
edXOrganizations are decision factories—employees at every level make choices that shape competitive advantage. This course teaches you to mine data effectively and feed robust foresight into decision-making. You'll inventory your organization's actual decisions and their data needs, learn to work with incomplete data, and extract insight from experience. Then explore emerging trends: low-code/no-code analytics tools for non-technical staff, and AI/RPA-powered analysis using R and Power Platform. Ideal for leaders elevating decision quality.
What makes a good business decision?
How can we combine effective data analytics and feed robust foresight and scenario planning processes?
We need to rethink the organization, and see it as essentially a “decision factory.” Like a factory, employees at all levels make or contribute to decisions that, taken together, gives the organization the competitive edge in the marketplace. The news media is filled with stories of how a minor decision has major ramifications on the organization. In this course, we will learn how to train organizational members to effectively data products in their business decisions.
Digital organizations capture an enormous amount of data. Knowing how to mine and refine that data for strategic decision making effectively is what will separate the winners from the losers. As the business guru, Dr. Roger L. Martin, wrote in a 2013 Harvard Business Review article, knowledge workers turn the "raw material" of data into decisions. Decision-makers need the best data to make the best decisions.
This course will help your organization inventory the decisions its customers, employees, and leaders make and their data needs. We will discuss how to make good decisions and build quality data creation processes. You will also learn how to work with incomplete or ambiguous data and how to learn effectively from experience.
We will close out the course by examining two recent trends in data analytics. The first trend is the use of low-code/no-code tools by non-technical employees to create data applications. We will discuss best practices for creating low-code/no-code applications while providing a robust data infrastructure for the apps.
The second trend is the use of artificial intelligence (A.I.) and robotic process automation (RPA) in data analytics. We will examine the use of these tools, along with two of the most popular advanced data analysis tools: R and Microsoft's Power Platform.
This course is a high-level view of topics that we will explore in greater depth in the Architect certification portion of this program.
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Tracking since 1 Aug— not enough history yet to tell you whether today's price is any good. Watch the course and we'll tell you when it drops.
This is what we recorded in US pricing — not every price this course has ever had, and prices differ by country.
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