Knowledge Management and Big Data in Business
Business Excellence in a knowledge-driven Industry 4.0 world,
The business landscape is changing so rapidly that traditional management, business and computing courses do not meet the needs for the next generation of workers in the business world. Most traditional methods are of a repetitive, rule-based nature and will be gradually replaced by Artificial Intelligence. In the knowledge era, the most value added job will be to manage knowledge, which includes how knowledge is created, mined, processed, shared and reused in different trades and industry. At the same time, the amount of data and information (prerequisites of knowledge) is exploding exponentially. By 2020, IDC projects that the size of the digital universe will reach 40 zetabytes from all sources including, websites, weblog, sensors, and social media. Digitalisation, Cloud Computing, Big data will transform how we live, work and even think in a Networked Economy. These trends and more will have a profound effect on how we see the world and create policies. In this course, the following topics and more are covered:
What is knowledge management?
How is knowledge captured, elicited, organized and created in business?
Managing knowledge at the enterprise, SMBs and personal levels
Digitalisation and its impact on the workplace, collaborations and new value creation
What is big data and how can we use data analytics from a laymen perspective?
What is Open Linked Data and how can it support machine reasoning?
How can new knowledge be mined from big data?
What are the technical and social problems with big data?
The Cloud as a canvas for service design and business model re-invention
What are examples of applications and case studies?
The course is offered by the Knowledge Management and Innovation Research Center (KMIRC) of the Hong Kong Polytechnic University. Most of our research is company and industry based. Capabilities and competencies of the KMIRC are further strengthened by the international alliances it has formed with leading practitioners, many of which are regarded as members of the "Hall of Fame" in knowledge management, and renowned worldwide. The course is suitable for participants with a background in humanities, management, social science, physical science or engineering. No prior technical background is needed.
What you'll learn
- Understand the role of Knowledge Management (KM) practitioners in creating business value
- Become familiar with the techniques and tools for capturing, processing, classifying and organizing knowledge
- How to analyze large quantities of data and information through analytics
- How to use Cloud Services to derive new values and business models
- Understand the role of social media and technologies in innovating new business services
- Apply the principles you have learnt to company-based business projects
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Rating | 4.3★ based on 13 ratings |
---|---|
Length | 8 weeks |
Effort | 8 weeks, 6–8 hours per week |
Starts | On Demand (Start anytime) |
Cost | $169 |
From | The Hong Kong Polytechnic University, HKPolyUx via edX |
Instructors | Eric Tsui, W.B. Lee, Klaus Tochtermann, Usama Fayyad, Jay Lee, Susanne Durst |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Business Data Science Social Sciences |
Tags | Business & Management Data Analysis & Statistics Social Sciences |
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What people are saying
my best greetings from
My best greetings from Morocco.
health concerns last week
Lee and all the team members of the Knowledge Management and Innovation Research Center of the Hong Kong Polytechnic University : I wanted to review on this course earlier, but I had some health concerns last week.
even without extensive database
Even without extensive database and knowledge management background the training adds tremendous value and indicates indirectly which fields in data science to study.
indicates indirectly which fields
will open another session
I hope you will open another session of this course, so I will come back to share with you and future participants the results of my KM experience within my company.
training adds tremendous value
gradually introduces some essential
The course was well designed and gradually introduces some essential concepts.
different way about e-learning
This was substantial academic experience I simply got so satisfied with this course that it has opened my mind in a very different way about e-learning, I have had some before, but for sure this one has been extremely good.
simply got so satisfied
most valuable point
I thank all the Professor for taking their time to share their knowledge with us, that is one of the most valuable point for me, that all of your actually work in the field and in very important companies, so examples used where very real.
warmly at polyu
I want to thank you again for welcoming me warmly at PolyU and especially professor Eric Tsui, Farzad and the team of KMIRC, for giving me further explanation and documents on themes of KM.
analysis topic enhanced
Specially, The Big Data and Data Analysis topic enhanced my professional knowledge.
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Knowledge Management Support $44k
Nutrition Knowledge Management Specialist $49k
Knowledge Management Coordinator $61k
Knowledge Management Architect $64k
Knowledge Management Specialist (Technology) $66k
Knowledge Management / Information Architect $67k
Administrator, Legal and Knowledge Management $81k
Product & Knowledge Management Analyst $91k
Knowledge Management Program Analyst $100k
Knowledge Management, Program Analyst $117k
Knowledge Management Manager $177k
Managing Partner, Knowledge Management $295k
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Rating | 4.3★ based on 13 ratings |
---|---|
Length | 8 weeks |
Effort | 8 weeks, 6–8 hours per week |
Starts | On Demand (Start anytime) |
Cost | $169 |
From | The Hong Kong Polytechnic University, HKPolyUx via edX |
Instructors | Eric Tsui, W.B. Lee, Klaus Tochtermann, Usama Fayyad, Jay Lee, Susanne Durst |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Business Data Science Social Sciences |
Tags | Business & Management Data Analysis & Statistics Social Sciences |
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