CTO Data Strategy & Analytics 2 — Questions and Answers
Question 1: A CTO wants to implement a data mesh architecture. What is the primary organizing principle of data mesh?
- Centralized data lake owned by IT
- Domain-oriented decentralized data ownership (Correct answer)
- Cloud-only data storage model
- Real-time streaming as the sole ingestion method
Correct answer: Domain-oriented decentralized data ownership
Data mesh decentralizes data ownership to domain teams, treating data as a product owned by the team closest to it.
Question 2: Which metric best measures the business value of a data analytics initiative?
- Number of dashboards created
- Volume of data processed per day
- Revenue or cost impact attributable to data-driven decisions (Correct answer)
- Query response time in milliseconds
Correct answer: Revenue or cost impact attributable to data-driven decisions
Business value is best measured by tangible outcomes like revenue uplift or cost savings tied to decisions enabled by analytics.
Question 3: A company is choosing between a data warehouse and a data lake. Which scenario favors a data lake?
- Structured financial reporting with strict schema
- Exploratory ML workloads on raw, unstructured sensor data (Correct answer)
- BI dashboards requiring sub-second query response
- Regulatory compliance reports with fixed formats
Correct answer: Exploratory ML workloads on raw, unstructured sensor data
Data lakes store raw, schema-on-read data and are ideal for exploratory analytics and machine learning on unstructured sources.
Question 4: What does a data catalog primarily provide to an organization?
- Automated data backup and recovery
- Discoverable metadata inventory of data assets across the enterprise (Correct answer)
- Real-time data replication between systems
- ETL pipeline orchestration
Correct answer: Discoverable metadata inventory of data assets across the enterprise
A data catalog provides a searchable metadata registry so data consumers can discover, understand, and trust available data assets.
Question 5: A CTO must ensure analytics workloads do not degrade production OLTP performance. The best architectural solution is:
- Add more indexes to the OLTP database
- Replicate data to a dedicated OLAP system or read replica (Correct answer)
- Run analytics queries during off-peak hours only
- Compress all OLTP tables to reduce I/O
Correct answer: Replicate data to a dedicated OLAP system or read replica
Separating OLTP and OLAP workloads by replicating to a dedicated analytical system prevents resource contention.
Question 6: In data governance, what is the role of a data steward?
- To write ETL pipeline code
- To physically store and back up data assets
- To define, monitor, and enforce data quality and usage policies for a domain (Correct answer)
- To approve infrastructure spend for data platforms
Correct answer: To define, monitor, and enforce data quality and usage policies for a domain
Data stewards are responsible for maintaining data quality, lineage, and policy compliance within their assigned domain.
Question 7: Which technique is most appropriate when a company needs near-real-time analytics on continuously arriving event data?
- Nightly batch ETL into a data warehouse
- Lambda architecture with stream and batch layers (Correct answer)
- Daily CSV exports to spreadsheet tools
- Weekly full-table snapshots
Correct answer: Lambda architecture with stream and batch layers
Lambda architecture combines real-time stream processing with batch processing to serve low-latency, accurate analytics on event streams.
CTO Data Strategy & Analytics 2
A CTO wants to implement a data mesh architecture.
What is the primary organizing principle of data mesh?