Teradata/jupyter-demos
Oct 2025 – Oct 2025
1 Month active
Languages Used
PythonSQL
Technical Skills
Data AnalysisDatabase ManagementGeospatial AnalysisMachine LearningNatural Language ProcessingONNX Runtime
Mohd-Hassan
PROFILE
Mohd-hassan
Developed a Travel Insights Demo Notebook for the Teradata/jupyter-demos repository, delivering an end-to-end analytics workflow that combines geospatial analysis, predictive modeling, and natural language processing to explore the relationship between travel distance and customer dissatisfaction. Leveraged Teradata ClearScape Analytics for in-database computation and ONNX Runtime for efficient, scalable inference within the notebook. The solution, implemented in Python and SQL, enables data-driven prediction of potential customer complaints and supports customer-experience optimization. This work established a reusable demo pattern, addressed specific stakeholder requirements, and demonstrated the integration of advanced analytics techniques for actionable insights in travel-related customer data.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
2,529
Activity Months1
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Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on Teradata/jupyter-demos. Delivered a Travel Insights Demo Notebook that showcases in-database geospatial analysis, predictive modeling, and NLP on customer complaints to analyze correlation between travel distance and customer dissatisfaction and to predict potential complaints. The notebook uses Teradata ClearScape Analytics for analytics and ONNX Runtime for efficient inference, and includes the commit 10c07ad80a8a52ca42e3f5cfcb3abb4bc34234aa implementing Improving_Customer_Satisfaction_Travel_Insights per Tatiana's request. This work advances our data-to-insights capabilities and provides a reusable demo for customer-experience optimization.
1 Commits • 1 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on Teradata/jupyter-demos. Delivered a Travel Insights Demo Notebook that showcases in-database geospatial analysis, predictive modeling, and NLP on customer complaints to analyze correlation between travel distance and customer dissatisfaction and to predict potential complaints. The notebook uses Teradata ClearScape Analytics for analytics and ONNX Runtime for efficient inference, and includes the commit 10c07ad80a8a52ca42e3f5cfcb3abb4bc34234aa implementing Improving_Customer_Satisfaction_Travel_Insights per Tatiana's request. This work advances our data-to-insights capabilities and provides a reusable demo for customer-experience optimization.
October 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
Data AnalysisDatabase ManagementGeospatial AnalysisMachine LearningNatural Language ProcessingONNX RuntimePredictive ModelingTeradata ClearScape Analytics
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