The Importance of Data Cleaning and Preprocessing in Data Science

In modern business, data is the backbone of decision-making processes, helping organisations make decisions, choose trends, and solve complex problems. However, raw data collected from multiple sources is often messy, inconsistent, and error-prone. Of course, data cleansing and preparation are fundamental to any successful data-driven project. If you are one of the many venturing towards this field, opting for a data science course in Mumbai can help you develop the necessary skills to decipher data! In this article, we will learn why data cleaning and preprocessing are so crucial in data science, take a deep dive into the methods and best practices, and see how this influences the outcome of any project. What is Data Cleaning and Preprocessing? In data cleaning, we aim to increase the reliability of inaccurate, inconsistent, and error-prone raw data by identifying and correcting it. The opposite of preprocessing is transforming raw data into a format that allows it to be analyse...