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4 Hours of Video Instruction
Good metrics can help a team continuously improve and deliver consistently, while poor metrics can create a culture of fear; this video shows how to measure Agile teams effectively and help create an environment that maximizes value and learning.
Finding the right balance of metrics for your Agile teams can significantly help your continuous improvement efforts, forecasting, and risk management on software development projects. Instilling curiosity about performance datainstead of dreading arbitrary performance goalsis the best way to promote a culture of continuous improvement. This video will guide you through how best to incorporate metrics into your teams and organizations to diagnose issues, unearth trends, predict issues, and apply historical results to prescribe preventative actions. You will also learn multiple techniques and approaches for creating data visualizations that make your metric reporting clear and impactful.
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Who Should Take This Course?
Course Requirements:
Understanding of the fundamentals of Agile software development and frameworks such as Scrum and Kanban.
Lesson descriptions:
Lesson 1: Why We Measure: This lesson discusses the underlying drivers for our data analytics and the importance of awareness and intent when measuring data. It's important to approach measuring data with the right intent. A common negative consequence of measuring data with the wrong intent is creating a culture of fear.
Lesson 2: Defining a Metric: This lesson explores what is a good metric, how to use simple questions to best outline what to measure, and how to avoid some common pitfalls when working with data.
Lesson 3: Descriptive Data Analytics: This lesson describes the first step to creating metrics, which is to collect and visualize historical data to see what's been happening with your team. Lesson 3 is a perfect example of the quote, A picture maybe worth a thousand words but a good report is worth a thousand data points.
Lesson 4: Diagnostic Data Analysis: This lesson explores the importance of understanding and uncovering why certain things happen with your team. Lesson 4 gives you behind-the-scenes kind of experience.
Lesson 5: Predictive Data Analytics: This lesson shows about how to get a decent idea of what's likely to happen within your team since the future is unpredictable. The instructor gives tips and tricks of using empirical data and simple math to get ahead of potential issues that might arise going forward.
Lesson 6: Prescriptive Data Analytics: This lesson shows how to analyze your data, identify trends therein, and make informed decisions for your team based on your analysis.
Lesson 7: Creating a Balanced Dashboard: This lesson covers the importance of considering the full landscape of collected data, and how to find the best mix of connective metrics to inform your analysis.
Lesson 8: Instilling a Culture of Continuous Improvement: This lesson shows how to use data safely while maintaining the freedom to experiment. You will learn to approach metrics in a way that inspires curiosity and not fear.
Lesson 9: Agile Metrics in Action: This lesson consists of real-world examples of topics and tools covered in previous lessons, and is intended to help you understand how metrics work in agile teams and organizations.
About Pearson Video Training:
Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.
Video Lessons are available for download for offline viewing within the streaming format. Look for the green arrow in each lesson.
Lesson 1: Why We Measure
1.1 How Metrics Correspond to Outcomes
1.2 How Metrics Influence Behavior
Lesson 2: Defining a Metric
2.1 Qualities of a Good Metric
2.2 Creating a Metric Questionnaire
2.3 Common Metric Pitfalls
Lesson 3: Descriptive Data Analytics
3.1 Collecting Data
3.2 Visualizing Data
Lesson 4: Diagnostic Data Analysis
4.1 Investigating Why
4.2 Drilling Down in Detail
Lesson 5: Predictive Data Analytics
5.1 Measuring Variability
5.2 Forecasting with Empirical Data
5.3 Thresholds and Boundaries
Lesson 6: Prescriptive Data Analytics
6.1 Identifying Data Trends
6.2 Data Informed Guidance
Lesson 7: Creating a Balanced Dashboard
7.1 Setting Up Guardrails
7.2 Defining a Metrics Quadrant
7.3 Trending Dashboards
Lesson 8: Instilling a Culture of Continuous Improvement
8.1 Data-Driven Improvement
8.2 Avoiding a Culture of Fear
Lesson 9: Agile Metrics in Action
9.1 End-to-end Metrics Demo