​Just today, I received this badge from one of the platforms I mentor. This is a place where I normally volunteer some mentoring, mostly for people who can't afford to pay for it. Should you wish to explore mentoring with me, feel free to check the mentoring section of this site. Cheers ..read more

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Lately, we've put together a new survey to better understand this area and the main pain points associated with it. It would be great if you could contribute through a response and perhaps through sharing this survey with friends and colleagues. Cheers! https://s.surveyplanet.com/arw5bz4a ..read more

Lately, I've started putting together a new course​ on problem-solving, targeted mainly at business people and team leaders (though any knowledge worker could benefit from it). I'm launching it in the next month or so. If you or anyone else you know is interested, you can fill in this short survey for it and join the waitlist. Cheers ..read more

This is the second part of the Data Literacy for Professionals article Examples of Data Literacy in Practice Data literacy adds value to an organization in various ways, one of which is to support decision-making. Say you need to create a new marketing campaign to increase customer retention, for example. Where would you start? Would you just come up with a few random ideas, select the most promising ones, and run with it? A data literate professional would take a step back, examine the data at hand, see if there was a way to collect additional data, if necessary, and then work with some ana ..read more

Introduction Different people mean different things when they talk about data literacy. For this article, so that we are on the same page, let's use the definition of "the ability to create, manage, read, work with, and analyze data to ensure & maximize the data's accuracy, trust and value to the organization" (D. Marco, Ph.D.). Note that this definition highlights a crucial characteristic of data literacy which entails coherency and collaboration within the organization, something that often reflects a particular kind of culture. I'm referring to the data culture, which is an integral pa ..read more

At the end of last month, OpenAI released its latest product, which made (and still makes) waves in the AI arena. Namely, about three weeks ago, ChatGPT made its debut, and before long, it gathered enough traction to outshine its predecessor, GPT3. Since then, many people have started speculating on it and making interesting claims about its capabilities, role in society, business value, and future. But what about the human aspects of this technology? How can ChatGPT affect us as human beings and professionals in the next few years? Let's start with the latter, as it's generally easier to un ..read more

Due to the success of the Analytics and Privacy podcast in the previous few months, when the first season aired, I decided to renew it for another season. So, this September, I launched the second season of the podcast. So far, I have three interviews planned, two of which have already been recorded. Also, there are a few solo episodes too, where I talk about various topics, such as Passwords, AI as a privacy threat, and more. Since I joined Polywork, many people have connected with me on various podcast-related collaborations, some of which are related to this podcast. So, expect to see more ..read more

Introduction I've written about Nim in the past, but it's been a while. So, I decided to do a deep dive on it this time as the language seems to have evolved a lot since then, plus I had promised that I'd keep an eye on it. So, let's look at this language anew and explore how it's faring these days. Why Nim and why it's worth learning about it Nim has been around for almost a decade and a half now but it remains in relative obscurity. So, why should you learn about it nevertheless, especially when there are other, more established languages out there? Well, Nim is super fast (it compiles to ..read more

It's been over two years since the Compressed Data Format (CDF) made its debut, making storing data files in Julia a breeze. Not only does it handle various types of data easily, but it also allows for comments and any other stuff you'd like to include in your data file before sharing it with other Julia users. The native data file formats the language has been okay, but when it comes to larger datasets, they fall short. Also, conventional data file formats like CSV and JSON, although mature and easy to use, tend to be bulky as the number of data points/variables grows. CDF remedies all that ..read more