Leveraging Full Stack Data Science for Healthcare Transformation: An Exploration of the Microsoft Intelligent Data Platform

Year : 2024 | Volume : 11 | Issue : 03 | Page : 1 8
    By

    Prashant D. Sawant,

  1. AI Research Director, Ai-Discovery Consultancy, Melbourne, Australia

Abstract

The rapid progress of the Fourth Industrial Revolution has been largely driven by the evolution of artificial intelligence (AI), with notable contributions from technologies such as Generative Pre-trained Transformers (GPT). This revolution has seen the convergence of physical, digital, and biological technologies, leading to transformative impacts across various sectors. Data science, serving as a crucial enabler, has enabled the development of intelligent value chains. However, the application of data science in this domain often remains limited to isolated elements of the data pipeline. The concept of Full Stack Data Science (FSDS) addresses this limitation by providing a comprehensive approach to managing all aspects of a data science project. This paper explores the challenges faced by Full Stack Data Scientists, such as data integration, quality, scalability, security, privacy, tool complexity, stakeholder communication, and regulatory compliance. It further discusses how the Microsoft Intelligent Data Platform (MIDP) offers a suite of tools and services that support FSDS, particularly in the healthcare industry. The roles of Full Stack Data Scientists in healthcare, including data integration, analysis, visualization, model deployment, and governance, are examined. The paper also highlights the significance of data processing frameworks and machine learning services provided by Azure, emphasizing their utility in the data science workflow.

Keywords: Artificial intelligence, generative pre-trained transformers, full stack data science, microsoft intelligent data platform, healthcare

[This article belongs to Journal of Advanced Database Management & Systems ]

How to cite this article:
Prashant D. Sawant. Leveraging Full Stack Data Science for Healthcare Transformation: An Exploration of the Microsoft Intelligent Data Platform. Journal of Advanced Database Management & Systems. 2024; 11(03):1-8.
How to cite this URL:
Prashant D. Sawant. Leveraging Full Stack Data Science for Healthcare Transformation: An Exploration of the Microsoft Intelligent Data Platform. Journal of Advanced Database Management & Systems. 2024; 11(03):1-8. Available from: https://journals.stmjournals.com/joadms/article=2024/view=169935


References

  1. Sawant PD. Artificial Intelligence: The era of new Industrial Revolution [eBook]. Kindle Store. Amazon.com.au; 2022.
  2. Sawant PD. A real-time visualization framework to enhance prompt accuracy and result outcomes based on the number of tokens. J Artif Intell Res Adv. 2024;11:45-53.
  3. Schwab K, World Economic Forum (2016). The Fourth Industrial Revolution: what it means and how to respond. [online] World Economic Forum. Available from: https://www.weforum.org/
    stories/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond/.
  4. ODSC Community. (2020). Data science in manufacturing: An overview. [online]. Open Data Sci. Available from: https://opendatascience.com/data-science-in-manufacturing-an-overview/.
  5. The Click Reader. (2021). Full-stack data science: A complete overview. [online]. Medium. Available from: https://medium.com/@theclickreader/full-stack-data-science-a-complete-overview-9d66df1ac771.
  6. Perfect eLearning. (2023). Building end-to-end data solutions: Full stack data science. [online]. Available from: https://perfectelearning.com/blog/building-end-to-end-data-solutions-full-stack-data-science.
  7. StrataScratch. (2020). How to become a full stack data scientist. [online]. Available from: https://www.stratascratch.com/blog/how-to-become-a-full-stack-data-scientist/n.
  8. Shopify. (2022). What is a full Stack data scientist? [online]. Available from: https://shopify.engineering/what-is-a-full-stack-data-scientist.
  9. Institute of Data. (2024). What is full stack data science? [online]. Available from: https://www.institutedata.com/us/blog/what-is-full-stack-data-science/.
  10. Kumar R. (2022). Introducing the Microsoft intelligent data platform. Microsoft Azure Blog. [online]. Microsoft Website. Available from: https://azure.microsoft.com/en-us/blog/introducing-the-microsoft-intelligent-data-platform/.
  11. Microsoft intelligent data platform. (2023). Microsoft Cloud. [online]. Microsoft.com. Available from: https://www.microsoft.com/en-us/microsoft-cloud/solutions/intelligent-data-platform.
  12. Hawk J. (2024). The Microsoft Intelligent Data Platform—Unleash your data and accelerate your transformation. Microsoft Azure Blog. Microsoft Website. [online]. Available from: https://azure.microsoft.com/en-us/blog/the-microsoft-intelligent-data-platform-unleash-your-data-and-accelerate-your-transformation/.
  13. Thomas S. (2022). Microsoft Cloud for Healthcare: Transforming patient care through data and insights. Microsoft Industry Blogs. Microsoft Website. [online]. Available from: https://www.microsoft.com/en-us/industry/blog/healthcare/2022/04/05/microsoft-cloud-for-healthcare-transforming-patient-care-through-data-and-insights/.
  14. Health. (2024). About health data in Australia. Australian Government Department of Health and Aged Care. [online]. Available from: https://www.health.gov.au/topics/health-data-and-medical-research/about-health-data.
  15. OAIC. (2019). Guide to health privacy. [online]. oaic.gov.au. Available from: https://www.oaic.
    gov.au/__data/assets/pdf_file/0011/2090/guide-to-health-privacy.pdf.
  16. Orion Health. (2023). Data masking vs de-identification: Understanding the differences and relevance in healthcare. [online]. Orion Health. Available from: https://orionhealth.com/us/blog/
    data-masking-vs-de-identification-in-healthcare/.
  17. Kadam S. (2019). Data masking: Concept, tools, masking policies & healthcare data masking. Medium. Petabytz. [online]. Available from: https://medium.com/petabytz/data-masking-concept-tools-masking-polices-healthcare-data-masking-3c28ca03a30a.
  18. Jain K. (2023). Data anonymization and data masking in healthcare. [online]. Medium. Available from: https://karen-j.medium.com/data-anonymization-and-data-masking-in-healthcare-db2650f0
  19. HealthIT.gov. (2019). Privacy, Security, and HIPAA. [online]. Available from: https://www.healthit.gov/topic/privacy-security-and-hipaa.
  20. Bhatia J. (2024). The role of data science in healthcare industry in 2024. [online]. PW Skills Blog. Available from: https://pwskills.com/blog/the-role-of-data-science-in-healthcare-industry-in-2024/.
  21. SQLPad. (2024). Guide to becoming a full stack data scientist in 2024. [online]. Available from: https://sqlpad.io/tutorial/guide-to-becoming-a-full-stack-data-scientist-in-2024/.
  22. Samuel Westby S. (2023). Full-Stack Data Science Roadmap 2023. [online] Samuel Westby. Available from: https://www.samwestby.com/2023/data-science-roadmap.
  23. Sinha V. (2020). Building a data science tech stack: A comprehensive guide. Hevo Data. [online]. Available from: https://hevodata.com/learn/building-a-data-science-tech-stack/.
  24. Microsoft. (2024). What is data science? Become a data scientist. Microsoft.com. [online]. Available from: https://azure.microsoft.com/en-ca/resources/cloud-computing-dictionary/what-is-data-science/.
Regular Issue Subscription Review Article
Volume 11
Issue 03
Received 27/04/2024
Accepted 03/06/2024
Published 31/08/2024
345

Login


My IP

PlumX Metrics