Online sources of data:

1. Government websites (e.g., data.gov.in)
2. URL/web-based databases (e.g., FAO website – www.fao.org)

Offline sources of data:

1. Files in CSV or Excel format stored locally
2. SQL databases stored on local systems

Source: No-Code AI for Statistical Data, Chapter 4

The passage mentions loading data via URL (online) and from websites like FAO (online), and loading from CSV, Excel, and SQL files (offline) using Orange's File widget. Examiners expect two clear examples from each category — one line each is sufficient for this 2-mark question.

(A) SQL databases

SQL databases are commonly used for storing tabular data sets in Data Science, as they organise data in rows and columns for efficient querying and analysis.

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The source passage (Orange Data Mining chapter) mentions that the File widget in Orange loads data from CSV, Excel, and SQL formats — confirming SQL databases as a standard storage format for tabular data. NumPy is a Python library (not a storage format), HTML is for web pages, and JSON stores non-tabular/nested data. Examiners expect you to simply identify option (A) with a brief justification.

Using Data Science, airline companies can:

1. Predict delays — Analyse weather patterns, air traffic, and historical data to forecast flight delays and improve punctuality.
2. Optimise routes — Identify the most fuel-efficient and cost-effective routes by analysing traffic data, distance, and demand patterns.

Source: Applications of Data Science, Chapter 4

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The question asks specifically about Airline Route Planning as a Data Science application. The source passages do not explicitly list airline tasks, so you are expected to apply general Data Science knowledge in context. Examiners look for two distinct, relevant points — each stated clearly in one line. Avoid repeating the same idea in different words. Common valid answers include: predicting delays, optimising routes, dynamic pricing, demand forecasting, and fuel efficiency analysis. Write any two with a brief justification for full marks.

(D) To search the house address of a relative on the Internet.

Genetics and Genomics uses data science to understand DNA's impact on health, analyze drug/disease reactions, and find individual biological connections — not for searching personal addresses.

The passage clearly states that data science applications in Genetics & Genomics include: understanding genetic issues, reactions to drugs and diseases, and individual genome/biological connections. Searching a house address is an everyday internet activity unrelated to genetics. Examiners expect students to identify the odd one out using the passage.

(c) Data Science

Data Science is a concept to unify statistics, data analysis, machine learning and their related methods in order to understand and analyse actual phenomena with data.

Source: Chapter 4, Lesson 4.1: No-Code AI for Statistical Data

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The passage directly defines Data Science with this exact phrase. Examiners expect you to identify the correct option and optionally write the supporting definition in one line. Avoid confusing it with Computer Science, which is broader and does not specifically unify statistics and machine learning in this context.

(b) Website

A website is not used for storing data in tabular format. CSV, SQL, and Spreadsheets are all standard formats for storing tabular data.

The source passage mentions that Orange can load data from CSV, Excel (Spreadsheet), and SQL formats — all tabular storage formats. A website is a medium for displaying information, not a tabular data storage format. Examiners expect you to directly identify the odd one out with a brief reason.