With the rapid use of machine learning and AI in every organization, business insights are helping them grow in new ways. Nevertheless, organizations cannot take full benefit of it as data siloes are holding them back. This session would focus on handling such data complexity while delivering end-to-end data governance and offering businesses the advantages of AI.
Key Takeaways
- Identifying data siloes within the organization.
- Design and plan the data landscape.
- Utilizing the full potential of Open Source.
- Building a cost-efficient data platform with end-to-end governance.
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Bio
Taranpreet Singh Grover – Solution Architect | Daimler Trucks Asia | Japan
Taranpreet possesses experience of 1.5 years as a solution architect working for Daimler Trucks Asia: A world-leading commercial vehicle manufacturing company. Previously, he had dual responsibility of data engineer and data cataloging in the same organization. He specializes in building efficient and scalable data platforms.
He is passionate about solving data complexities and performing quick data PoCs across different cloud vendors.
On the side, he enjoys working on applications involving Augmented Reality and Blockchain.
With a background in Computer Science, Machine Learning and AI, he actively participates and collaborates with people in the same domain to explore and try out new improvements in the technical world.
Day 1 | Stage 1
Taranpreet Singh Grover – Solution Architect | Daimler Trucks Asia | Japan