Using Data to Find Data: Data Discovery & Exploration

Data Science
  • 12 Videos | 57m 12s
  • Includes Assessment
  • Earns a Badge
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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.

WHAT YOU WILL LEARN

  • recognize the differences between data exploration and data discovery
    list the components of the Exploratory Data Analysis framework, which is involved in finding data facts
    recall the tools that can be used to facilitate data Exploration
    describe how Knime can be used to apply data exploration and data finding methods
    describe the techniques that can be used to implement data transformation in order to get essential data attributes
    pivot data using Python to find informative data
  • recognize the need for data de-identification and describe data de-identification techniques
    recall the need for data quality analysis and the intended outcomes of the analysis
    recognize the need for data tracing and describe data tracing techniques
    describe the essential building blocks of finding data using data
    recall essential data exploration tools, identify critical data transformation and tracing techniques, and specify the building blocks of using data to find data

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 26s
    UP NEXT
  • Playable
    2. 
    Data Exploration vs. Data Discovery
    3m 39s
  • Locked
    3. 
    Exploratory Data Analysis Framework
    5m 7s
  • Locked
    4. 
    Data Exploratory Tools
    3m 56s
  • Locked
    5. 
    Data Exploration Using Knime
    6m 13s
  • Locked
    6. 
    Data Transformation Techniques
    5m 3s
  • Locked
    7. 
    Pivoting Data
    4m 40s
  • Locked
    8. 
    Data De-Identification Techniques
    3m 33s
  • Locked
    9. 
    Data Quality Analysis
    6m 58s
  • Locked
    10. 
    Data Tracing Approach
    3m 58s
  • Locked
    11. 
    Finding Data Using Data
    3m 46s
  • Locked
    12. 
    Exercise: Find Data with Data
    3m 54s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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