Fix Non-English Text in Excel - Fix Unreadable Multilingual Text in Excel

If you work with non-English text data in Excel, you have probably experienced one of the most frustrating issues in data handling. You open your dataset, expecting to see words in Arabic, Urdu, Chinese, Persian, or another language, but instead you see strange symbols, broken characters, or unreadable text. This problem is extremely common, especially in multilingual research, and it usually happens because of incorrect file encoding. In this video, Dr. Muhammad Awais explains clearly and step by step how to fix this issue and make Excel properly display non-English text without losing your original data. For one on one guidance, send an email at mawwaisgill@gmail.com In this tutorial, you will learn a practical and reliable solution using Excel’s built in import tools. Instead of opening the file directly, you will use the From Text or CSV option under the Data tab. This method allows Excel to read the file using the correct encoding, which is usually UTF 8 for multilingual text. The video walks you through the entire process. First, you open Excel and go to the Data tab. Then you choose From Text or CSV and select the file containing your non-English text. At this stage, Excel shows a preview window where the text appears correctly because the encoding is handled properly. Once you confirm and load the data, the sheet contains readable characters instead of strange symbols. The next crucial step demonstrated in the video is saving the file correctly. Even if you have loaded the data properly, saving it in the wrong format can reintroduce the same problem. That is why Dr. Awais shows how to use the Save As option and choose CSV UTF 8 delimited format. This ensures that the file retains the correct encoding, so the text remains readable whenever it is opened again or used in other software. The video also includes a comparison between the original corrupted file and the corrected version. When you open the original file, the characters are broken. When you open the updated UTF 8 version, the words appear clearly. This visual comparison helps viewers understand the impact of encoding and why this method works. This tutorial is particularly important for people working in research and data analysis. If you are dealing with multilingual survey responses, social media data, interview transcripts, or documents in different languages, encoding issues can slow down your work and lead to errors. Properly displayed text is essential before moving into coding, thematic analysis, text mining, or statistical analysis. Students conducting theses or dissertations often face this problem when collecting data from non-English contexts. Researchers working with international datasets, digital humanities scholars, communication researchers, and social scientists frequently encounter encoding problems. This video gives them a simple solution that prevents future complications. Correct encoding also matters when using other analysis tools. Software such as NVivo and MaxQDA, which are used for qualitative data analysis, depend on clean text input. If characters are corrupted, coding becomes inaccurate. Similarly, programming environments like R and Python require properly encoded text for text analysis, natural language processing, and computational research. Fixing encoding at the Excel stage saves time and prevents technical errors later. Another important point highlighted in the video is that this issue is not limited to one language. Although Arabic text is shown in the example, the same method applies to Urdu, Persian, Chinese, and many other languages that use non-Latin scripts. The key concept is understanding encoding and ensuring that Excel reads the file in UTF 8. The tutorial is designed to be easy to follow, even for beginners. You do not need advanced technical skills. The steps are simple, but the impact on your data quality is significant. Once you understand this method, you can confidently handle multilingual datasets without worrying about unreadable characters. Dr. Mohammad Awais also mentions his experience and expertise in data analysis tools. As a certified expert and trainer in NVivo and MaxQDA, he regularly works with qualitative and multilingual data. He also offers guidance in data analysis using R and Python. Viewers who need additional help with data collection, cleaning, organization, or analysis can reach out through the contact information shown in the video. This tutorial is part of a broader effort to make research methods and data analysis more accessible. Many data problems seem complicated, but they often have simple solutions once you understand the underlying issue. Encoding is one such problem. By learning how to handle it correctly, you improve the reliability of your research. #Excel #UTF8 #TextEncoding #MultilingualData #DataCleaning #ResearchMethods #NVivo #MaxQDA #Rstats #Python #QualitativeResearch #DataAnalysis