It's an older one, but a good one about the importance of Data Quality from Horst Feldhaeuser. "Employing real-time monitoring and applying data validation checks as survey responses are collected can help to identify and address data errors or inconsistencies before it is too late." https://lnkd.in/eA3cP6aH #dataquality #surveytogo
Dooblo - SurveyToGo’s Post
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🚨 Is your data working for you or against you? 🚨 Bad data can cost your business more than just dollars—it can lead to flawed strategies, missed opportunities, and a compromised reputation. In our blog by Todd Eviston (SVP, Operations), he reveals how our Sentinel System identifies and eliminates fraudulent respondents, ensuring your insights are accurate and actionable. Discover how we’re staying ahead of the game in the fight for data quality, leveraging both human expertise and cutting-edge technology to protect your research integrity. 💡 📖 Read the full blog here: https://bit.ly/4ef0Kev #MRX #DataQuality #MarketResearch #Insights #AdvancedAnalytics #QuantitativeResearch #CRResearch
The Cost of Bad Data: Why Data Quality is More Important Than Ever | C+R
crresearch.com
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"What IS iMAD?" We've been posting a new blog series that highlights each letter in the "iMAD" name, introducing you to what we're all about, and telling you a little more about our core values. In this fourth and final post, we bring you: "D - Data Quality: A Comprehensive Approach". Aside from bringing awareness to the foundations of the iMAD name, this is also an educational post that outlines exactly what researchers should be looking for when it comes to choosing a panel provider. To read the full post, click here: https://lnkd.in/d_2B--qC #dataquality #onlinesurvey #panelprovider #mrx #marketresearch #consumerinsights #humaninsights John Wulff, CAIP
Data Quality: A Comprehensive Approach
https://imadresearch.com
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🔍 The Cost of Bad Data: Why Data Quality is More Important Than Ever 🛡️ In today’s fast-paced business world, data is everything—but only if it's accurate. Bad data can lead to misguided strategies that risk millions of dollars, all because of compromised insights. At C+R Research, we take data quality seriously. In a recent blog, Todd Eviston, Senior Vice President of Operations, explains how our Sentinel System combats bad actors in survey data, ensuring that the insights driving your business decisions are reliable and trustworthy. From pre-survey screening to post-survey analysis, our multi-layered approach to data integrity has removed up to 47% of fraudulent respondents in key studies, protecting your business from inaccurate insights. Discover how data quality impacts your strategy and how C+R is leading the charge in maintaining the highest standards in market research. 📖 Read the full blog here: https://bit.ly/3MG4Ujk #MRX #DataQuality #MarketResearch #Insights #AdvancedAnalytics #QuantitativeResearch #CRResearch
The Cost of Bad Data: Why Data Quality is More Important Than Ever | C+R
crresearch.com
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Are Likert scales accidentally hurting your data? From unclear labels to ‘oops’ moments with biased wording, even experienced researchers can make mistakes. Our latest blog post explores 5 common errors and what you can do to solve them. Read it now: https://lnkd.in/gqenZFSn
5 Mistakes You’re Making With Your Likert Scales
blog.intellisurvey.com
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📊 Tackling the ever-evolving landscape of Data Quality is essential to achieving trustworthy insights in our industry! This latest article explores the key challenges impacting data quality today and provides strategies to address these head-on. From survey fraud to response bias, data quality remains one of the biggest hurdles for researchers. Dive into these insights to see how you can keep pace with these challenges and ensure high-quality, reliable data for your projects! Read more here: https://lnkd.in/d3i3jVyg #DataQuality #MarketResearch #ESOMAR #Insights Enric C. Xabier Palacio Ajitha Lakshmi Gopalakrishnan Lilas Ajaluni
Keeping up with the data quality challenges
researchworld.com
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Data masking is the best way to anonymize and protect sensitive data in non-production environments. Find out why in our latest blog: https://lnkd.in/eVYAE8q7
Data Masking vs. Data Anonymization | What’s the Difference? | Delphix by Perforce
delphix.com
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https://lnkd.in/dtyqjc_r The second article of three. This describes data types and some of its uses. Again, thanks to Kelly Wright for her work on this project.
Qualitative vs. quantitative data
ems1.com
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Precisely highlights how every organisation's path to data integrity is unique. Build trust and maximise the value of your data. 📊✨ Read more: https://lnkd.in/eNsd2ydg
The Path to Data Integrity: Each Journey is Unique
business-reporter.co.uk
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Dear Researchers, Data quality remains a significant challenge for many of us in the field of market research. To understand the breadth and depth of this issue, we conducted an extensive study spanning 18 countries. Our research included 103 market research companies and independent consultants, totaling 117 participants. Among these participants, 37% were top and senior-level management, 32% were market research consultants, and 31% were middle-level management. The findings were revealing: a striking 78% of market research professionals regularly face data quality issues, even when employing various techniques to mitigate them. The specific problems reported include: Bias: 36% Speeders: 37% Outliers: 31% Mono answers: 21% Junk/bad data: 27% Data inconsistency: 26% Data discrepancy: 18% These issues collectively impair the accuracy of the insights we derive, hampering our ability to make informed decisions. In response to these findings, our team has developed a comprehensive solution aimed at eradicating these data quality challenges. You can find more details about our approach in the attachment below. Let's work together to enhance the quality of our data and, consequently, the value of our research. #DataQuality #MarketResearch #ResearchInsights #DataChallenges #InnovationInResearch
Navigating through data quality challenges in market research: exploring the roadblocks to reliable insights and actionable data In market research, data cleaning and validation are industry standards. Similarly, fraud detection is also actioned by most of the market research companies through various platforms that track location, IP address, device, proxies, etc. However, ensuring the authenticity and genuineness of the collected data still remains a challenge. To explore this issue, we conducted a study across 18 countries, comprising 103 market research companies and independent consultants, involving 117 participants. These participants included 37% top and senior-level management, 32% market research consultants, and 31% middle-level management. The study highlighted that 78% of market research professionals encounter data quality challenges, despite using various techniques. Issues arise from bias (36%), speeders (37%), outliers (31%), mono answers (21%), junk/bad data (27%), data inconsistency (26%), and data discrepancy (18%). These challenges hinder the accuracy of insights. Industry experts have been meticulously working to overcome these challenges. After extensive efforts, we developed a solution using a statistical perspective to improve data quality: the Data Quality Score Module. It comprises 6 parameters: outliers, speeders, mono answers, junk/bad data, data inconsistency, and data discrepancy, including fraud detection. This acts as a bridge between data collection and data processing by flagging the poor-quality data at the respondent level, which helps researchers distinguish between authentic and unreliable responses. Let’s work together in overcoming the existing data quality challenges and move towards bias-free data. #MarketResearch #DataQuality #ResearchInsights #SurveyResults #DataChallenges #SamplingMethods #DataIntegrity #ResearchConsulting #IndustryTrends #ProfessionalInsights #DataManagement #BusinessResearch #QualityData #MarketAnalysis #ResearchProfessionals
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"When the data you need is locked behind a report request form that takes two weeks to process." #DataHeartbreak alert: Limited access equals limited impact. Analysts can’t perform magic without the right data in their hands. Solution? Push for democratized data access. Build guardrails, not walls. What’s your strategy for striking the balance between accessibility and governance? Let’s discuss!👇 #DataAccess #DataGovernance #AnalyticsLife
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