Learn to build large language model applications: vector databases, langchain, fine tuning and prompt engineering. Learn more
$13.5B
$1.26 B
2,034
Fifteen dashboards were deployed bearing different metrics, providing an easy-to-use interface for data visualization and analysis.
Six machine learning solutions were showcased in the demo, covering a range of use cases such as predictive maintenance, anomaly detection, and product defect detection. These solutions demonstrated the power of AI and ML in enabling a smart factory and improving worker safety while optimizing manufacturing operations
Custom end-to-end data lineage flows were created using Purview, providing a complete view of data movement and lineage across multiple systems and processes. This helped the client gain better visibility into their data and make informed decisions.
Disparate data sources were registered on Purview, enabling the client to easily discover and understand their data assets across the organization.
The team uploaded a total of 643 data assets onto the Purview platform. These assets were collected from various sources and were classified, organized, and made discoverable using Purview's automated metadata extraction capabilities. This enabled the team to gain a better understanding of the data and the relationships between different assets, which in turn facilitated better decision-making
The project involved creating a comprehensive glossary of 48 terms on Purview to establish a common vocabulary and ensure consistency in data interpretation across the organization. This enables stakeholders to quickly find and understand the meaning of terms used in the data, resulting in improved data accuracy and informed decision-making
Overall impact: The project demonstrated the power and potential of advanced data analytics and governance in the manufacturing industry, specifically through the use of the Dream Demo deployment. By showcasing the capabilities of machine learning, data visualization, and data governance using the demo data, the project provided valuable insights into how manufacturers can improve their operations and make informed decisions based on their data. The project highlighted the importance of leveraging the right tools and technologies to achieve digital transformation and improve overall efficiency in the manufacturing sector.
