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Answer: Clustering
Clustering (K-means, hierarchical, DBSCAN) discovers natural groupings in unlabeled data. Applications: customer segmentation, anomaly detection, document organization.
Answer: Time Series Forecasting
Time series forecasting (ARIMA, Prophet, LSTM) models temporal patterns for demand prediction, anomaly detection, capacity planning. Critical for business planning and operations.
Answer: True
Data minimization (DPDP Act, GDPR) limits collection to what's necessary for specified purpose. Reduces privacy risks, storage costs, breach impact. Critical for responsible AI data practices.
Answer: All of these
Proportion visualization: bar charts for clear comparison, pie charts for part-to-whole (limited categories), stacked bars for multiple groups. Choice depends on data and audience.
Answer: Scatter
Scatter plots display individual data points for two variables, revealing correlations, clusters, outliers. Foundation for regression analysis and exploratory data science.
Answer: True
Bias in training data or model design can lead to discriminatory outcomes. Mitigation: diverse datasets, fairness metrics, bias audits, human oversight. Critical for ethical AI deployment.
Answer: Transparency
Transparency (Explainable AI/XAI) ensures AI decisions can be interpreted by humans. Techniques: LIME, SHAP, attention visualization. Critical for trust, debugging, regulatory compliance.
Answer: Integration / Warehousing
Data integration combines disparate sources via ETL/ELT, virtualization, or federation. Enables unified analytics, reporting, and decision-making. Critical for enterprise data strategy.
Answer: Multi-Site Active-Active
Active-active runs full workload in multiple regions simultaneously, enabling instant failover with zero RPO/RTO. Highest cost but maximum resilience. Critical for mission-critical systems.
Answer: Serverless / Athena
Serverless query engines (AWS Athena, Google BigQuery) enable SQL queries directly on data in object storage using schema-on-read. Eliminates ETL for ad-hoc analysis. Pay-per-query pricing.
Answer: All of these
IaC (Terraform), Configuration Management (Ansible), GitOps all use version-controlled code to define infrastructure state. Enables repeatability, auditability, peer review, automated testing.
Answer: True
Data lakes (S3, ADLS) store raw structured/unstructured data for flexible analysis; data warehouses (Snowflake, Redshift) store curated, schema-on-write data for BI. Modern: lakehouse pattern combines both.
Answer: All of these
Managed Kubernetes: EKS (AWS), AKS (Azure), GKE (GCP) handle control plane, updates, scaling. Abstracts infrastructure while retaining container flexibility. Critical for cloud-native development.
Answer: Parquet
Parquet is columnar storage format optimized for analytics: efficient compression, predicate pushdown, schema evolution. Reduces I/O by reading only required columns. Used in Spark, Hive, Presto.
Answer: True
Serverless (Lambda, Cloud Functions) auto-scales based on demand, charges per execution. Trade-offs: cold starts, vendor lock-in, execution limits. Critical for cost-optimized cloud design.
Answer: All of these
Resilience patterns: self-healing replaces failed instances, circuit breaker prevents cascading failures, retry logic handles transient errors. Combined for fault-tolerant cloud applications.
Answer: OECD
OECD AI Principles (2019) provide values-based guidelines: inclusive growth, human-centered values, transparency, robustness, accountability. India endorses for domestic policy alignment.
Answer: True
National Cyber Security Strategy (draft) addresses: critical infrastructure protection, cyber diplomacy, capacity building, public-private partnerships. Foundation for India's cyber defense posture.
Answer: Data Protection Board
Data Protection Board of India (under DPDP Act 2023) adjudicates disputes, imposes penalties, enforces compliance. Distinct from CERT-In (cyber incidents) and MeitY (policy).
Answer: FOSS / Free and Open Source Software
MeitY's FOSS policy encourages government adoption of open-source for cost-effectiveness, security, and vendor independence. Critical for sustainable digital governance.