JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD B.Tech III DATA ANALYTICS Previous Question Paper (August - 2022 - R18)

Data is defined as raw, unorganized facts, figures, symbols, or observations that require processing to become meaningful information. It can exist in structured (relational databases), semi-structured (JSON, XML), or unstructured (text, images, video) formats.

Handling large collections of data, often referred to as Big Data, requires specialized techniques and architectures:

• Distributed Computing: Utilizing frameworks like Apache Hadoop or Spark to process data in parallel across clusters of commodity hardware.
• Storage Solutions: Using NoSQL databases (e.g., MongoDB, Cassandra) for unstructured data and Data Lakes for storing raw data at scale.
• Cloud Infrastructure: Leveraging cloud-based services (AWS, Azure, GCP) to provide elastic storage and scalable compute resources.
• Data Partitioning and Indexing: Organizing data into smaller, manageable chunks to improve query performance and retrieval speed.

Data is generated from a diverse array of sources, which can be categorized as follows:

• Transactional Systems: Operational data generated from daily business activities, such as point-of-sale systems, banking transactions, and e-commerce orders, typically stored in relational databases.
• Social Media and Web: Massive volumes of unstructured data from social platforms (tweets, posts, comments), search engine logs, and web scraping, providing insights into user behavior and sentiment.
• Internet of Things (IoT) Sensors: Real-time streaming data collected from smart devices, industrial machinery, wearables, and environmental sensors, which record continuous metrics like temperature, speed, or location.
• Machine-Generated Data: Log files from servers, applications, and network devices that track system performance, security events, and error reports.
• Public and Open Data: Datasets made available by government agencies, research institutions, and international organizations (e.g., census data, climate records) for public use.
• Multimedia Content: Digital assets including images, audio files, and video streams, which require advanced processing techniques like computer vision or natural language processing to extract value.