Exam PL-600 topic 1 question 76 discussion

A. User access: Understanding who needs access to the data and how they access it is crucial for designing a secure and efficient data architecture. B. Quality: Assessing the quality of the data helps in identifying any issues related to data accuracy, consistency, and completeness, which are essential for reliable decision-making. D. Location: Knowing where the data is stored, whether on-premises or in the cloud, and its geographical distribution can influence data management strategies, compliance, and performance.

B - quality (does it need to be transformed, migrated into a new system for better transactions) D-location (how we will connect to the data and integrate with apps, etc.) E-History (This question is asked over and over and is very critical in enterprise solutions, especially big data. Data retention, especially for building reports over time) User access and pain points are important but not related to the question at hand, which is about the data itself, not security, permissions, or problems.

BDE: From courses in Microsoft training https://learn.microsoft.com/en-us/training/modules/discover-customer-needs/3-meetings Ask your customers the following questions to determine how these influencers affect the data architecture: Where does the data reside now? Where should it reside? Do you have integrity concerns? Do you have duplicates or other data quality issues? Are you keeping historical data, and how much? What type of access will users need to historical data?

B. Quality: Understanding the quality of the data is essential to assess whether the data is accurate, consistent, and reliable. Data quality can impact decisions, operations, and insights generated by the architecture. D. Location: The location of data is important for data residency, privacy laws, and performance. It influences how the data is stored, processed, and accessed, and can have implications for compliance with regional regulations. E. History: The historical context of the data is important for understanding trends, how data is collected over time, and how past decisions or events influence current architecture. It can also indicate the need for data migration or transformation as the system evolves.