Author: Michael Yung

Michael possessed over 30 years of experience in Information Technology with focuses on complex application development, database technologies and IT strategy. He also spent the last 20 years in Internet technology, eCommerce development / operations, web usability, computer security and Public Key Infrastructure technologies.

Reflecting on 40 Years in Tech: A Career Journey of Transformation and Gratitude

My career journey in the ever-evolving world of information technology started back in September 1984. At that time, the 8-inch floppy disk was considered cutting-edge technology! Fresh out of university, I embarked on my career at a local software development company, where I maintained a system for a British bank on an IBM System/34 using RPG II. This was a significant leap forward from the punch cards, teletypes, and dumb terminals I had used during my university days.

Four decades on, the technological advancements I’ve witnessed still leave me in awe. We’ve moved from the physical constraints of punch cards and magnetic tapes to the limitless potential of the cloud. My personal computing journey mirrors this progress, starting with my trusty Commodore 64 and Apple II, then transitioning through PCs and MacBooks, and now embracing the efficiency of Chromebooks.

The programming languages I’ve learned and utilized over the years paint a vivid picture of the industry’s evolution: Assembly Language, Fortran, APL, LISP, PL/1, COBOL, Pascal, Basics, Prolog, RPG, 3GL, C, C++, JAVA, HTML, JavaScript, PHP, Python, Objective C, Swift, and currently, Flutter. And who could forget the revolution in mobile communication, from the humble pager to the Personal Digital Assistant and feature-rich smartphones of today – Psion, Nokia, Sony, iPaq, Dopod, iPhone, and Android.

What about databases ? IDMSX, Informix, Ingres, Sybase, Oracle, MySQL, and of course, dBase, Clipper, Foxbase, FoxPro, Filemaker …

My career path has zigzagged through diverse sectors, including banking, freight forwarding, supermarkets, container terminals, computer vendors, management consulting, e-government, e-commerce, tourism, media, airlines, and now, cloud service provider – Google Cloud.

I also have had the privilege of holding a variety of roles in these 40 years, starting as a Programmer and progressing to Analyst Programmer, Systems Analyst, Project Manager, Database Consultant, Managing Consultant, System Architect, Project Director, General Manager, Chief Technology Officer, Chief Information Officer, Head of Digital and currently, Strategic Advisor.

As I reflect on my journey, I’m humbled by the remarkable strides technology has made and deeply grateful for the experiences I’ve gained along the way. I consider myself incredibly fortunate to have had a career that has allowed me to continuously learn, grow, and contribute to the fascinating field of information technology.

As I prepare for the next 40 years 🤪, I’m filled with a sense of accomplishment and gratitude. I’m excited to see what the future holds for technology and the generations to come. Thank you to everyone who has been a part of my journey. Your contributions will continue to shape the world for years to come.

As the saying goes, it’s not about the destination, it’s not about the journey either … it’s about the person you become on the journey.

Onward and upward!

數據的型態

數據是石油，還是原油？

2006 年，英國數學家 Clive Humby 創造了「數據是新的石油。」（「Data is the new oil.」）這句說話。

由於某些原因，這句說話被人扭曲了，譬如著名的 Wired.com 就發表過「二十一世紀的數據就像十八世紀的石油：一種尚未開發的、極其寶貴的資產。就像石油一樣，對於那些看到數據的基本價值並學會提取和使用它的人來說，將會有巨大的回報。」。
換句話說，它表明我們的數據就像一口噴湧的油井，我們應該在從數據中流出的利潤中分一杯羹。

這本來沒有什麼錯，但 Humby 先生真正想說的是「數據，就像 Crude Oil / 原油一樣，必須經過提煉和轉化才能變成有用的產品和服務。只有這樣，它才變得有價值。」
換句話說，數據是必須經過處理和分析才能有價值。

擁有數據並不是關鍵，每間公司都有大量的數據。然而，關鍵在於你是否已經將你的數據轉化為信息、知識、見解，並最終令公司交付出更優秀的產品及服務。

數據又是水嗎？

1971 年，李小龍在有參與演出的美國電視劇 Longstreet 內，對劇中男主角 Michael Longstreet 說了一段話，翻譯成中文後，大意是「放空你的思想，變得無形。無形，就像水。如果你把水放進一個杯子，它就變成那個杯子。你把水放進一個瓶子，它就變成那個瓶子。你把它放在一個茶壺裡，它就變成那個茶壺。現在，水可以流動，也可以崩潰。朋友，你要成為水。」

其實，數據亦都像水一樣，也是可以無形的。如果你把數據放進一個列表（List），它就變成那一個列表。你把數據放進一個績效儀表板（Performance Dashboard），它就變成那個績效儀表板。你把它放在一個數據倉庫裡（Data Warehouse），它就變成那個數據倉庫。所以，數據亦都是可以流動，是可以多型態的。

那麼，數據會隱形嗎？

筆者是作家 Tim Harford 的忠實粉絲，他每一本著作都會細讀。2021 年，在他的作品 Data Detective 一書中，他表示我們在接觸數據及統計數字的時候，需要保持好奇、務實和貫徹的精神，而且遵循十條清晰易懂的規則。而其中，筆者對規則五，六，七最為認同：

規則五：了解數據背後的故事

當你擁有大量數據的時候，理解數據背後的故事與數據本身是一樣重要的：譬如，數據是否遺漏了一些相關內容？報告是否遺漏了什麼特別的內容？所有的發現都清楚了嗎？

規則六：了解數據背後的重要假設

正當大數據開始成為新常態，很多時候，只有數據收集者才知道正在收集哪些資料。不過，數據很可能有偏差，這意味著在顯示結果時，可能做出了重要假設，所以我們對這些假設一定要清楚。

規則七：對數據要求透明度

小數據的分析往往很容易評估和審核，我們不需要花巧的演算法才能得出結論。另一方面，自從大數據開始大放異彩以來，其他更精細的演算法也隨之興起。這些先進的演算法通常會帶來更好的結果，但代價是成為不易解釋的「黑盒子」。所以擁抱數據固然重要，但也一定要了解處理數據的「黑盒子」！

最後，你認識的數據是甚麼型態呢？是原油，水，還是隱形的呢？是時候加入數據素養協會，對數據再一次深入了解。

One Book At A Time – 2023

In 2023, the world of information consumption was dominated by short-form content. We’re constantly bombarded with bite-sized pieces of information from websites news, short / long videos, blog posts, social media, slide decks, even industrial research reports and PDFs. Podcasts have also become a popular way for me to consume information while jogging.

This constant influx of quick hits has undoubtedly impacted my reading habit, making it a slower year for in-depth, long-form reading, particularly of ebooks.

Anyway, here are the books (in purchasing order) of 2023:

And the best book to me this year is … The Coming Wave: Technology, Power, and the Twenty-first Century’s Greatest Dilemma. YMMV.

Previous years’ book list:

From Mainframe to AI

While watching the Google Next 2023 Keynote Live streaming, which featured numerous impressive AI product announcements, I was reminded of my early experiences with computing. The Timehop app popped up an image of the IBM 360, the first computer I ever used to run programs decades ago.

The evolution from mainframe computers to advanced AI systems operating on cloud platforms has been remarkable. I can’t wait to see the future developments in this ever-evolving field.

(I captured this photograph during a visit to the Computer History Museum in Mountain View, CA. It is my conviction that every IT professional should experience this museum at least once in their career.)

AI 2041

Instead of believing in the marketing hype of generative AI, it’s important to understand what AI is, what AI can do, and what likely we will see by year 2041. Mr. Kai-Fu Lee’s AI 2041 is really a good read with all sorts of different AI use case scenarios. Highly recommended.

It’s also a dream came true to have Mr. Kai-Fu Lee’s “digital” signature with my Kindle Scribe in an AI event !