Data-Management-Foundations Dumps with Practice Exam Questions Answers

Binary searchis an algorithm that finds a search value byrepeatedly dividing the search space into two halves. It is commonly used inindexed searches.

Example Usage in Databases:

B-Trees and B+ Trees(used in database indexing) applybinary searchto navigate the index efficiently.

If searching for ID = 50 in asorted list of IDs, binary search:

Splits the list into two halves.

Checks the middle value.

Eliminates half of the dataset.

Repeats until the value is found.

Why Other Options Are Incorrect:

Option A (Table scan) (Incorrect):Readsevery row,much slowerthan binary search.

Option C (Index scan) (Incorrect):Uses indexes but does not necessarily apply binary search.

Option D (Fan-out) (Incorrect):Describesbranching in B-Trees, not searching.

Thus, the correct answer isBinary search, as it repeatedlysplits the indexin two.

In SQL, aprimary key is explicitly defined using the PRIMARY KEY keywordwhen creating a table.

Example Usage:

sql

CREATE TABLE Products (

ProductID INT PRIMARY KEY,

Name VARCHAR(100),

Price DECIMAL(10,2)

);

Here,PRIMARY KEY is the SQL keyword that designates ProductID as the primary key.

Why Other Options Are Incorrect:

Option A (Formula in SQL) (Incorrect):SQLdoes not use formulas to define primary keys.

Option C (Bold typeface) (Incorrect):SQL syntax does not rely on text formatting.

Option D (Diamond symbol) (Incorrect):ER diagramsmight use symbols, but SQLdoes not use diamonds to indicate keys.

Thus, the correct answer isSQL keyword, as primary keys are explicitly defined using PRIMARY KEY.

In SQL,literalsrepresent explicit values such asnumbers, strings, or binary datadirectly written into queries. For example:

SELECT * FROM Employees WHERE Salary > 50000;

Here, 50000 is anumeric literal.

Option A (Correct):Literalsare explicit values used in SQL queries, such as 123, 'John Doe', and TRUE.

Option B (Incorrect):Commentsare non-executable text used for documentation within SQL code, typically denoted by -- or /* ... */.

Option C (Incorrect):Identifiersare names oftables, columns, or other database objects, such as EmployeeID.

Option D (Incorrect):Keywordsare reserved words in SQL (e.g., SELECT, FROM, WHERE) that define operations and syntax.

TheMERGEstatement, also known asUPSERT, combinesINSERT, UPDATE, and DELETEoperations into asingle statementbased on a given condition. It is commonly used indata warehouses and large-scale databases.

Example Usage:

sql

MERGE INTO Employees AS Target

USING NewEmployees AS Source

ON Target.ID = Source.ID

WHEN MATCHED THEN

UPDATE SET Target.Salary = Source.Salary

WHEN NOT MATCHED THEN

INSERT (ID, Name, Salary) VALUES (Source.ID, Source.Name, Source.Salary);

If a match is found, the UPDATE clause modifies the existing record.

If no match is found, the INSERT clause adds a new record.

Why Other Options Are Incorrect:

Option A (INTO) (Incorrect):Used in INSERT INTO, butdoes not combine operations.

Option B (JOIN) (Incorrect):Used to combine rows from multiple tables, butnot for merging data.

Option D (DROP) (Incorrect):Deletes database objects liketables, views, and indexes, butdoes not merge data.

Thus, the correct answer isMERGE, as itcombines inserts, updates, and deletes into a single operation.

Non-relational databases(also calledNoSQL databases) are designed for handlingbig dataandunstructured dataefficiently. They are optimized forhorizontal scaling, making them ideal forlarge-scale distributed systems.

Option A (Correct):Non-relational databases areoptimized for big data, handling massive volumes of data across distributed architectures.

Option B (Incorrect):NoSQL databases donotuse SQL as their primary query language. They often use JSON-based queries (e.g., MongoDB).

Option C (Incorrect):Transaction-heavy applications requireACID compliance, which relational databases (SQL) handle better than NoSQL databases.

Option D (Incorrect):NoSQL databases usedocument, key-value, graph, or column-family storage models, nottables, columns, and rowslike relational databases.