Arizona State University
Value Creation with Dark Data
Arizona State University

Value Creation with Dark Data

Curtis Thompson

位教师:Curtis Thompson

包含在 Coursera Plus

深入了解一个主题并学习基础知识。
初级 等级

推荐体验

1 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入了解一个主题并学习基础知识。
初级 等级

推荐体验

1 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Learners will gain next level thinking about value creation with Dark Data from a principled approach and demonstrate value creation skills.

要了解的详细信息

可分享的证书

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作业

1 项作业

授课语言:英语(English)

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Dark Data Migration and Architecture 专项课程 专项课程的一部分
在注册此课程时,您还会同时注册此专项课程。
  • 向行业专家学习新概念
  • 获得对主题或工具的基础理解
  • 通过实践项目培养工作相关技能
  • 获得可共享的职业证书

该课程共有4个模块

Welcome to Value Creation with Dark Data. We are excited that you are here and hope you finish this course with working knowledge of creating value by using dark data and the foundational ideas of dark data. In this course, you will work through a project scenario to identify and leverage data to create a solution.

涵盖的内容

2个视频3篇阅读材料

In this module, you will be learning more about dark data and putting the principles of working with dark data into practice. This is important as your understanding now will inform how you work toward a solution in the project in Module 2. Think about what you know, what you are learning now, and what you might use in the future as you work through this module.

涵盖的内容

11个视频5篇阅读材料

As you move through this module, remember that your focus now is to shift from knowing to practicing; that is, being able to use what you know. In this module, you will learn about insight, intelligence, and data management. These will all be important as you begin your project in the next module.

涵盖的内容

7个视频3篇阅读材料

It is now time for you to put your new knowledge and skills into practice. In this project, you will work with a common problem that vexes Fortune 500 companies. Companies constantly struggle to ensure that they have enough engineering capacity to build the software applications they need to provide appropriate staffing levels. Staffing appropriately includes not only having the right people available at the right time but also reducing the amount of over and idle time for engineers while ensuring the pace of projects is appropriate for business needs. In this project, you need to find a way to manage and transform the data and automate the engineering measurement, tracking, and reporting for a large corporation. You will download and use a complex spreadsheet for this task. There is no simple answer to this problem; in fact, there are some very wrong answers and many ways to approach this problem that can work. The right answer will always be the one that enables you to: 1. have a clear line of sight into the teams work 2. improve the ability to measure teams in a more uniform manner 3. improve the ability of your organization to manage engineering processes uniformly 4. map engineering efforts toward enterprise and organizational goals 5. automate effort and capacity reporting 6. improve capacity and effort transparency enterprise-wide 7. map business outcomes to the actual engineering work and products being delivered The danger to be aware of here is the dark data. When you do not know what you are missing, you can easily think you are successful when you are not. As you work through this problem, consider all you have learned about dark data in this course and use that knowledge to learn from the data, apply your knowledge of business and engineering teams, transform and enrich the data, and develop an end-user dashboard that allows people to quickly understand capacity at a high-level and allows them to dive into the details. Quick note: When we speak of engineering capacity, it refers to the amount of engineering ability available to deliver software applications needed for business use.

涵盖的内容

4个视频2篇阅读材料1个作业2个讨论话题

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位教师

Curtis Thompson
Arizona State University
3 门课程440 名学生

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