Course details

Data Driven Organizations

Data Driven Organizations

Expected Duration
Lesson Objectives
Course Number
Expertise Level


Examine data-driven organizations, how they use data science, and the importance of prioritizing data in this 13-video course. Data-driven organizations are committed to gathering and utilizing data necessary for a business holistically to gain competitive advantage. You will explore how to create a culture within an organization by involving management and training employees. You will examine analytic maturity as a metric to measure an organization's progress. Next, learn how to analyze data quality; how it is measured in a relative manner, not an absolute manner; and how it should be measured, weighed and appropriately applied to determine the value or quality of a data set. You will learn the potential business effects of missing data and the three main reasons why data are not included in a collection: missing at random, missing due to data collection, and missing not at random. This course explores the wide range of impacts when there is duplicate data. You will examine how truncated or censored data have inconsistent results. Finally, you will explore data provenance and record-keeping.

Expected Duration (hours)

Lesson Objectives

Data Driven Organizations

  • Course Overview
  • 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