Data cleaning through the years [a funny yet true timeline]
From stone tablets to artificial intelligence, researchers have always battled data quality issues, just with increasingly sophisticated tools (and increasingly creative fraudsters). Our lighthearted journey through history reveals that while technology evolves, the fundamental challenge remains: keeping data clean enough for reliable insights. Let’s explore how data cleaning has evolved from ancient times to today’s […]
Questions to ask during data analysis: 3 expert researchers weigh in
At dtect, we don’t do research – we make research better. While our platform works tirelessly to maintain data quality by keeping fraudulent participants out of your surveys, we’re constantly learning from researchers about what happens after data collection. Understanding how analysts approach their work helps us build better tools to protect data quality from […]
4 Keys to Developing a Robust Data Quality Strategy
Discover essential keys to developing a robust data quality strategy in market research. Learn how to ensure reliable data and gain a competitive advantage.
Show me where it hurts: The true cost of poor data quality
The data quality crisis in the market research industry has reached a tipping point. For years, conversations about the importance of data integrity have been circulating among professionals in the field, but there seems to be a new urgency around the issue. As the industry grapples with challenges posed by fraudulent responses, disengaged participants, an […]
5 steps to create an effective data quality management strategy
Data quality management (DQM) is a structured process for managing quality, checking validity, and maintaining integrity of market research data. The process covers the full workflow, including how study participants are vetted, and how data is collected, stored, processed, analyzed, and presented. Why is DQM important? Data is the most important asset a company has […]