Exercise-Module-8 Adhere to APA formatting, use 1.5 line spacing, and use 12 point font for Times new roman. Deductions will be made for egregious grammatical errors. Blackboard SafeAssign is used to check for plagiarism. Question.1: (4 pages) Imagine the use of DataOps in some organizational environment (business/non-profit, large/small, any industry, etc.) for some particular data analytic project (i.e. a defined scenario). Describe the environment, the project, and – mostly – the processes and procedures of a working DataOps environment for your scenario. Question.2: (1 page) Once you have a good understanding of DataOps, describe how you might apply the principles and concepts between other units of an organization in support of data analytics. For instance, between data scientists/analysts and customer service. Argue the problem and briefly describe how your solution would help. Sources on DataOps: ( feel free to search for different resources on DataOps for Data Analytics/Science): 1- https://learn-us-east-1-prod-fleet01-xythos.s3.amazonaws.com/5b06b62e5266a/15501729?response-cache-control=private%2C%20max-age%3D21600&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27DataKitchen_dataops_cookbook.pdf&response-content-type=application%2Fpdf&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20200623T180000Z&X-Amz-SignedHeaders=host&X-Amz-Expires=21600&X-Amz-Credential=AKIAZH6WM4PLTYPZRQMY%2F20200623%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=c1879fe31fe7a80a5202e6d2041be0fa58f29ffa0a9779d7405de5730ccaff64 2- https://learn-us-east-1-prod-fleet01-xythos.s3.amazonaws.com/5b06b62e5266a/15501730?response-cache-control=private%2C%20max-age%3D21600&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27Data%2520Driven%2520Enterprise%2520with%2520DataOps.pdf&response-content-type=application%2Fpdf&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20200623T180000Z&X-Amz-SignedHeaders=host&X-Amz-Expires=21600&X-Amz-Credential=AKIAZH6WM4PLTYPZRQMY%2F20200623%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=e0868541fd1bb45d69f8fd5d58ad703266aa79d0e62a57560ec1e115b8d144a7 3- https://www.tamr.com/blog/dataops-ecosystem-emerges/ 4- https://pubsonline.informs.org/do/10.1287/LYTX.2019.06.03/full/ 5- https://www.youtube.com/watch?v=hncbbdWevOo&list=PLVbsAdgZXvtyy6HVKCP0HChjCcq2oW3eK&index=5 6- https://www.tamr.com/blog/from-devops-to-dataops-by-andy-palmer/ 7- https://www.datakitchen.io/dataops-vs-devops.html?utm_source=google&utm_medium=cpc&utm_campaign=brand&utm_term=dataops&utm_campaign=Brand&utm_source=adwords&utm_medium=ppc&hsa_acc=4149132021&hsa_cam=1484277812&hsa_grp=61494010030&hsa_ad=318228753345&hsa_src=g&hsa_tgt=kwd-380307544461&hsa_kw=dataops&hsa_mt=p&hsa_net=adwords&hsa_ver=3&gclid=Cj0KCQjw0Mb3BRCaARIsAPSNGpVmhhyMyfuyMV_BjSoWf74SYXZzZUUGyCwf7-dK1Zxfsakok5V-PRIaApLPEALw_wcB 8- https://www.infoworks.io/5-characteristics-define-dataops-agile-data-engineering/
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