CompTIA Data+: Data Mining
Build a strong foundation in data acquisition, cleaning, and profiling. Master data manipulation, transformation, and query optimization to enhance data quality and performance across applications—all while preparing for CompTIA Data+ certification.
What you'll learn
In today's data-centric world, many organizations struggle to manage and prepare data effectively for analysis, facing challenges in data acquisition, cleansing, and manipulation. In this course, CompTIA Data+: Data Mining, you’ll gain the skills to efficiently handle, clean, and prepare data for analysis, enhancing its quality and usability. First, you’ll explore foundational data acquisition concepts, learning to gather and integrate data from various sources using methods like ETL, ELT, delta loading, and APIs. Next, you’ll discover best practices for data cleansing and profiling, focusing on techniques to address issues such as duplicate data, missing values, and outliers, ensuring data accuracy and reliability. Finally, you’ll learn to apply a range of data manipulation techniques—such as recoding, merging, concatenation, and normalization—and optimize data processing with functions like filtering, sorting, and query optimization to refine datasets effectively. By the end of this course, you’ll have mastered data preparation techniques for transforming raw data into clean, well-structured datasets ready for analysis, and also gained the skills needed to succeed on the CompTIA Data+ certification exam, giving you a comprehensive foundation to help drive informed decision-making and actionable insights within your organization.
Table of contents
- Introduction to Data Manipulation Techniques 2m
- Recoding Data and Derived Variables 4m
- Demo: Recoding Data and Derived Variables 1m
- Merging and Blending Data 4m
- Demo: Merging and Blending Data 1m
- Concatenation, Data Append, and Imputation 3m
- Demo: Concatenation, Data Append, and Imputation 2m
- Advanced Techniques: Reduction, Transpose, and Normalization 2m
- Demo: Reduction, Transpose, and Normalization 2m