Data Analytics

Volume

Refers to the massive amount of data being generated that traditional methods struggle to handle.

Velocity

Denotes the speed at which data is produced and needs to be processed.

Variety

Indicates the diverse formats of data that require processing.

Authentication

Verifies the identity of users or systems accessing a resource, e.g., passwords or biometrics.

Authorization

Determines the actions authenticated users or systems are allowed to perform, e.g., Access Control Lists.

Centralized administration and audit

Involves managing security policies and logs from a central point for consistency.

Data at rest/in motion encryption

Involves converting data into coded form to prevent unauthorized access, e.g., SSL for data transmission.

Encryption

Process of converting data into coded form to prevent unauthorized access in data at rest and in motion.

Centralized key management

Managing cryptographic keys centrally within an organization.

User access control

Mechanisms to manage and restrict user access rights within an information system.

Intrusion detection and prevention

Detecting and responding to unauthorized activities within a network or system.

Physical security

Protecting personnel, equipment, and data from physical threats, e.g., CCTV cameras.

Principal Component Analysis

Pre-processing step in big data to clean and reduce data for analysis.

Standardization

Adjusting the range of continuous variables to contribute equally to the analysis.

Covariance Matrix Computation

Determines relationships between variables in the input set.

CNN (Convolutional Neural Networks)

Specialized deep learning algorithm for tasks like image classification.

Hadoop

Open-source framework for distributed storage and processing of large datasets.

Advantages of Hadoop

Can handle large data volumes, is cost-effective, replicates data, and versatile for various data types.

Disadvantages of Hadoop

Requires technical expertise, complex management, single point of failure, integration challenges, and data migration complexities.