How does data quality affect decision making and IT operations?

• A. Data quality has no impact on IT operations
• B. Poor data quality leads to wrong decisions, degraded analytics, and increased remediation costs
• C. Data quality only affects storage costs
• D. High data quality causes longer processing times

Answer: (B)

Data quality directly affects both decision making and IT operations. When data is accurate, complete, timely, consistent, and unique, decisions are based on trustworthy inputs and analytics produce reliable insights, so actions taken are more likely to yield the desired outcomes and risks are better managed.

When data quality is poor, you get wrong conclusions because dashboards, reports, and models are fed with faulty information. That leads to degraded analytics—forecasts, trends, and anomaly detections become unreliable—and decisions based on those insights end up misdirecting resources or introducing new risks. In IT operations, bad data fuels misdiagnosed incidents, incorrect capacity planning, and ineffective automation, which translates into higher remediation costs as you spend more time cleaning data, reconciling records, and implementing governance measures. Overall, poor data quality increases rework, slows response times, and drains resources.

Some misconceptions people have are that data quality only affects storage costs or that making data high quality automatically slows processing. In reality, while quality checks add some overhead, the benefits—more accurate decisions, trusted analytics, and fewer costly fixes—greatly outweigh the extra processing time.