Think about your data intelligently and ask the right questions Key FeaturesMaster data cleaning techniques necessary to perform real-world data science and mac

Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and incorrect business

Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME W

Data Science: A First Introduction focuses on using the R programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective

Get your raw data cleaned up and ready for processing to design better data analytic solutions Key FeaturesDevelop the skills to perform data cleaning, data int