- Ethics, Fairness, and Bias in AI, by Aditya Aggarwal - Jun 30, 2021.
As more AI-enhanced applications seep into our daily lives and expand their reach to larger swaths of populations around the world, we must clearly understand the vulnerabilities trained machine leaning models can exhibit based on the data used during development. Such issues can negatively impact select groups of people, so addressing the ethical decisions made by AI--possibly unknowingly--is important to the long-term fairness and success of this new technology.
- Unleashing the Power of MLOps and DataOps in Data Science, by Yash Mehta - Jun 29, 2021.
Organizations trying to move forward with analytics and data science initiatives -- while floating in an ocean of data -- must enhance their overall approach and culture to embrace a foundation on DataOps and MLOps. Leveraging these operational frameworks are necessary to enable the data to generate real business value.
- Data Scientists are from Mars and Software Developers are from Venus, by Anand Rao - Jun 28, 2021.
Within the broad universe of IT in the business world, the approaches for deploying solutions by traditional software engineers and trendy, new data scientists couldn't be more different. However, appreciating these differences are incredibly important because great business value can be gained by integrating both worlds of development into driving more efficiency and effectiveness into an organization.
- What will the demand for Data Scientists be in 10 years? Will Data Scientists be extinct?, by Matthew Mayo - Jun 24, 2021.
Participate in the latest KDnuggets survey and share your opinion: what does the next decade have in store for data scientist demand?
- In-Warehouse Machine Learning and the Modern Data Science Stack, by Nick Acosta - Jun 24, 2021.
As your organization matures its data science portfolio and capabilities, establishing a modern data stack is vital to enabling such growth. Here, we overview various in-data warehouse machine learning services, and discuss each of their benefits and requirements.
- Analytics Engineering Everywhere, by Jason Ganz - Jun 22, 2021.
Many new roles have appeared in the data world ever since the rise of the Data Scientist took the spotlight several years ago. Now, there is a new core player ready to take center stage, and we may see in five years, nearly every organization will have an Analytics Engineering team.
- Major changes: Where Analytics, Data Science, Machine Learning were applied in 2020/21, by Gregory Piatetsky - Jun 18, 2021.
Our latest poll shows major change in where AI, Data Science, Machine Learning are being applied, with decline in interest in traditional fields like CRM/Consumer Analytics, and growth in applications to Computer Vision, COVID, Agriculture, and Education.
- Data Science is Not Becoming Extinct in 10 Years, Your Skills Might, by Ahmar Shah, PhD - Jun 18, 2021.
4 reasons why data science is here to stay and what you need to do to ensure that your skillset stays in demand.
- How to Land a Data Analytics Job in 6 Months, by Natassha Selvaraj - Jun 17, 2021.
Go from zero to hero in under six months.
- Data storytelling: brains are built for visuals, but hearts turn on stories, by Hrvoje Smolic - Jun 17, 2021.
Today, we need much more than just numbers about our organization to understand, gain insights, and take relevant actions. While visualizations of the data are important, making an emotional connection with the stories behind the data is key. If you want to sell a story, send a missile to the heart.
- Data Scientists Will be Extinct in 10 Years, by Mikhail Mew - Jun 14, 2021.
And why it’s not a bad thing.
- Data Scientists, You Need to Know How to Code, by Tyler Folkman - Jun 9, 2021.
You need to know how to code — and not just code, but write good code.
- How a Single Mistake Wasted 3 Years of My Data Science Journey, by Pranjal Saxena - Jun 9, 2021.
Self-paced courses are just sleeping pills; Industry experts are the right choice.
- 5 Tips for Picking an Edge AI Platform, by Erik Ottem-Cachengo - Jun 8, 2021.
Edge Analytics isn’t just coding and tools. The different environment outside the datacenter or cloud means a purpose built platform is the best way to deliver consistent results. We discuss 5 different considerations for an edge platform to support your training and deployment.
- BigQuery vs Snowflake: A Comparison of Data Warehouse Giants, by Anji Velagana - Jun 3, 2021.
In this article we are going to compare the two topmost data warehouses: BigQuery and Snowflake.
- Will There Be a Shortage of Data Science Jobs in the Next 5 Years?, by Pranjal Saxena - Jun 3, 2021.
The data science workflow is getting automated day by day.
- How I Doubled My Income with Data Science and Machine Learning, by Terence Shin - Jun 1, 2021.
Many career opportunities exist in the ever-expanding domain of data. Finding your place -- and finding your salary -- is largely up to your dedication, focus, and drive to learn. If you are an aspiring Data Scientist or have already started your professional journey, there are multiple strategies for maximizing your earning potential.
- Overcoming the Simplicity Illusion with Data Migration, by Yancy Blum - Jun 1, 2021.
What’s the key to a smooth data migration experience? It comes down to this primary issue: whether or not you can rapidly determine your dataset composition.