Data Quality and Validation in IoT

Question ^*

What data validation methods are you currently using? (Select all that apply)

1. A) Threshold-based checks,B) Range checks,C) Data type validation,D) Statistical analysis,E) Manual review,F) No validation methods,G) Other (Please specify)

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Question ^*

What types of data quality issues cause the most significant problems for your decision-making?

1. A) Incorrect sensor readings,B) Delayed data delivery,C) Data loss,D) Data duplication,E) Lack of data context,F) All of the above

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Question ^*

What features are most important to you in an IoT data quality and validation solution? (Select top 3)

1. A) Automated data cleansing,B) Real-time anomaly detection,C) Customizable validation rules,D) Data lineage tracking,E) Alerting and notification capabilities,F) Integration with existing systems,G) Data visualization and reporting

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Question ^*

What is the biggest challenge you face with data quality in your IoT deployments?

1. A) Inconsistent data formats,B) Missing data,C) Sensor inaccuracies/noise,D) Data latency,E) Data security breaches,F) Other (Please specify)

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Question ^*

How important is real-time data validation in your IoT applications?

1. A) Critical - Requires immediate validation,B) Important - Validation needed within minutes,C) Somewhat important - Validation can be delayed,D) Not very important - Validation is a secondary concern,E) Not at all important

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