Data Analytics
Description
Professionals in all industries rely on data to make decisions. By including data in your decision-making process, you can remove some of the guesswork that comes from relying solely on instincts and experience. This course will introduce you to the world of data analysis by exploring the Davenport-Kim three-stage model for quantitative analysis. You will learn about different analytical methods, data quality and management, and visual representations of data. You will also explore research standards and best practices, as well as challenges that may arise as you analyze data. This course will provide you with information you can use to better understand data and its importance in the business world.
credits
- PMI PDUs: 5
- Leadership PDUs: 2
- Strategic & Business Management PDUs: 1
- Technical PM PDUs: 2
- IACET CEUs: 0.5
- HRCI Credits: 5
- SHRM PDCs: 5
features
- Mobile-friendly
- Audio-enabled
- Badge and credit-awarding
- Fully accessible
- Games & Flashcards
- Expert-supported
- Video content
learning Outcomes
- Explain the value of analytics for an organization and define key terms related to data analysis
- Explain the stages of the Davenport-Kim three-stage model for analysis
- Describe different data collection methods
- Differentiate between qualitative and quantitative data
- Explain standard analytical techniques
- Describe the characteristics of high-quality data
- Describe the elements of data management
- Identify possible biases and errors within a data set
- Describe different graphical displays for a data set
- Describe common challenges associated with data analysis