In this course, you will learn next-level thinking about value creation with Dark Data, using a principled approach that demonstrates your ability to use dark data to add value to an end-deliverable.
Value Creation with Dark Data
Dieser Kurs ist Teil von Spezialisierung Dark Data Migration and Architecture
Dozent: Curtis Thompson
Empfohlene Erfahrung
Was Sie lernen werden
Learners will gain next level thinking about value creation with Dark Data from a principled approach and demonstrate value creation skills.
Kompetenzen, die Sie erwerben
- Kategorie: Creating value and working a problem with dark data concepts
Wichtige Details
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1 Aufgabe
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In diesem Kurs gibt es 4 Module
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.
Das ist alles enthalten
2 Videos3 Lektüren
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.
Das ist alles enthalten
11 Videos5 Lektüren
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.
Das ist alles enthalten
7 Videos3 Lektüren
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.
Das ist alles enthalten
4 Videos2 Lektüren1 Aufgabe2 Diskussionsthemen
Dozent
Empfohlen, wenn Sie sich für Data Analysis interessieren
Coursera Project Network
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IE Business School
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