Exam DP-900 topic 1 question 214 discussion

That's a strange question, to be honest. It depends on the data operation that needs to be performed. Data can be read from multiple tables and written to a single or multiple tables as well.

answer is D, you can only write to one table at a time, but can join select read from multiple tables

Question definitely allows for different perspectives. I said A because of the "fully normalized" specification.

chatGPT

answer is D, you can only write to one table at a time, but can join select read from multiple tables

A CHATGPT:In a fully normalized database, reading and writing data for a single entity involves navigating through multiple tables

There is no redundency in normalized database. Assuming you know the primary key to access the data you want, then the answer is B.

In a fully normalized database, reading and writing data for a "single entity" is a straightforward process: Reading: You access the specific table designed for that entity. All the relevant information about the entity is stored in this single table. No need to join with other tables, as data redundancy is minimized in a fully normalized schema. Writing: You interact with the same table dedicated to that entity. Any updates or additions for the entity are performed within this table. Essentially, for a single entity, both reading and writing happen in a single location, promoting data integrity and simplicity. So, both reading and writing happen in a single location!

Answer is D, understand the question correctly "In a fully normalized database". Fully normalized means NF5. So each entity is completely separate and isolated, so read can be at single entity or multiple entity level but write has to be at entity level only.

THE ANSWER IS A

In a fully normalized database, the aim is to reduce redundancy and dependency by organizing fields and table of data in such a way that every piece of data is stored only once. This means that data is often spread out across multiple tables, each designed to handle a part of the data based on its type or category. For a single entity, the following can happen: Reading Data: You often need to perform joins across multiple tables to collect all the attributes for a single entity. Writing Data: When inserting or updating an entity, you may need to add or modify data in multiple tables to keep the normalization intact.

In fully normalized databases (at least, we are talking 3NF), data is stripped to remove duplication, data redundancy, or dependency of entity attributes on columns other than the "Primary Key" column(s). This is done by separating different entities into distinct tables based on specific criteria. Each individual table typically represents a DISTINCT entity (Customer; Product; Sales; Sales Order; Employee; Department; etc), to guarantee that only pertinent information about each entity is stored in their respective tables. For fully normalized tables, when you need information about a SINGLE entity, you only read from a single source. Likewise, when you need to write information about a single entity, you write to a single destination table. However, when you require information that span more than ONE entity (say, Product, Order, and Order Details), then a TABLE join will be required (reading from multiple sources, and possibly writing to multiple sources).

B is correct answer as per my understanding. As they asked about single entity

B. Data is read from a single table and written to a single table. In a fully normalized database, data is organized to minimize redundancy and dependency by separating it into multiple related tables based on specific criteria. Each table typically represents a single entity or concept. This ensures that each piece of information is stored in only one place, which helps maintain data integrity. When you want to read or write data for a single entity, you interact with a single table that is specifically designed for that entity. This makes the process more straightforward and efficient compared to having to navigate multiple tables for a single operation.

Imagine it as a linear case. Reading from Single source and writing to single source as well.

In fully normalized data, data is definitely read from multiple tables No DOUBT. When it comes to write, I would say that they are write in to Multiple tables also, if there is this single table exists that has all the data to be written into, the database is not fully normalized.

In the end, it's Microsoft's definition of "entity" that matters. In discussing structured data, Microsoft Learn (https://learn.microsoft.com/en-us/training/modules/explore-core-data-concepts/2-data-formats) says. Most commonly, the schema for structured data entities is tabular - in other words, the data is represented in one or more tables that consist of rows to represent each instance of a **data entity**, and columns to represent attributes of **the entity**. So "table" = "entity" and "entity" = "table". Assuming that the person who wrote this question was using this as their guide, it's "read one table, write one table."