National Yang-Ming University
  • 2019 Mar 12
  • National Yang Ming University GLORIA - Big Data Corporate Keynote Speech - The Next Digital Wave: OpportunitiesChallenges
Following the digitalization trend, digital technologies are pouring into all walks of life. The key to future success in the healthcare field relies on making good use of big data and allowing artificial intelligence (AI) to get closer to users through algorithms. This is the only way to grasp opportunity. Therefore, the Big Data Corporate Keynote Speech (1/3) specially invited Bing-tsu Chang, Vice President of the Business Intelligence Department of GodSpeed Ltd. BI Dept., who has spared no effort in developing smart websites to share the information environment and technology of Big data. Ideally, teachers and students who are also working to develop this field can seize these opportunities and apply Big data to the biomedical industry.
 
When talking about the digital wave, we first have to understand what is digital? Digit usually refers to as a system that uses the discrete (i.e., discontinuous) value of 0 or 1 to represent information for input, processing, transmission, storage, etc. However, the non-digit (analog signal) system uses a continuous range to describe information. The advent of the big data era means that the information we obtain is both digital and non-digital, so the data analysis we now perform is no longer traditional digital data but comes mostly in the form of non-digitization and non-structural data. This also allows us to test the information system capabilities and the advantages and disadvantages of each algorithm.


When we discuss the value of big data, it seems that trivial and ordinary data have been sorted out, aggregated, and then analyzed through algorithms to show the high-value features that are invisible from any part of the data.
 
Let’s start with a smaller piece of big data that you experience, such as perception. In the face of the data age, do you have any feelings about numbers? If you’re not sensitive to the numbers around your life, even if you’re given big data, you still can’t demonstrate the effectiveness of data analysis, especially in the biomedical and medicine fields. Now, let’s get back to you. If you can record what you have seen and heard every minute of your life in great detail, that would be a form of big data. In today’s technological world, as long as storage space is not a problem, technology can do what the brain cannot. The key is in the analysis method.

In his speech, Vice President Chang asked the distinguished guests: “What’s the most important part of the stethoscope?” His response - the thing that comes between the two earplugs, that is, the doctor’s brain.
 
The same is true about Big data. Data analysis can be used as a reference for decision making, but don’t put all your faith in data analysis or allow yourself to be manipulated by data analysis.
 
Vice President Chang also mentioned that: “Paradigm is always on the move.” It contains two concepts, open source economy and cloud revolution.
 
The “open source” production model has surpassed the scope of software production, cultural industries, biopharmaceuticals, life sciences, and academic research, and the modern Internet economy has widespread “open source” behavior. Bluntly speaking, this behavior refers to the use of software that others have developed or designed, so that you don’t have to write your own programs. Moreover, while the supply side of the cloud revolution has already been finalized, the good days of the user side have just begun. The booming development of cloud technology allows users to pay little but use a large space and big technology, without having you to set up and maintain the servers or purchase a lot of storage space.

Vice President Chang also reminded everyone that although cloud technology and Big data have made AI more refined, security is always a priority.
 
Finally, Vice President Chang explained how to seize these opportunities:
 
1. If you want to develop your algorithms, you must first master linear algebra and higher calculus; otherwise, just continue to focus on your own profession!
2. Pay more attention to collecting cross-domain knowledge.
3. Start learning a programing language. Logic is more important than grammar. If you really don’t know which language to learn, start with Python!
4. English is definitely a key point. I don’t even have to explain that.
5. Develop the habit of sorting out the data at hand.
6. Control the open source wave.
7. Put knowledge into practice with a benevolent and artistic mind.

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