The document discusses how data science and artificial intelligence can be used to improve data in three key ways: 1) Data consolidation can provide a 360-degree view of customers to gain insights into their habits, interests, needs, and behaviors to enable hyper-personalized engagement and access to products and services. 2) Data cleansing is an important but unglamorous part of the process that can consume 60-80% of engineer time; artificial intelligence can help identify and address issues like duplicates, missing data, and ensuring proper data context. 3) Artificial intelligence can help address data quality issues in real-time to avoid time lags in decision making compared to traditional engineering approaches.

1. Data Science and Artificial Intelligence
towards improving Data
Somu Vadali
Head - C&D Labs
Chief Data and Product Officer @ Future Group

2. The Trinity of ML/AI
 Consolidation
 Cleansing
 Augmentation
 Optimization
 Scalability
 Multi-dimensionality
 ML Platform & Stack
 Frameworks
 Application services
Data
AlgorithmsML/AI

3. Data Consolidation + Insights
360° Customer View
Customer Insights
• Habits & Interests
• Needs & Predictions
• Buying patterns
• Basket Size
• Behavior
• Share of wallet
Customer Engagement
• Hyper Personalization
• Broader access to
products and services
• Faster & convenient
process

4. Data Cleansing - Is it important?
60%-80% of time – 12x Engineers Vs
Scientists
Better Data > Fancier Algorithms
Real-time needs – time-lag in
decisions
Not the glamorous part

5. AI can help in Many ways
Duplicates
• Name-identity recognition
• Irrelevant observations
• Filter unwanted outliers
Missing
Data
• Many algorithms don’t accept
• Dropping and imputing?
• Categorical and Numeric data
Context
• Diversity including alternate data sets
• Alternate data – linking
• Semantics & Integrity checking