Hello Data Strategy Pro and hello May!!
In this month's newsletter, we'll discuss ways data practitioners can get involved with Web3.0. We also cover what we learned in April, and talk about upcoming events in May. As promised, we'll conclude with a discussion about the benefits of coffee on personal and societal wellbeing.
To get things started: why should data practitioners care about Web3.0?
Web3.0 represents a new paradigm of connecting people through a participative internet. The concept is associated with decentralization and token-based economies. The objective of Web3.0 is to make it possible for users to own the data they create online without the intermediation of giant corporations such as Meta, Twitter, and the like.
Blockchains, the open ledger technology of Web3.0, are showing up in all kinds of experimental use cases. Blockchain can be used to represent a store of value (cryptocurrency), ownership of a digital product (nonfungible tokens [NFTs]), or proof of lineage.
As more than a decade of experimentation proves, there are some practical applications for this technology. A discussion of how to get involved would take up more space than we have here, but opportunities are abundant if you're willing to do your research. Consider investing, staking, minting an NFT, or participating in a DAO related to an area of interest.
Proponents of Web3.0 argue that it can make the internet more fair and accessible. For example, digital tokens could give users a way to monetize their online activity and contributions. Detractors argue that decentralization creates oversight challenges and opportunities for shady behavior in a largely unregulated environment.
As a data practitioner, you are uniquely positioned to develop a solid understanding of this new technology and serve as a thought leader on how Web3.0 may influence your industry. Blockchain, after all, is merely a data storage system of immutable, distributed, peer-to-peer databases.
What are you doing to get involved in Web3.0? What questions do you have about this space? Check out the discussion thread on LinkedIn to share your thoughts.
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Community Corner
Congratulations on passing the CDMP Fundamentals Exam: Haneen Husien, Jennifer Pinargote, Mike Smith, and Frank Bonnette
Congrats on working towards the CDMP Specialist Certification: Wendy Groven-Hogenboom (Data Governance)
Want to let us know about your accomplishments? Make sure you post in the CDMP Study Group 🎉
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In the CDMP Study Group, we covered Data Modeling, which is ch. 5 of the DMBOK and 11% of the content on the CDMP exam.
- There are three levels of modeling: Conceptual, Logical, and Physical
- As a best practice, when the Data Modeling process is completed, the team should reverse engineer the Logical and Conceptual Models based on the Physical Model to ensure the business requirements have been met
- One popular method for Data Modeling is to create non-normalized fact and dimensional tables. Each fact table is comprised of quantitative data and is linked to many dimensional tables containing descriptive data. Dimensional modeling creates a star-shaped diagram, which is therefore called the star schema
You can read more about methods for Data Modeling in this article.
In Breaking into Data Science, we learned about pandas - not the endangered bear species endemic to China, but actually the premier Python package for working with data in a table format.
- pandas was developed by Wes McKinney while working as a quantitative researcher. He wanted to create a tool to quickly and flexibly manipulate financial data
- A lambda is an anonymous function that allows you to flexibly create short functions as needed. They're very useful to implement alongside pandas. Read more here and here
- Pivot tables are one of the most useful functions of pandas. Learn how to use them here
If you're excited about Data Science and want to learn more, check out our guide to Data Science for non-technical folks or try out the Breaking into Data Science Email Bootcamp (you can sign up to get the program free for seven days).
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Book Recommendations
Recapping our list of book recommendations for the month of May:
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Upcoming in May
In the CDMP Study Group, we'll spend the month focused on ch. 6 of the DMBOK, Data Storage & Operations. In Breaking into Data Science, we'll be jumping into scientific computing and experimentation with sklearn. In Data Strategy Professionals on LinkedIn, we'll continue to share the latest news about Data Strategy along with our regular #ScienceSaturday and #SundayPunday themed posts.
On Sun, May 15th, Community Organizer Nicole will be doing a full day of Career Coaching sessions. The goal is to help you figure out what you want to achieve and how to advance your career. These sessions will be targeted at data practitioners who want to grow their skills or find a new job in the field. We can touch on job search, interview skills, resume review, promotion preparedness, or anything else that's top of mind for you.
On Thurs, May 19 at 7pm EST, we're bringing back Speed Friending with Data Strategy Professionals. We'll hang out on Gatheround for an hour of "get-to-know-you" questions in groups of different sizes. Some of the questions will be related to our work as data practitioners, others will be just for fun. Hope you'll drop in to this opportunity to engage with other data folks around the globe.
On Mon, May 30th at 12pm EST, I'll host a special guest to answer your questions about the Certified Data Management Professional (CDMP) exam. I'll share my experience passing the test in October 2020 with an 80%+ score and address any questions you have about where this credential fits in to your career plans as a data practitioner.
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Final Thoughts
Hi there, your Community Organizer Nicole here 👋 I am obsessed with coffee. This potent and mostly positive drug enables personal productivity and has also empowered societal shifts and grand new ideas.
Coffee plants are native to Ethiopia. By the 15th century, the drink made from roasted coffee beans had spread to the Middle East, stoking the cultural, economic, and scientific flourishing of the Islamic Golden Age.
Within another 150 years, European coffee houses began to arise. They served as a place to refresh oneself and exchange ideas. Europe began to sober up. As coffee gradually replaced alcohol as the daytime drink of choice, it had a positive impact on the quality of thought and production.
"It's not an accident that the ‘age of reason’ accompanies the rise of caffeinated beverages…" states Steven Johnson, author of Where Good Ideas Come From. "The culture [of Europe] is moving from a depressant to a stimulant." New business ventures, great works of literature, and classical compositions were produced and shared at coffee houses.
With few downsides, coffee has many benefits on our health. Here's a list of 8 reasons to feel good about your morning pick-me-up:
1. Coffee helps you concentrate and pay attention (duh!)
2. Coffee improves physical performance. Black coffee one hour before a workout can boost athletic performance 11-12% by increasing the production of adrenaline.
3. Coffee contains nutrients such as magnesium and potassium, which helps the body use insulin to regulate blood sugar levels.
4. Coffee reduces the risk of cancer. According to one study, coffee can reduce the risk of prostate cancer in men by 20% and the risk of endometrial cancer in women by 25%. People in the test group drank four cups of coffee a day. Caffeine can also prevent the development of basal cell carcinoma, the most common type of skin cancer.
5. Coffee reduces the risk of stroke. Consumption of 2-4 cups per day is associated with a low risk of stroke.
6. Coffee reduces the risk of aging-related diseases. There is evidence that coffee causes activity in parts of the brain affected by Parkinson's, Alzheimer's, and dementia. Studies show that drinking coffee regularly reduces your risk of Parkinson's by 25%.
7. Coffee protects your body. Coffee is rich in antioxidants. Think of them like small warriors that fight and defend against free radicals.
8. Coffee improves your mood. Caffeine stimulates the central nervous system and increases the production of neurotransmitters such as serotonin, dopamine, and norepinephrine.
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While personal motivation is key to attaining your goals, the impact of a supportive group cannot be overstated.
CDMP Study Group offers preparation for the open-book Certified Data Management Professional exam on best practices in Data Strategy. This valuable leadership credential is associated with top positions in management, data architecture, and data science.
Breaking into Data Science is a Facebook group for sharing resources on data science and machine learning. Each month, we cover a different topic related to breaking into Data Science.
Data Strategy is a crucial discipline that spans end-to-end management of the data lifecycle. Given that what we choose to measure and evaluate is a reflection of our values, Data Strategy Professionals offers a thoughtful forum for conversation about these critical topics.
We also offer training for Data Strategists and Data Scientists. Your ambitions are within your reach!
Cheers,
Nicole
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