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Data scientists typically have strong skills in areas such as Python, R, statistics, machine learning, and data analysis. Believe it or not, these skills are valuable in data engineering for datawrangling, model deployment, and understanding data pipelines.
Data Integration Tools Technologies such as Apache NiFi and Talend help in the seamless integration of data from various sources into a unified system for analysis. Understanding ETL (Extract, Transform, Load) processes is vital for students. Students should learn about datawrangling and the importance of data quality.
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