Using Data to Find Data: Data Discovery & Exploration

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. Explore essential approaches of deriving value from existing data in this 12-video course. Learn to produce meaningful information by implementing certain techniques such as data cleansing, data wrangling, and data categorization. The course goal is to teach learners how to derive appropriate data dimension, and apply data wrangling, cleansing, classification, and clustering by using Python. You will examine such useful data discovery and exploration techniques as pivoting, de-identification, analysis, and data tracing. Learn how to assess the quality of target data by determining accuracy of the data being captured or ingested; data completeness; and data reliability. Other key topics covered include data exploration tools; Knime data exploration; data transformation techniques; and data quality analysis techniques. The concluding exercise asks learners to list prominent tools for data exploration; recall some of the essential types of data transformation that can be implemented; specify essential tasks that form the building block to finding data with data; and recall essential approaches of implementing data tracing.