Draft:DSciBA
Submission declined on 18 May 2024 by DoubleGrazing (talk).
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
|
DSciBA Data Science Board of America
The DSciBA Data Science Board of America (DSciBA) is a professional organization dedicated to advancing the field of data science in the United States. Established in 2023, DSciBA serves as a hub for data science professionals, researchers, educators, and enthusiasts to collaborate, share knowledge, and promote excellence in the rapidly evolving field of data science.
History
DSciBA was founded by a group of passionate data scientists who recognized the growing importance of data-driven decision-making across various industries. With the exponential growth of data and the increasing complexity of analysis techniques, there was a clear need for a centralized platform to foster collaboration and drive innovation in the field of data science.
Mission and Objectives
The mission of DSciBA is to promote the growth and development of data science as a discipline, profession, and community in the United States. To achieve this mission, DSciBA has set the following objectives:
Professional Development: Provide opportunities for data science professionals to enhance their skills, expand their knowledge, and advance their careers through workshops, seminars, and networking events.
Knowledge Sharing: Facilitate the exchange of ideas, best practices, and research findings among members of the data science community through conferences, publications, and online forums.
Education and Training: Support the education and training of the next generation of data scientists by collaborating with academic institutions, offering certification programs, and promoting the adoption of data science curricula.
Ethical Standards: Promote ethical and responsible use of data science techniques and technologies by establishing guidelines, codes of conduct, and ethical frameworks for data scientists and organizations.
Advocacy: Advocate for policies and initiatives that promote the responsible use of data, protect privacy and security, and ensure equitable access to data science resources and opportunities.
- in-depth (not just brief mentions about the subject or routine announcements)
- reliable
- secondary
- strictly independent of the subject
Make sure you add references that meet all four of these criteria before resubmitting. Learn about mistakes to avoid when addressing this issue. If no additional references exist, the subject is not suitable for Wikipedia.