What is Data Science

In short

Data science is the practice of extracting meaning from data through a combination of statistics, computation, and domain knowledge. It spans collecting and cleaning data, finding patterns through exploration and modelling, and communicating findings in ways that actually change decisions.

1. 01Data literacy is becoming a basic professional skill across sectors, not just a technology specialty.
2. 02The difference between a good and bad business decision often comes down to whether someone understood what the data actually showed.
3. 03India's digital infrastructure generates data that can inform public health, agriculture, and financial inclusion policy, but only if the analysis is sound.
4. 04Correlation versus causation confusion is responsible for an enormous number of expensive mistakes in product, policy, and medicine.

A fintech startup in Mumbai was seeing high credit card application drop-off on step three of their mobile form. The product team assumed the step was too complex. A data scientist ran exploratory analysis on session logs and found: drop-off was highest between 2pm and 4pm on weekdays, predominantly on 4G connections in certain pin codes, and the step three field was a document upload that frequently timed out on slower connections. The problem was not complexity. It was a latency bug on specific network conditions. Fixing the upload timeout reduced step-three drop-off by 34%. Dashboards said 'step 3 has high drop-off.' Analysis found the actual cause.

• A/B testing→MarketingThe same statistical significance principles from A/B testing apply to marketing experiments and pricing tests.
• Bayes theorem→Human PsychologyBayesian reasoning is the formal version of updating beliefs with evidence. The same updating errors that Kahneman identifies appear in data interpretation.
• Data storytelling→Communication & StorytellingThe best analysis is worthless if it is not communicated in a way that changes decisions. Data storytelling is a communication skill.
• Correlation vs causation→Famous Scientific LawsThe correlation-causation distinction is the statistical version of the same causal reasoning principles that underlie scientific laws.