.
The insights gained from data can be used by companies:
- to provide valuable information to optimize their current operational efforts and thus become more customer-focused;
- to forecast future trends;
- to make them more adaptable to the constant state of change in the digital world;
- to help them developing strategies and new activities (cf. blue ocean) in order to generate more revenue.
During the presentation we will explain how we can make the traditional organization AI proof by initiating methods and techniques for the creation of company awareness about the importance of data, the setup of data maturity tracks, the improvement of data quality, "ideation" setup, etc.), and what architectural resources we need to consolidate and store company data to achieve all these and make it accessible to analytics and AI.
By the end of the session it will be obvious to the listener how decisive and how important it is to have a robust, consistent data foundation layer for obtaining reliable results through analytics and AI.PDF
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