DATA PREPARATION – TACKLE THE MOST EFFORT-PRONE PHASE IN DATA PROJECTS
The most effort-consuming phase in data science projects is data preparation. No standard procedure exists that covers all potential data preparation issues. In this seminar, you will learn how to increase the efficiency of data preparation in order to gain faster insights into your data using data analytics.
From a process point of view, the CRoss-Industry Standard Process for Data Mining (CRISP-DM) describes six major steps for any data analysis project. After having gained Business Understanding, we need to identify and semantically understand the required data (Data Understanding). This requires domain knowledge as well as data engineering and data analysis knowledge. Therefore, Data Understanding is the starting point for Data Ingestion and Data Preparation.