What is the purpose of data quality control in assessment administration and name two common QC methods?

• A. To speed up data entry by removing validation.
• B. To centralize all data in a single system.
• C. To ensure accuracy, completeness, and reliability of data; methods include validation rules and reconciliations across sources.
• D. To reduce the need for audits.

Answer: (C)

Data quality control in assessment administration is about keeping information accurate, complete, and reliable for decisions that affect property values and taxes. When data is trustworthy, the valuation process rests on solid footing, and decisions are fair and defensible. Two common QC methods are validation rules and reconciliations across sources. Validation rules are checks built into data entry and processing that enforce required fields, correct data types, valid ranges, and logical consistency (for example, ensuring a date isn’t in the future or that an acreage value isn’t negative). Reconciliations across sources involve comparing data from different systems or feeds to spot and resolve inconsistencies, such as aligning parcel ownership, land area, and tax status between assessment rolls and parcel maps. These approaches help catch errors early, reduce gaps, and maintain the integrity of the dataset.