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Data Science 2: Data Driven Organizations

Data Science 2: Data Driven Organizations


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

In order for an organization to be data science aware, it must evolve and become data driven. In this course, you will examine the meaning of a data driven organization and explore analytic maturity, data quality, missing data, duplicate data, truncated data, and data provenance.



Expected Duration (hours)
1.2

Lesson Objectives

Data Science 2: Data Driven Organizations

  • describe what it means to be data driven and the importance of it for an organization
  • recognize how to enable data-driven decision making
  • identify the different levels of analytic maturity
  • identify the different types of roles required in data driven organizations
  • prioritize resources appropriately
  • describe the aspects of data quality
  • use PowerBI Desktop to visualize and manipulate a dataset
  • describe the importance of dealing with missing data and use Azure Machine Learning Studio to clean it up
  • describe the importance of identifying and dealing with duplicates using Azure Data Explorer
  • describe what truncated data is and how to remove it using Azure Automation
  • describe data provenance
  • use Informatica Data Quality
  • Course Number:
    it_dsevtddj_01_enus

    Expertise Level
    Intermediate