Buying Decision - Data Analysis

This could be biased but when you have limited budget and have to take a convincing decision :)

 

Keep Exploring!!!

Corona Stats - As of March28th

Data Source - Link (As of March28th data)
Case Stats and Growth Trend
Start Date - 2019-12-31

• Day 69 - 102133
• Day 81 - 213258
• Day 84 - 305270
• Day 87 - 417061
• Day 89 - 528019

Summary

• 1st 100K - 69 Days
• 2nd 100K - 12 days
• 3rd 100K - 3 days
• 4th 100K - 3 days
• 5th 100K - 2 days

Death Stats and Trend

• Day 1 - 2019-12-31 
• Day 76 - 5407
• Day 83 - 11251
• Day 86 - 16365
• Day 88 - 20991

Summary

• First 5K - 76 Days
• Second 5K - 7 Days
• Third 5K - 3 Days
• Fourth 5K - 2 Days

Case Distribution by Country

Fatality

I hope we get through this challenge and recover soon. With global lockdown measures hope we observe downwards trend in the coming weeks.

Good Read - Response to COVID-19 in Taiwan Big Data Analytics, New Technology, and Proactive Testing

Key Points

• Specific approaches for case identification, containment, and resource allocation

Databases Leveraged

• Immigration and customs database for travel to Risk Areas
• Health insurance database for proactively seeking out patients with severe respiratory symptoms 

Risk Categorization

• Low risk (no travel to level 3 alert areas) 
• Higher risk (recent travel to level 3 alert areas) 

Inference

• Real-time alerts during a clinical visit based on travel history and clinical symptoms to aid case identification
• Tracked through their mobile phone from Self Quarantine

Good Read - Lessons from Italy’s Response to Coronavirus

Key Summary Points (Implementation)

• Avoid partial solutions
• Learning is critical

Key Summary Points (Lessons Learnt)

• Extensive testing 
• Proactive tracing
• Home diagnosis
• Monitor and protect health care and other essential workers

Corona Perspectives (July 5th 2020)

Covid Cycle

Unlock Cycle

IT Impact

Carefully we need to plan, bride the gap to address the gaps in the economy, unorganized sectors, poor performing domains. Hope the new normal provide more innovation and newer job opportunities

From NPTEL Lecture Link

Webinar 2 - Link

Keep thinking!!! 

Data-flow -> Knowledge-flow -> Future Prospects

• Data to Datalake
• Datalake to Collective DataInsights
• DataInsights to Features
• Features to Models
• Models to Predictions
• Predictions to Preparedness

Data -> Insights -> Predictions

Happy Learning!!!

Day #298 - Data Analysis of PNB Defaulters

Data Source - Link

Data Analysis of PNB Defaulters

Chart #1 - Top 20 States By Company Registration State and Defaulted Amount



Chart #2 - Top 20 States By Defaulters Count





Chart #3 - Top 20 Branches with Maximum Defaulters





Chart #4 - Top 20 Branches with Maximum Defaulters Loan Value





Possible Feature Variables

1. Branch Related Approval Score, Higher Defaulters lower the rating
2. Similar Industry Match Score
3. State Related Scores
4. Connections / Joint ventures in Past with Collapsed Companies
5. Rules for threshold limit based on Industry / State / Branch
6. Multiple Models for ongoing monitoring / performance / social medial trends etc..
7. Build a global model with defaulter list across banks and identify common patterns/modus operandi

Happy Learning!!!

The Value of Data

The value of data across the chain as we look at data from different perspectives.

Early Stages of Data Analysis

• Data Collection
• Data Reporting
• Dashboard Reporting

Mid Level Data Analysis

• Metrics / Measures for Creation (Business Intelligence / Trends)
• Predictive (Forecasting)

Advanced Level

• Machine Learning Based Models
• End to End Automated Workflow chain with all levels of Data Analysis

Pain Points of BI

• Reactive Mode - It doesn't help us to know the future but rather learn from past
• Data Distribution - Cannot fit Data and Distributions to understand better, Data can be fit into any form of pattern / distribution. BI does not help us Deep Dive to identify that
• Tight Schema Bound Architecture - Models, Dimensions are Static, Dynamically cannot change the facts, a measure without changing underlying ETL

Happy Understanding with Data!!!

Day #107 - Data Analysis and Exploration

Happy Learning!!!