(Midterm) Advanced Database Systems Mocktest BSIT - 505

Xai Alexandrei Delos Reyes · 58問 · 2年前

通報

問題一覧

It is a collection of operations that form a single logical unit of work

Transaction

is the equivalent of a single SQL statement in an application program or transaction.

Database Request

satisfies the constraints specified in the schema.

Database consistent state

A DBMS uses this to keep track of all the transactions that update the database.

Transaction log

In Properties of transactions, which is described as it requires that all operations (SQL requests) of a transaction should be completed.

Atomicity

In Properties of transactions, it ensures that only valid data following all rules and constraints will be written in the database. When a transaction results in invalid data, the database reverts to its previous state

Consistency

In Properties of transactions, it is when the data used during the execution of a current transaction cannot be used by another transaction until the first one is completed.

Isolation

In Properties of transactions, it ensures that once transaction changes are done and committed, they cannot be undone or lost.

Durability

In SQL Transaction commands, This marks the beginning of transaction execution.

BEGIN TRANSACTION

In SQL Transaction commands, this signals a successful end of the transaction so that any changes (updates) executed by the transaction can be safely committed to the database and will not be undone.

COMMIT

In SQL Transaction commands, This signals that the transaction has ended unsuccessfully so that any changes or effects that the . transaction may have applied to the database must be undone.

ROLLBACK TRANSACTION

In SQL Transaction commands, it is a point in a transaction when you can roll the transaction back to a certain point without rolling back the entire transaction.

SAVE TRANSACTION

In SQL Transaction commands, it returns the number of BEGIN TRANSACTION statements that have occurred on the current connection.

@@TRANCOUNT

in this state, a transaction stays in this state to perform READ and WRITE operations. Which Transaction Execution States is being described?

Active state

where the final statement in queries has been executed Which Transaction Execution States is being described?

Partially committed state

after all the operation has been completed Which Transaction Execution States is being described?

Committed state

if one of the operations cannot be done or proceed Which Transaction Execution States is being described?

Failed State

corresponds to the transaction leaving the system and if it is either committed or aborted Which Transaction Execution States is being described?

Terminated

which best describes concurrency control?

When several transactions execute simultaneously in the database, there will be a chance that the consistency and integrity of data may no longer be preserved.

occurs when two concurrent transactions, T1 and T2, are updating the same data element, and one of the updates is lost (overwritten by the other transaction). Which concurrency problem is being described?

Lost Update

occurs when two transactions, T1 and T2, are executed concurrently, and the first transaction (T1) is rolled back after the second transaction (T2) has already accessed the uncommitted data. Which concurrency problem is being described?

Uncommitted data

occur when a transaction accesses data before and after one or more other transactions finish working with the same data. Which concurrency problem is being described?

Inconsistent retrievals

It guarantees exclusive use of data item to a current transaction.

Lock

Which statement is NOT TRUE about Locks

The entire table is locked.

Which statement is NOT TRUE about database-level lock

The entire table is locked

Which statement is NOT TRUE about Table-Level Locks

Locks the entire database

Which statement is NOT TRUE about Row-level locks?

Locks the entire database

Which statement is NOT TRUE about Binary Lock?

An exclusive lock exists when access is reserved specifically for the transaction that locked the object.

Which statement is NOT TRUE about shared/ exclusive locks

Has only two states: locked (1) and unlocked (0)

It occurs when two (2) transactions wait indefinitely for each other to unlock data.

Deadlock

A transaction requesting a new lock is aborted when there is the possibility that a deadlock can occur. If the transaction is aborted, all changes made by this transaction are rolled back, and all locks obtained by the transaction are released. Which technique of deadlock control is being described?

Deadlock prevention

The DBMS periodically tests the database for deadlocks. If a deadlock is found, the “victim” transaction is aborted (rolled back and restarted), and another transaction continues. Which technique of deadlock control is being described?

Deadlock detection

The transaction must obtain all the locks it needs before it can be executed. However, the serial lock assignment required in deadlock avoidance increases action response time. Which technique of deadlock control is being described?

Deadlock avoidance

It is when a transaction can read data that is not committed yet.

Dirty Read

a transaction reads a given row at time T1, and then it reads the same row at time T2, yielding different results. The original row may have been updated or deleted.

Non-repeatable read

a transaction executes a query at time T1, and then it runs the same query at time T2, yielding additional rows that satisfy the query.

Phantom Read

Which statement is NOT TRUE about READ UNCOMMITTED

it is a default isolation level for SQL Server

Which statement is NOT TRUE about A READ COMMITTED

Ensures that no other transactions can modify or delete data that has been read by the current transaction until the current transaction commits

Which statement is NOT TRUE about A REPEATABLE READ

Most restrictive level and gives solution to the phantom read problem.

Which statement is NOT TRUE about A SERIALIZABLE isolation

Is the least restrictive isolation level

It is a database designed to enable and support business intelligence (BI) activities, especially analytics.

data warehouse

In Characteristics of Data Warehouses (DW), It is when the DW can analyze data about a particular subject or functional area.

Subject-Oriented

In Characteristics of Data Warehouses (DW), It is when the DW creates consistency among different data types from different sources.

Integrated

In Characteristics of Data Warehouses (DW), It is when the data in DW represents the flow of data through time. It can be organized weekly, monthly, or annually, etc.

Time-variant

In Characteristics of Data Warehouses (DW), it is once data is in a data warehouse, it is stable and does not change.

Non-volatile

In Components of Data Warehouse (DW), This is a databank that stocks all enterprise data and makes it manageable for reporting.

Data Warehouse Database

In Components of Data Warehouse (DW), These tools are used for performing all the conversions, summarizations, and all the changes needed to transform data into a unified format in the data warehouse

Extraction, Transformation, and Loading Tools (ETL)

In Components of Data Warehouse (DW), it is data about data that describes the data warehouse. It provides the source, transformation, integration, storage, usage, relationships, and history of each data element.

Metadata

contains information about the warehouse, which is used by data warehouse designers and administrators. Which type of Metadata is this?

Technical Metadata

It contains details that give end-users an easy way to understand the information stored in the data warehouse. Which type of Metadata is this?

Business Metadata

In Components of Data Warehouse (DW), it corporate users generally cannot work with databases directly.

Data Warehouse Access Tools

In Data Warehouse Access Tools, it help users produce corporate reports for analysis that can be in the form of spreadsheets, calculations, or interactive visuals.

Query and reporting tool

In Data Warehouse Access Tools, In such cases, custom reports are developed using application development tools when built-in graphical and analytical tools do not satisfy the analytical needs of an organization.

Application development tools

In Components of Data Warehouse (DW), a process of discovering meaningful new correlations, patterns, and trends by mining a large amount of data.

Data mining

In Components of Data Warehouse (DW), it allow users to analyze the data using elaborate and complex multi-dimensional views.

OLAP tools

In Components of Data Warehouse (DW), a small, single-subject data warehouse subset that provides decision support for the particular user group.

Data Marts

It is a data-modeling technique used to map multi-dimensional decision support data into a relational database.

star schema

In a star schema, these are data that will be included in reports and used as the basis of business decisions. It contains measurement or facts to the data and foreign key to dimension table.

Facts table

In a star schema, these are attributes that qualify and provide more information about facts. It contains dimensions of a fact and they are joined to fact table via foreign key.

Dimension table

It is a software tool that is used for data analysis and reporting purposes for business decisions

Online Analytical Processing (OLAP)

an operational system that manages the day-to-day transactions of an organization

Online Transaction Processing (OLTP)

Which Statement is NOT TRUE about OLAP

Manages day to day operations

Which Statement is NOT TRUE about OLTP

Provides historical data for reporting and planning

In Characteristics of OLAP, It is when Data is processed and viewed as part of a multi-dimensional structure.

Multi-dimensional data analysis techniques

In Characteristics of OLAP, To deliver efficient decision support

Advanced Database support

In Characteristics of OLAP, to permit the user to navigate the data in a way that simplifies and accelerates decision making or data analysis with easy-to-use graphical interfaces

Easy-to-use end-user interfaces

In types of OLAP, extends OLAP functionality to multi-dimensional database management systems (MDBMS). It is best suited to manage, store, and analyze multi-dimensional data

Multi-dimensional OLAP (MOLAP)

In types of OLAP, It works directly with relational databases. Fact and dimension tables are stored as relations.

Relational OLAP (ROLAP)

Which Statement is NOT TRUE about ROLAP?

Uses data cubes

Which Statement is NOT TRUE about MOLAP?

Unlimited dimensions

In OLAP Operations, an extension of the GROUP BY clause that is used to create subtotals and grand totals for a set of columns

ROLLUP operator

In OLAP Operations, Like ROLLUP, this generates subtotals for all the combinations of grouping column s specified in the GROUP BY clause.

CUBE operator

In OLAP Operations, allows you to write a cross-tabulation, which means you can aggregate your results and rotate rows into columns

PIVOT operator

It refers to analyzing massive amounts of data in a data warehouse or other sources to uncover hidden trends, patterns, and relationships. This explains the past and predicting the future for analysis

Data mining

In data mining techniques, used to retrieve important and relevant information about data and metadata.

Classification

In data mining techniques, used to identify data that are like each other. This process helps to understand the differences and similarities between the data.

Clustering

In data mining techniques, used to identify and analyze the relationship between variables.

Regression

In data mining techniques, used to help find the association between two or more Items. It discovers a hidden pattern in the data set.

Association Rules

In data mining techniques, used to observe data items in the dataset that do not match an expected pattern or expected behavior.

Outer detection Rules

In data mining techniques, used to discover or identify similar patterns or trends in transaction data for a certain period.

Sequential Patterns

In data mining techniques, used to combine other data mining techniques like trends, sequential patterns, clustering, classification, etc. It analyzes past events or instances in the right sequence for predicting a future event.

Prediction

Which statement is FALSE about data mining?

used to identify and analyze the relationship between variables.

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