• Unit 4: Types of Data

    Data is, naturally, at the heart of DDDM. Numerous types of data and sources must be included in a robust DDDM initiative. Every type of data must be extracted from a source, transformed into a standard format acceptable for the data warehouse, and then made available for analysis. Once data is prepared, there are four types of analytics. Each one requires specific tools and well-formed queries to create both hindsight and foresight analytics. You will need to understand these types of analytics and how they relate to successful DDDM initiatives. This unit will cover different types of data and how they can be used, both individually and together, to generate insights into business operations and customers. We will also explore the role of "big data" in building a DDDM enterprise and how certain types of data can create additional complexity in analysis.

    Completing this unit should take you approximately 4 hours.

    • 4.1: Quanitative Data

    • 4.2: Qualitative Data

    • 4.3: Big Data

    • 4.4: Types of Analytics

    • Study Guide: Unit 4

      We recommend reviewing this Study Guide before taking the Unit 4 Assessment.

    • Unit 4 Assessment

      • Receive a grade