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Are your numbers correct? Does it add up? Data checking for quantitative research – Best practice/ Tips and tricks (from design to QC checks)
November 10 @ 1:30 pm – 2:00 pm
|Speaker: Evgeny Zlatkovsky from N’counter, Germany|
Convenor: Alexander Rummel, Aurum Research and LDC member
In market research, great value is placed on data quality. Insights are the basis for making decisions about important questions for products and services. Good and correctly applied data cleaning is standard and is often necessary for valid, meaningful results. The data collected should always meet the requirements of the quality guidelines for market research results – even with fast studies under time pressure. For meaningful, target-oriented results and a good basis for decision-making, the data must be free of so-called risks of distorting results. The final insights should therefore have gone through data cleaning in any case. Data cleaning is the automated or manual sorting out of cases that do not meet certain quality criteria in surveys or that provide inconsistent answers. The aim of data cleaning is to improve the data quality and thus the validity and informative value of survey results.
This webinar will focus on the various parameters which can spoil the data (e.g., doublets, “speeders”, outliers, improper open-ended entries), how to find them in the raw data and how to exploit them for a sustained improvement of the results. The real challenge herewith is not just to catch such cases that do not meet the requirements but to perform it quickly, ideally while the fieldwork is still running.
Special software that is focused on the data cleaning will be shown and some examples of outcomes will be given.
The webinar is for anyone interested in data, professionals, and learners.
After finishing the Moscow State University with a diploma in sociology, Evgeny decided in favour of market research and remained loyal for fifteen years to this fascinating activity. During this time, Evgeny gathered plenty of experience in the different fields and technics, with a strong focus on healthcare research. Evgeny managed a healthcare research unit of a renowned agency for many years.
After that, he changed to data analysis and runs for more than a decade an agency for data analysis and software development.