data managment

eflect on your understanding of the concepts you have learned in modules 5 that addresses Master Data Management (MDM) and Metadata Management (MM). From what you have learned in this module, what propositions or change-recommendations would you propose to your organization regarding MDM and MM, and how these could be better leveraged to optimize the firm’s enterprise wide Data Management? Reflect upon the connection(s) among Data Storage Solutions and MDM and MM. Then provide some tangible propositions on how data storage technologies, particularly data vault data warehouses, dimension model data warehouses and lake houses can/could be used to optimize/ maximize / enhance the management of Master Data and Metadata within your organization. Which of the three would you propose to your organization for use in MDM and/or MM and why? Then read the article titled data-management-101-ebook-databricks.pdf which elaborates data management in/on DATA BRICKS, an emergent platform for data storage, business intelligence and machine learning. What does Databricks bring to data management that conventional approaches do not? How do you see artificial intelligence (AI) technology contributing to and/or transforming/disrupting data management as a program, process, discipline or profession? What was the Muddiest topic in module 5? Considering the entire course thus far, what topic remains the least clear to you as we draw nearer to the end of the course? Post your reflection (a good post will be between 200-600 words) to this discussion forum by FRIDAY. Return to this discussion forum before the due date and reply to TWO other students, reflective posts. Make sure that your post addresses ALL the questions listed above.