Data preparation is an important aspect of data processing and analytics use cases. Business analysts and data scientists spend about 80% of their time gathering and preparing the data rather than analyzing it or developing machine learning models. Kelly Stirman spoke last week at Enterprise Data World…
Data preparation is an important aspect of data processing and analytics use cases. Business analysts and data scientists spend about 80% of their time gathering and preparing the data rather than analyzing it or developing machine learning models. Kelly Stirman spoke last week at Enterprise Data World 2017 Conference about the data preparation best practices.
Kelly talked about the differences between data preparation and data integration efforts. Data preparation is primarily done by Business Analysts using tools like Alteryx , Trifacta , and Paxata. Data integration has been an essential tool for IT and is performed by IT teams with the help of tools like Informatica , IBM , SAS, and SQL tools.
