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Data Science 2: Data Driven Organizations

Data Science 2: Data Driven Organizations

Expected Duration
Lesson Objectives
Course Number
Expertise Level


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)

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:

    Expertise Level