DATA MINING PREPARATION: PROCESS, TECHNIQUES AND MAJOR ISSUES IN DATA ANALYSIS

Abstract

Data preparation is an iterative-agile process for exploring, combining, cleaning and transforming raw data into curated datasets for self-service data integration, data science, data discovery, and BI/analytics. To perform data preparation, data preparation tools are used by analysts, citizen data scientists and data scientists for self- service. The tools are also used by citizen integrators and data engineers for data enablement to reduce the time and complexity of interactively accessing, cataloging, harmonizing, transforming and modeling data for analytics in an agile manner with metadata and lineage support. These tools can provide data access for use in mostly analytical tasks that include storage, logical and physical data modeling, and data manipulation for data visualization, data integration and analytics. Some tools support machine-learning algorithms that can recommend or even automate actions to augment and accelerate data preparation. Keywords: Data Mining, Data preparation, Data Analysis, Big Data Analytics