Improving Digital Decisions with Machine Learning – Face-to-Face
$1,195.00
This course shows you how to effectively operationalize advanced analytics and data science in business processes by focusing on decisions first. You’ll learn how to define and scope the business problem, ensuring that analytics are useful in business terms. You’ll also find out how to operationalize the results and use analytical decision-making to innovate business processes.
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Learn how to operationalize the latest advanced analytic technologies such as data mining, predictive analytics, machine learning, and artificial intelligence to become more data-driven and drive business process innovation.
Is your organization using the latest advanced analytic technologies to full advantage? The key to deriving maximum business value is taking into account the decision-making you want to improve. This course shows you how to effectively operationalize advanced analytics and data science in business processes by focusing on decisions first. You’ll learn how to define and scope the business problem, ensuring that analytics are useful in business terms. You’ll also find out how to operationalize the results and use analytical decision-making to innovate business processes.
By using standards-based approaches (CRISP-DM, Decision Model and Notation [DMN]), you’ll learn how to effectively apply data-driven decision-making and analytics to business processes by identifying and modeling business decisions; applying advanced analytic technologies and data science to improve these decisions; and using analytical improvements in decision-making to drive real process innovation.
Outline:
- Introducing CRISP-DM, a methodology for advanced analytics and data science
- Focusing on decision-making to maximize the ROI of advanced analytics and data science
- Decisions versus processes and the role of data and advanced analytics in both
- Modeling decisions to build business understanding and bring clarity to decision requirements
- Business-centric evaluation and deployment of advanced analytics and data science
- The role of advanced analytics in decision-centric process improvement
- Technical options for operationalizing advanced analytics and data science in business processes
- Continuous improvement through ongoing decision monitoring and management
- Understand how a focus on decision-making ensures that advanced analytics and data science add value
- Understand how advanced analytics and data science can be used to improve decisions
- Become familiar with the structure of CRISP-DM and its role in projects
- Use decision modeling to understand business problems in a way that allows advanced analytics and data science to be applied effectively
- Compare and contrast processes and decisions and the different roles of data and advanced analytics in each
- Improve processes by improving decision-making
Participants will learn a proven approach to applying advanced analytic techniques to improve business processes by focusing on the operational decisions within those processes.
- Process improvement team members
- Business analysts
- Business and enterprise architects
- Program and portfolio managers
- Business strategists
- Data scientists and other analytic professionals