M9 Discussion: Big Data

Part 1 (400 words in total):
Write a discussion post.
Paragraph 1: (3-4 sentences)
What is the definition of big data in your own words?
Include, as part of your definition, 3 of the “V”s your text book uses to define big data.
Do not use quotes.
Paragraph 2: (4-5 sentences maximum)
Research one example of the use of predictive analytics and/or artificial intelligence (AI/Machine Learning) in healthcare from a journal article in Pubmed.gov or one of the websites below.
How is your example method of big data analytics used to improve patient health, population health or healthcare delivery? Discuss one or two specific health outcomes it aims to improve such as patient level or population level outcomes.
Describe at least one challenge of using big data analytics in healthcare or public health.
Some good sources to search for an example include: the HIMSS website(https://www.himss.org/), Pubmed(https://pubmed.ncbi.nlm.nih.gov/), AMIA(https://amia.org/), SAS(https://www.sas.com/en_us/industry/health-care.html), the ONC(https://www.healthit.gov/), the CDC(https://www.cdc.gov/genomics/events/genomic_data_2019.htm), the NIH( https://www.nih.gov/), etc.
The post should include at least 2-3 referenced sources cited in APA or MLA format.

Part 2 (100 words for each reply. There are two posts to reply to. Therefore 200 words in total)
Reply to 2 of your peers posts (given below) with at least 2-3 full sentences on something interesting in their post and/or a question. (I will add the posts once you complete part 1 and send it to me) each respond to the peer post should be 100 words.

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