Data & AI Cognitive (DAC) Architecture

Data & AI Cognitive (DAC) Architecture

I had the pleasure of being a guest on the ???????? & ???? ???????? podcast hosted by the incredible Mirko Peters, where I shared insights into a concept close to my heart: ’Data & AI Cognitive Architecture.’**

?? ????????????????????:

? How this architecture bridges the gap between business objectives and AI-driven technologies.

? Its role in enabling organizations to create actionable intelligence while ensuring scalability and trust.

? A practical framework that ensures data, AI, and cognitive systems work together seamlessly to deliver business value.

?? ?????? ???????????? ??????????????????:

1?? The motivation behind developing this architecture.

2?? How it aligns with modern data strategies.

3?? Real-world examples and challenges solved by this approach.

??? ?????????? ?????? ???????? ???????????????????????? on the Data & AI Show: https://youtube.com/live/33ho4tDfFg4?feature=share

big thanks to Mirko Peters for hosting such an engaging discussion! I’m excited to share this as part of *??????’?? ???????? ?????????? ????????! and look forward to hearing your thoughts and questions.

?? ???????? ?????????? and find more thought-provoking episodes on Let’s Talk About Data! https://youtube.com/@letstalkaboutdata

#DataAI #CognitiveArchitecture #DataStrategy #LetsTalkAboutData #Podcast

Data & AI Cognitive (DAC) Architecture --> Few Slides




Perry (Pin) Chen, PhD

Head of Design and Product, specialist in enterprise data ecosystems, enterprise data practice management, and data product practice and technology

2 个月

Very good forward thinking on Architecture Practice, Mustafa Qizilbash, which is actually very close what we are trying to achieve for Enterprise Data Practice Management. There are some challenges for conveying such a message or new concept (that is, DAC architecture). First, architecture is everywhere and somehow overutilised in IT and data space in modern orgnisations, including EA, BA, various data architectures/approaches (i.e. Mesh and Fabric), platform architectures, landscapes of systems and technologies, data models/modelling, solution/integration architectures, AI/ML-related architectures, and concept/approach-related architectures (metadata architecture, orchestration architecture, and data quality architecture. How are all these different architectures related? What is the architecture capability for modern orgs? Who should be responsible for architecture management and applications or ROIs after developing various architectures?

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