Issues
Introduction
Data Curiosity is a newsletter for professionals who want to —
- Learn – Acquire in-demand data skills and improve professional growth opportunities.
- Grow – Understand the market dynamics of the companies in the data space, hear from the experts and though leaders, and position your career for advancement.
The breakdown of the content categories in this newsletter is displayed in a visual format below. An example issue is here.
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What This Is and Isn’t
Beginner | Intermediate | Advanced | |
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Data Engineering | |||
Data Science | |||
Cloud | |||
Business & Investing |
I make absolutely no promises that you will find this useful, but I do promise to do my best to educate or entertain you. These are the rules of the game:
- Lower your expectations. This is an outlet for sharing interesting things I find about data. This includes learning data skills for professional growth (job promotions) and improve your understanding of the technology and the business. Once in a while, I’ll have longer essays, interviews, and deep-dives. I probably won’t blow your mind, but I’ll try to expand it at least a little.
- It’s not about machine learning algorithms. We will talk about machine learning every so often. We won’t, however, get into the intricacies and the math.
- It won’t be linear, feel free to jump around. Once in a while I may do a theme or narrative, but most editions won’t be like that. You can skim the sub-titles and scan the images and just read what grabs you.
- I change my mind, I make mistakes. I can add/subtract. On a sunny day, I can even multiply and divide. I am, however, theoretical mathematically challenged. If you spot errors, factual or logical, please let me know (my DMs are open on Twitter, or you can “reply” to newsletter emails). If you read an old edition, it may contain things that are no longer correct. I blame it on the invention of continuous integration (CI) and constantly changing nature of silicon valley.
- I’m not “qualified” for anything. Nothing here is investment advice or technical advice or DIY home renovation advice. I do have extensive hands-on and leadership experience in the technology industry. It is still a day 0 for me. I hope to learn from the awesome community of people like you.
Frequently Asked Questions
There is two types of content. The first is technical topics about data engineering, data science, and data visualization. We will also cover cloud technologies as they relate to data management.
The other type of content is looking at data from a business perspective. Our focus will be on understanding the market trends. For example, right now, in Spring 2022, Snowflake is one of the most richly-valued software company.
The primary audience is a data professional or those who aspire to work with data. This can include students.
Email opt-in is provided as a convenience for readers. Majority of the content on this site will be available without a paywall. I do not plan to market anything to you, solely for the commercial benefits. If there are any paid offerings, I plan to make those available for free (or almost free) to students from developing countries.