- Building a solid data team - Dec 8, 2021.
How do you put together a solid data science team when it comes to developing data-driven products? A variety of roles are available to consider, so which ones do you need and which are most crucial?
Agile, Careers, Data Engineer, Data Science Team, Data Scientist, Product Owner, Software Developer
- Two Simple Things You Need to Steal from Agile for Data and Analytics Work - Nov 16, 2021.
Peer Review and Definition of Done: small changes, BIG impact.
Agile, Analytics, Data Science, Data.world
- Agile Data Labeling: What it is and why you need it - Aug 16, 2021.
The notion of Agile in software development has made waves across industries with its revolution for productivity. Can the same benefits be applied to the often arduous task of annotating data sets for machine learning?
Agile, Data Labeling, Machine Learning, Tesla
- Can Data Science Be Agile? Implementing Best Agile Practices to Your Data Science Process - Jan 18, 2021.
Agile is not reserved for software developers only -- that's a myth. While these effective strategies are not commonly used by data scientists today and some aspects of data science make Agile a bit tricky, the methodology offers plenty of benefits to data science projects that can increase the effectiveness of your process and bring more success to your outcomes.
Agile, Best Practices, Data Science, Development
- Data Science as a Product – Why Is It So Hard? - Dec 30, 2020.
Developing machine learning models as products that deliver business value remains a new field with uncharted paths toward success. Applying well-established software development approaches, such as agile, is not straightforward, but may still offer a solid foundation to guide success.
Agile, Data Science, Deployment, Product
- A Holistic Framework for Managing Data Analytics Projects - May 22, 2020.
Agile project management for Data Science development continues to be an effective framework that enables flexibility and productivity in a field that can experience continuous changes in data and evolving stakeholder expectations. Learn more about the leading approaches for developing Data Science models, and apply them to your next project.
Agile, CRISP-DM, Data Analytics, Data Management, Data Mining, Decision Management, Development, Software Engineering
- Top 5 must-have Data Science skills for 2020 - Jan 8, 2020.
The standard job description for a Data Scientist has long highlighted skills in R, Python, SQL, and Machine Learning. With the field evolving, these core competencies are no longer enough to stay competitive in the job market.
2020 Predictions, Agile, Cloud Computing, Data Science Skills, Deep Learning, Deployment, GitHub, NLP
- Why software engineering processes and tools don’t work for machine learning - Dec 5, 2019.
While AI may be the new electricity significant challenges remain to realize AI potential. Here we examine why data scientists and teams can’t rely on software engineering tools and processes for machine learning.
Agile, Andrew Ng, Comet.ml, Machine Learning, Software Engineering
- A Doomed Marriage of Machine Learning and Agile - Nov 28, 2019.
Sebastian Thrun, the founder of Udacity, ruined my machine learning project and wedding.
Agile, Machine Learning, Udacity
- How to Make an Agile Team Work for Big Data Analytics - Oct 31, 2019.
Learn how to approach the challenges when merging an agile methodology into a data science team to bring out the best value for your Big Data products.
Agile, Big Data, Big Data Analytics, Data Science Team
- Data-science? Agile? Cycles? My method for managing data-science projects in the Hi-tech industry. - Feb 7, 2019.
The following is a method I developed, which is based on my personal experience managing a data-science-research team and was tested with multiple projects. In the next sections, I’ll review the different types of research from a time point-of-view, compare development and research workflow approaches and finally suggest my work methodology.
Agile, Data Science, Development, Project
- Getting Real World Results From Agile Data Science Teams - Feb 10, 2017.
In this post, I’ll look at the practical ingredients of managing agile data science. By using agile data science methods, we help data teams do fast and directed work, and manage the inherent uncertainty of data science and application development.
Agile, Data Science, Data Science Team, SVDS