Challenges¶
Despite the great potential of AI and the large investments industrial enterprises have undertaken in AI technologies, AI has not delivered on the promises in industry practice, yet and data management issues constitute the main reasons for the insufficient adoption of AI in industrial enterprises. [Groeger, 2021]:
Data management generally comprises all concepts and techniques to process, provision and control data throughout its lifecycle. The data management challenge of AI lies in comprehensively managing data for AI in a heterogeneous and polyglot enterprise data landscape. This particularly refers to data modelling, metadata management and data architecture for AI.
There Is No AI Without Data from CACM on Vimeo.
To learn more, read the article “There Is No AI Without Data” from Christoph Gröger, enterprise architect for data analytics at Bosch and a senior technical professional in Bosch’s global data strategy team in Stuttgart, Germany.