Data Operations Quiz_2

What is the main problem with poor data quality?

• Increases the cost of storage

• Reduces accuracy of models and decisions

• Makes data collection faster

• Eliminates the need for machine learning

What is a major challenge for data scientists despite their high qualifications?

• Lack of programming knowledge

• Need to learn organizational culture and leadership skills

• Inability to work with machine learning

• Over-dependence on automation

What is the most commonly used traditional data science method?

• TDSP

• SEMMA

• CRISP-DM

• Agile

Why is CRISP-DM considered less effective for modern data science?

• It does not emphasize iterative improvements

• It is too expensive to implement

• It lacks a structured workflow

• It is focused on cloud computing

How does DataOps ensure secure tracking and management of data?

• By enforcing strict manual oversight

• By integrating with cloud platforms

• By restricting data access

• By eliminating the need for compliance

What business model do DataOps tools like Snowflake use?

• One-time purchase

• Subscription-based services (SaaS)

• Open-source only

• Pay-per-use cloud storage

In the Waterfall software development model, which phase comes after testing?

• Maintenance

• Design

• Deployment

• Programming

What is the purpose of data ingestion in DataOps?

• Removing duplicate records

• Gathering data from multiple sources and storing it centrally

• Transforming raw data into meaningful insights

• Cleaning incorrect or incomplete data

What is the most valuable type of data analytics for decision-making?

• Descriptive analytics

• Diagnostic analytics

• Predictive analytics

• Prescriptive analytics

What is a "unicorn" data scientist?

• A data scientist who specializes only in coding

• A data scientist skilled in coding, machine learning, business knowledge, and communication

• A data scientist who focuses only on deep learning

• A data scientist who works exclusively with IT teams