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Why should you care about data cleaning and how can you get started with the process right away? In this video, we explore the relevance of data cleaning and provide 5 guiding steps as well as caveats that’ll help you dive into the process right away 🌟 This saying means that you can put a lot of thought and effort into your data analysis and come up with lots of results. However, these results will mean nothing if the input data is not accurate. In fact, the results may even be harmful as they can misrepresent reality Cleaning and ordering this data can be a time-consuming process. Indeed, aggregating data from all these different data sources and making them compliant can take weeks or even months. This holds especially true for international companies. These often use different systems in different countries to record the same data 💽 🏁 But where do you start? In answering this question, we will touch upon: 💡updating data 💡checking for unique identifiers 💡missing values 💡numerical outliers 💡defining valid and removing invalid data values Want to dive deeper into data cleaning in HR? We have an in-depth article for that 👇 https://www.analyticsinhr.com/blog/hr... Also, you can find here access to the following resources: Link to how to calculate the interquartile range: https://en.wikipedia.org/wiki/Interqu... Link to Global Data Integrity Course: https://www.aihr.com/global-data-inte... Feel free to out our HR analytics + digital human resources management courses and certification programs: 🎓 Learn everything you need to drive data-driven decision-making in HR (certificate program) 💥 https://bit.ly/3c6UQN8 🎓 Get the skills you need to use technology to make HR more effective (certificate program) 💻 https://bit.ly/2VjsdGm Have a greater strategic impact with data as an HR Business Partner 🎯 https://bit.ly/2vZou6a Can’t decide? You can access all our courses and certificate programs with our full academy license 👩🎓 https://bit.ly/2w4k9P1 👋👋 P.S. Follow us on LinkedIn for the latest HR Analytics developments! / aihr