20 Mar Exploring Data Operations (DataOps
DataOps is enterprise data management for the AI era. It applies lessons learned from DevOps to data management and analytics. Effective deployment of DataOps has shown to accelerate time to market for analytic solutions, improve data quality and compliance, and reduce cost of data management. Data operations is not a product, service or solution. It’s a methodology: a technological and cultural change to improve your organization’s use of data through better collaboration and automation. Please read the article from Nexla regarding DataOps. After reading assigned materials and watching video lectures, locate 3 additional articles and summarize the learnings of this week’s curriculum by writing a discussion post that reviews the three biggest takeaways from the Nexla article as well as current and future trends in DataOps research.
1) Provide a 600 to 800-word summary (formatted according to APA guidelines) of the research in this area from a minimum of three journal articles and identify questions that need exploring in future research. Your discussion should be organized in a three-paragraph format:
- Introductory Paragraph: gives an overview and definition of the topic you chose. At the end of the paragraph it gives an idea of how your forum is organized.
- Current Trends Paragraph: In this paragraph, you will discuss the themes that you found in the research from the 3 journal articles related to your topic. This paragraph should be a synthesis of the research and not just a listing of annotated summaries.
- Future Research Paragraph: In this paragraph, you will discuss areas of future research by referencing the 3 journal articles that you identified. The future research areas should be based on the findings of the authors of those articles rather than general ideas you may have.
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