Rehashing is a technique used in dynamic hash tables when the load factor (ratio of entries to bucket size) exceeds a certain threshold. It ensures efficient lookup, insertion, and deletion operations.

Option A (Correct): A larger hash table is allocated in memory to accommodate more entries.

Option B (Correct): A new hash function is typically required to map keys into the expanded table range.

Option C (Correct): All key-value pairs from the old table are re-inserted (rehashed) into the new table using the new hash function.

Since all three conditions (A, B, and C) are true, the best choice is Option E (All of the above).

Python’s built-in data containers are widely used in data science and programming:

Lists (Option A): Ordered, mutable sequences.

Tuples (Option B): Ordered, immutable sequences.

Dict (Option D): Dictionaries, key-value data structures implemented using hash tables.

LinkedList (Option C): Python does not provide a native linked list as a built-in container. While linked lists can be implemented manually or through external libraries (e.g., collections.deque for efficient appends/pops), they are not part of Python’s main native containers.

Thus, the correct answer is Option C (LinkedList).

A Big Data Strategy document provides a framework for aligning data initiatives with organizational objectives. It typically includes:

Business strategy (Option A): Ensures that big data initiatives align with overall corporate strategy.

Key decisions (Option B): Identifies the decisions data will help optimize or automate.

Key business initiatives (Option D): Links big data projects with critical organizational initiatives.

Key business entities (Option E): Defines the core entities (customers, products, channels) around which data will be organized.

However:

Business decisions (Option C): This is redundant and not a standard section; "key decisions" covers this aspect already.

Thus, the correct answer is Option C (Business decisions).

Inductive learning techniques in machine learning (such as decision trees, neural networks, or SVMs) follow a systematic sequence of steps for classification:

Training Step (i): A model is built using training data, where the system learns relationships between features and target labels.

Test Step (ii): The trained model is evaluated on unseen test data to measure its performance and generalizability.

Validation Step (iii): Often, a validation set is used to fine-tune model parameters, avoid overfitting, and choose the best model configuration.

Application Step (iv): The final validated model is applied to classify new, real-world data.

Since all four steps (i, ii, iii, iv) are essential to inductive classification, the correct answer is Option D (i, ii, iii, iv).

Optical Character Recognition (OCR) is the process of automatically recognizing and converting different types of documents — such as scanned paper documents, PDFs, or images — into editable and searchable text.

OCR systems use Machine Learning (ML) and Computer Vision techniques to detect and classify patterns of characters in images.

Algorithms like Convolutional Neural Networks (CNNs) are commonly used for image-based OCR.

While OCR may indirectly contribute to data mining or big data workflows, the core application is based on machine learning, where models are trained to classify and recognize text patterns.

Thus, OCR is primarily a Machine Learning application, making Option B correct.

JSON (JavaScript Object Notation) is a lightweight data-interchange format widely used for storing and exchanging structured or semi-structured data. JSON allows hierarchical (tree-like) structures, such as nested objects and arrays, to be serialized into a textual representation.

Option A (Plain text format): Correct. JSON files are stored as plain text, making them human-readable and language-independent.

Option B (Plain string format): Correct. JSON objects are transmitted as strings across networks (e.g., via APIs, RESTful services).

Option C: Incorrect. JSON does not serialize into “any format,” but specifically into text/string-based formats.

Option D: Correct. Since JSON is both plain text and transmitted as string format, the right answer is both A and B.

Option E: Incorrect.

Thus, JSON serializes hierarchical data into plain text and string formats.

The DevOps movement evolved as a natural extension of the Agile methodology.

Agile (Option A): Agile emphasizes iterative development, collaboration, and flexibility. While Agile improved software development speed, it created challenges in integrating development with IT operations. DevOps emerged to address this by bringing operations into the Agile cycle — enabling continuous integration, delivery, and deployment.

Waterfall (Option B): Incorrect. Waterfall is a rigid, sequential methodology, fundamentally opposite to the DevOps philosophy.

Promise-based algorithms (Option C): Not a methodology — irrelevant here.

Test-driven development and model-driven development (Option D): While these practices support DevOps, they are not the origin of the movement.

Thus, the DevOps movement is an outgrowth of Agile methodology.