All Hands on Data #63
The term data science may have lost its luster in the last couple of years, but it's still being widely talked about. You can see it referenced in several of the articles our team picked this week!
Generative AI And Data Science Have Mightily Paired Up To Reinvent Data Strategies, Exemplified Via Release Of OpenAI’s ChatGPT Code Interpreter
“The narrative of AI killing data or augmenting it has been an extremely hot topic so I think our list would find it interesting.” - Angel Catalan
Data science vs web development: What’s the difference?
“I find that data scientists and web developers share a love of programming. There were many data analysts in my web development bootcamp and I often wondered why they didn't dive into data science instead. After reading this article about the similarities and differences between the two, I better understand why. You never know, maybe reading this article will spark a desire for a career shift for you too.” - Katt Baum
Will data science be automated by ChatGPT?
“Despite the much hyped doom and gloom around ChatGPT destroying everyone's jobs, the author provides an alternative and realistic impact of the technology specifically on the data science space. While the AI model is hugely helpful, and can be leveraged to handle lots of boring work, it's incapable of knowing the ins-and-outs of what a data scientist is attempting to accomplish in their work. Don't worry, it won't steal your job and definitely won't paperclip us out of existence.” - John Forstmeier
The Rise of the Dual Data Scientist / Machine Learning Engineer
“There is a prevalent "silo" mentality that divides professionals into specialized roles, such as data scientists, ML engineers, and analysts. Individuals skilled in multiple domains are considered "unicorns", but they might not be recognized or fit into traditional job roles due to compartmentalization. This article brings to light the benefits of being a dual engineer/scientist who can bridge the gap between these roles. However, becoming a dual engineer/scientist involves continuous practice in both domains, but such individuals can find job opportunities in various capacities. There are some challenges in identifying and hiring unicorns, but with AI tools, finding these unicorns has become a lot easier.” - Reed Cowan
A Map to Explain all Data Roles
“When I began my journey into the data world a few years ago, the titles in the space were so confusing to me. Honestly, they still can be. Depending on the job description, a data analyst can be expected to know how to write complex Python code or just know how to use Excel. Quite a gap there. This article does a great job of trying to add some better descriptions to the job titles in the space.” - Steven Johnson
Understanding Data Orchestration: A Symphony in the Data World
“You can’t have different tools working together without collaboration and orchestration between them. So why not take that approach with people from competitor companies? I was thrilled that we got to partner with Matt Palmer from Mage to help educate people on Data Orchestration. After all, what matters most is that the users have the best data orchestration tool that fits their needs and skills, whether that’s Shipyard or not.” - Arynn Martin-Post