.BLD() Tech Talk: Data cleaning - Techniques for identifying and filling in missing values
This evening, we will focus on data engineering. How to identify missing data and how to fill missing data. We have two amazing speakers with lot's of experience in data engineering who will share their knowledge about these interesting topics!
Identifying Missing Data 🎤 Speakers: Frances Dreyer
When you get a dataset for the first time then going back to basics is always a good idea. Does your data have missing data? What does this mean? Do you have to worry about the missing data? Can you just remove it or should you try to fill it? What method should be used for filling the data and how do you know if you can just remove it? These are all questions that should go through your head when you receive data for the first time.
#About: Frances Dreyer
Data engineer at Capgemini, 5 years of experience, Talking about solutions including Big data and bikes are certainly topics that she is always keen on talking.
Filling Missing Data 🎤 Speaker: Andre Marques
To fill the gaps or not to fill the gaps? That is the question. Should you fill the gaps in the missing data or should you just remove the missing data? This is a question we all have when working with datasets that have missing data. The answer depends on the type of missing data as well as the type of data you have.
#About: Andre Marques
Data engineer at BlueHarvest, 10 years of experience, he sees data everywhere !
What the .BLD() Community is all about
Group of Capgemini software experts, friends and others who have a passion for tech! | Because we love to share our knowledge! | Every 2nd Tuesday of the month | Check all our Tech Talks on our Youtube channel.
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