CompTIA Data+: Data Acquisition & Cleansing

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. Data, when coming in from a source en masse, is rarely structured the way that data analysts would like it to be. When you consider the multitude of sources that data comes from, it would be highly unrealistic to assume that you could take a tranche of data and begin working with it without some sort of processing to make it more useful. In this course, you will explore data acquisition and cleansing, beginning with data integration and data integration tools, focusing on the roles and characteristics of the extract, transform, load (ETL) and extract, load, transform (ELT) processes. Then you will examine tools and methods such as delta load and data acquisition application programming interfaces (APIs). Next, you will learn how to clean datasets and investigate common data issues, including data redundancy, missing values, non-parametric data, and outliers. Finally, you will take a look at key characteristics of data type validation. This course can be used to prepare for CompTIA Data+ (DA0-001) exam.