OS Syllabus

 

Introduction to Operating Systems

1. Definition, Objectives, and Core Functions of an Operating System – Overview of OS purposes and essential functions
2. System Calls and System Services – Explanation of system calls (e.g., process control, file operations) and system services
3. Structures of Operating Systems – Explanation of any two OS structures (e.g., Monolithic, Microkernel, Layered)

Processes and Scheduling

1. Process Control Block (PCB) – Explanation with a diagram highlighting components like process ID, state, CPU registers
2. SJF (Shortest Job First) CPU Scheduling – Calculation of average turnaround and response times for given process data
3. Process Definition and State Diagram – Detailed explanation of process states (New, Ready, Running, Waiting, Terminated)

Concurrency and Synchronization

1. Critical Section Problem – Explanation with an example (e.g., shared resource access in a multi-threaded environment)
2. Monitor in Synchronization – Explanation of monitors and example of their use in synchronizing access to shared resources
3. Semaphore and Producer-Consumer Problem – Definition of semaphore and example of solving producer-consumer synchronization

Memory Management

1. Contiguous Memory Management Techniques – Explanation of fixed and variable partitioning, and their pros and cons
2. Page Fault and Handling Process – Definition of a page fault and steps involved in handling it
3. Internal vs. External Fragmentation – Explanation of fragmentation types in

Disk and File Management

1. File Allocation Methods – Brief overview of contiguous, linked, and indexed file allocation methods with examples
2. Direct Memory Access (DMA) – Explanation of how DMA improves system efficiency by reducing CPU load
3. FCFS vs. SSTF Disk Scheduling – Comparison of First-Come, First-Served and

Linux Operating System

1. fork() vs. clone() System Calls in Linux – Comparison of system calls for process and thread creation
2. Inter-Process Communication (IPC) in Linux – Explanation of IPC mechanisms like pipes, message queues, and shared memory
3. Design Principles of Linux OS – Overview of Linux's core design principles like modularity, security, and efficiency

PDF

Banker Algorithm 

Example of FCFS CPU Scheduling algorithm

 Evaluate FCFS CPU Scheduling algorithm for given Problem Problem and Average Turn Around Time and Average Response Time  

Process	P1	P2	P3	P4
Process Time	24	3	5	6

Given:

• Processes:
  • P1: Burst Time = 24 ms
  • P2: Burst Time = 3 ms
  • P3: Burst Time = 5 ms
  • P4: Burst Time = 6 ms
• Assumption: All processes arrive at the same time (0 ms), as no specific arrival time is provided.

Step 1: Process Execution Order

In FCFS scheduling, processes are executed in the order they arrive. Since all processes are assumed to arrive at the same time, they will be executed in the order they are listed.

Order of Execution:
P1 → P2 → P3 → P4

Step 2: Calculate Completion Time (CT), Turnaround Time (TAT), and Response Time (RT)

• Completion Time (CT): The time at which each process completes its execution.
• Turnaround Time (TAT): The total time taken from arrival to completion of a process. $$\text{TAT} = \text{Completion Time (CT)} - \text{Arrival Time (AT)}$$
  
• Response Time (RT): The time from the arrival of the process until it starts executing. Since in FCFS, a process starts execution immediately when the CPU is available, the response time is the same as the waiting time. $$\text{RT} = \text{Start Time} - \text{Arrival Time (AT)}$$
  

Execution and Calculations

Process	Burst Time (BT)	Start Time (ST)	Completion Time (CT)	Turnaround Time (TAT)	Response Time (RT)
P1	24 ms	0 ms	24 ms	24 ms	0 ms
P2	3 ms	24 ms	27 ms	27 ms	24 ms
P3	5 ms	27 ms	32 ms	32 ms	27 ms
P4	6 ms	32 ms	38 ms	38 ms	32 ms

Step 3: Average Turnaround Time and Average Response Time

• Average Turnaround Time (TAT):

  $$\text{Average TAT} = \frac{24 + 27 + 32 + 38}{4} = 30.25 \text{ ms}$$

• Average Response Time (RT):

  $$\text{Average RT} = \frac{0 + 24 + 27 + 32}{4} = 20.75 \text{ ms}$$

• Order of Execution: P1, P2, P3, P4
• Average Turnaround Time: 30.25 ms
• Average Response Time: 20.75 ms

Example on SJF CPU Scheduling algorithm

Evaluate SJF CPU Scheduling algorithm for given Problem , Find Average Turn Around Time and Average Response Time  

Process	P1	P2	P3	P4
Process Time	8	4	9	5
Arrival Time	0	1	2	3

Given:

• Processes:
  • P1: Burst Time = 8 ms, Arrival Time = 0 ms
  • P2: Burst Time = 4 ms, Arrival Time = 1 ms
  • P3: Burst Time = 9 ms, Arrival Time = 2 ms
  • P4: Burst Time = 5 ms, Arrival Time = 3 ms

Step 1: Process Execution Order

The SJF algorithm selects the process with the shortest burst time that has arrived and is ready to execute. If two processes have the same burst time, the one that arrived earlier is selected.

Order of Execution:

1. P1 arrives at 0 ms, and it starts execution immediately since it's the only process available.
2. P2 arrives at 1 ms and has the shortest burst time after P1 finishes.
3. P4 arrives at 3 ms and has the shortest burst time after P2 finishes.
4. P3 arrives at 2 ms but has the longest burst time, so it is executed last.

Step 2: Completion Time (CT), Turnaround Time (TAT), and Response Time (RT)

• Completion Time (CT): The time at which each process completes its execution.
• Turnaround Time (TAT): The total time taken from arrival to completion of a process. $$\text{TAT} = \text{Completion Time (CT)} - \text{Arrival Time (AT)}$$
• Response Time (RT): The time from the arrival of the process until it starts executing. $$\text{RT} = \text{Start Time} - \text{Arrival Time (AT)}$$

Execution and Calculations

Process	Arrival Time (AT)	Burst Time (BT)	Start Time (ST)	Completion Time (CT)	Turnaround Time (TAT)	Response Time (RT)
P1	0 ms	8 ms	0 ms	8 ms	8 ms	0 ms
P2	1 ms	4 ms	8 ms	12 ms	11 ms	7 ms
P4	3 ms	5 ms	12 ms	17 ms	14 ms	9 ms
P3	2 ms	9 ms	17 ms	26 ms	24 ms	15 ms

Step 3: Average Turnaround Time and Average Response Time

• Average Turnaround Time (TAT):

  $$\text{Average TAT} = \frac{8 + 11 + 14 + 24}{4} = 14.25 \text{ ms}$$
  

• Average Response Time (RT):

  $$\text{Average RT} = \frac{0 + 7 + 9 + 15}{4} = 7.75 \text{ ms}$$
  

• Order of Execution: P1, P2, P4, P3
• Average Turnaround Time: 14.25 ms
• Average Response Time: 7.75 ms

Examples of Round Robin CPU Scheduling algorithm

 Evaluate Round Robin  CPU Scheduling algorithm for given Problem Time slice =3 ms.

Process	P1	P2	P3	P4
Process Time	10	5	18	6
Arrival Time	5	3	0	4

Given:

• Time Slice (Quantum): 3 ms
• Processes:
  • P1: Burst Time = 10 ms, Arrival Time = 5 ms
  • P2: Burst Time = 5 ms, Arrival Time = 3 ms
  • P3: Burst Time = 18 ms, Arrival Time = 0 ms
  • P4: Burst Time = 6 ms, Arrival Time = 4 ms

Step 1: Order of Execution

We will simulate the round-robin scheduling process:

1. Process Arrival:

   • P3 arrives at time 0 ms. Burst Time = 18 ms
   • P2 arrives at time 3 ms. Burst Time = 5 ms
   • P4 arrives at time 4 ms. Burst Time = 6 ms
   • P1 arrives at time 5 ms. Burst Time = 10 ms

2. Time Chart: We will execute each process for up to 3 ms (time slice) in a round-robin manner, continuing until all processes are completed.

   Time (ms)	Process Executed	Remaining Time of Process
   0 - 3	P3	P3 (15 ms left)
   3 - 6	P2	P2 (2 ms left)
   6 - 9	P4	P4 (3 ms left)
   9 - 12	P1	P1 (7 ms left)
   12 - 15	P3	P3 (12 ms left)
   15 - 17	P2	P2 (0 ms, completed)
   17 - 20	P4	P4 (0 ms, completed)
   20 - 23	P1	P1 (4 ms left)
   23 - 26	P3	P3 (9 ms left)
   26 - 29	P1	P1 (1 ms left)
   29 - 32	P3	P3 (6 ms left)
   32 - 33	P1	P1 (0 ms, completed)
   33 - 36	P3	P3 (3 ms left)
   36 - 39	P3	P3 (0 ms, completed)

Step 2: Calculate Completion Time, Turnaround Time, and Waiting Time

Completion Time (CT): The time at which each process completes execution.

Turnaround Time (TAT): The total time taken from arrival to completion of a process.
$\text{TAT} = \text{Completion Time} - \text{Arrival Time}$

Waiting Time (WT): The total time the process spends waiting in the ready queue.
$\text{WT} = \text{Turnaround Time} - \text{Burst Time}$

Process	Arrival Time (AT)	Burst Time (BT)	Completion Time (CT)	Turnaround Time (TAT)	Waiting Time (WT)
P1	5 ms	10 ms	33 ms	28 ms	18 ms
P2	3 ms	5 ms	17 ms	14 ms	9 ms
P3	0 ms	18 ms	39 ms	39 ms	21 ms
P4	4 ms	6 ms	20 ms	16 ms	10 ms

Step 3: Summary of Metrics

Step 3: Summary of Metrics

• Average Turnaround Time (TAT): $$\text{Average TAT} = \frac{28 + 14 + 39 + 16}{4} = 24.25 \text{ ms}$$
  
• Average Waiting Time (WT): $$\text{Average WT} = \frac{18 + 9 + 21 + 10}{4} = 14.5 \text{ ms}$$
  

• Completion Order: P2, P4, P1, P3
• Average Turnaround Time: 24.25 ms
• Average Waiting Time: 14.5 ms

==========================================================================

Consider 3 processes P1, P2 and P3, which require 5, 7 and 4 time units and arrive at time 0, 1 and 3. Draw the Gant chart, process completion sequence and average waiting time for. Round robin scheduling with CPU quantum of 2 time units.

Given:

• Processes:
  • P1: Burst Time = 5 ms, Arrival Time = 0 ms
  • P2: Burst Time = 7 ms, Arrival Time = 1 ms
  • P3: Burst Time = 4 ms, Arrival Time = 3 ms
• Time Quantum: 2 ms

Step 1: Gantt Chart

1. Initial State:

   • P1 arrives at 0 ms.
   • P2 arrives at 1 ms.
   • P3 arrives at 3 ms.

2. Execution Sequence:

   • Time 0 - 2: P1 executes (Remaining Burst Time: P1 = 3 ms).
   • Time 2 - 4: P2 executes (Remaining Burst Time: P2 = 5 ms).
   • Time 4 - 6: P3 executes (Remaining Burst Time: P3 = 2 ms).
   • Time 6 - 8: P1 executes (Remaining Burst Time: P1 = 1 ms).
   • Time 8 - 10: P2 executes (Remaining Burst Time: P2 = 3 ms).
   • Time 10 - 12: P3 executes (Remaining Burst Time: P3 = 0 ms, completed).
   • Time 12 - 14: P1 executes (Remaining Burst Time: P1 = 0 ms, completed).
   • Time 14 - 16: P2 executes (Remaining Burst Time: P2 = 1 ms).
   • Time 16 - 17: P2 completes (Remaining Burst Time: P2 = 0 ms).

Gantt Chart:

Step 2: Completion Time (CT), Turnaround Time (TAT), and Waiting Time (WT)

Completion Time (CT): The time at which each process completes its execution.

Turnaround Time (TAT): The total time taken from arrival to completion. $\text{TAT} = \text{Completion Time (CT)} - \text{Arrival Time (AT)}$

Waiting Time (WT): The total time a process spends waiting in the ready queue. $\text{WT} = \text{Turnaround Time (TAT)} - \text{Burst Time (BT)}$

Process	Arrival Time (AT)	Burst Time (BT)	Completion Time (CT)	Turnaround Time (TAT)	Waiting Time (WT)
P1	0 ms	5 ms	14 ms	14 ms	9 ms
P2	1 ms	7 ms	17 ms	16 ms	9 ms
P3	3 ms	4 ms	12 ms	9 ms	5 ms

Step 3: Average Waiting Time

• Average Waiting Time (WT): $$\text{Average WT} = \frac{9 + 9 + 5}{3} = 7.67 \text{ ms}$$
  

• Completion Time (CT): P1 = 14 ms, P2 = 17 ms, P3 = 12 ms

• Average Turnaround Time (TAT): 13 ms

• Average Waiting Time (WT): 7.67 ms

Operating Systems MCQ Unit-3

 The critical section problem is primarily concerned with:

a) Process creation

b) Memory management

c) Process synchronization

d) Deadlock prevention

Which of the following conditions must be satisfied to solve the critical section problem?

a) Mutual Exclusion, Progress, Bounded Waiting

b) Mutual Exclusion, Deadlock, Fairness

c) Progress, Fairness, Memory Management

d) Mutual Exclusion, Paging, Swapping

The principle of mutual exclusion ensures that:

a) Multiple processes can enter their critical sections simultaneously

b) Only one process is allowed to execute in its critical section at a time

c) Processes execute independently without synchronization

d) No process enters the critical section

A mutex lock is used to:

a) Allow multiple processes to enter the critical section

b) Protect a critical section by ensuring mutual exclusion

c) Switch between user and kernel modes

d) Handle memory allocation dynamically

If a process holds a mutex lock, and another process tries to acquire it:

a) The other process will proceed immediately

b) The other process will be blocked until the lock is released

c) Both processes will enter the critical section

d) The lock will be shared between the processes

Which of the following problems can occur if a mutex lock is not used properly?

a) Deadlock

b) Starvation

c) Race Condition

d) All of the above

The Dining Philosophers problem is an example of:

a) Deadlock

b) Starvation

c) Mutual Exclusion

d) All of the above

In the Producer-Consumer problem, the buffer is used to:

a) Store processes

b) Store resources

c) Store items produced by the producer before they are consumed by the consumer

d) Store memory allocation information

In the Readers-Writers problem, a writer is allowed to write if:

a) No other process is writing

b) No process is reading or writing

c) At least one reader is reading

d) Another writer is writing

Which of the following is a solution to prevent deadlock in the Dining Philosophers problem?

a) Allowing at most 3 philosophers to sit at the table at the same time

b) Using semaphores to restrict the number of philosophers that can pick up forks

c) Allowing philosophers to eat in turns

d) Avoiding the use of shared resources

Operating Systems MCQ Unit- 2

 

A process in execution is called:

a) Program

b) Task

c) Thread

d) Job

The Process Control Block (PCB) does NOT contain:

a) Process State

b) Program Counter

c) Memory Management Information

d) I/O Devices List

Which of the following is NOT a possible state for a process?

a) New

b) Ready

c) Running

d) Exited

A process that is terminated but still available in the process table is called:

a) Orphan

b) Zombie

c) Suspended

d) Blocked

Which of the following is a CPU scheduling algorithm?

a) Round Robin

b) Least Recently Used

c) First-In-First-Out

d) Quick Sort

In pre-emptive scheduling, the CPU can be taken away from a process:

a) Only when the process finishes

b) Only if a process requests I/O

c) By the operating system to allocate to another process

d) None of the above

The turnaround time of a process is defined as:

a) Time taken to complete the execution of a process

b) Time taken to load the process into the CPU

c) Time taken for a process to move from ready to running state

d) Time taken to block a process

In which of the following scheduling algorithms is the waiting time for a process minimized?

a) First-Come, First-Served (FCFS)

b) Shortest Job Next (SJN)

c) Round Robin (RR)

d) Priority Scheduling

The fork() system call is used to:

a) Terminate a process

b) Create a new process

c) Execute a new program

d) Bring a process to the foreground

What happens to the parent process when the child process is terminated?

a) The parent process also terminates

b) The parent process must terminate the child

c) The parent process receives a SIGCHLD signal

d) The parent process is suspended until the child terminates

Operating Systems MCQ Unit-1

 

Which of the following is not considered a system service?

a) Process Management

b) Memory Management

c) User Authentication

d) Text Editing

System services are typically provided by the:

a) Hardware

b) User Applications

c) Operating System

d) None of the above

Which of the following is an example of a system call?

a) printf()

b) fork()

c) scanf()

d) strlen()

System calls provide an interface between:

a) User and Hardware

b) User and System Programs

c) User and Kernel

d) Hardware and Kernel

Which of the following is NOT a system program?

a) File Management Utilities

b) Compilers

c) Text Editors

d) Web Browsers

System programs are designed to:

a) Allow user interaction with hardware directly

b) Facilitate development of user applications

c) Manage system resources

d) Execute system calls directly

The layered approach to system structure implies:

a) Each layer is independent of others

b) Lower layers provide services to upper layers

c) Upper layers control the lower layers directly

d) All layers operate simultaneously

In a microkernel system structure, most of the operating system functions are:

a) Located in the kernel

b) Implemented in user space

c) Not present

d) Controlled by hardware

During the system boot process, the first program that is typically loaded is:

a) Bootloader

b) Operating System

c) BIOS/UEFI

d) Kernel

Which of the following steps occurs first during the system boot process?

a) Loading the Kernel

b) Loading the Bootloader

c) Power-On Self Test (POST)

d) Initializing System Services

Question Bank Operating Systems

 

Operating System Question Bank

Unit-1

1. Define Operating System and explain the various types of Operating Systems?

2. Explain Operating System Structures?

3. Explain the different functions of an operating system and discuss the various services provided by an operating system.

4. Explain about the dual mode operation in OS with a neat block diagram.

5. What is operating system? Explain multiprogramming and time sharing systems.

6. Explain briefly concept of virtual machines

7. Write the differences between monolithic kernel and microkernel.

8. Explain briefly system calls with examples.

9. Explain different operations performed by the operating system.

10. Explain different types of system calls with suitable example.

11. What are the functionalities of Operating Systems? Explain in detail

12. Explain difference between Multitasking and Multi Programming?

13. Explain briefly User and Operating System Interface

Unit-2

1. Define Process? Explain process State diagram? Explain about process schedulers?

2. Consider 3 processes P1, P2 and P3, which require 5, 7 and 4 time units and arrive at time 0, 1 and 3. Draw the Gant chart, process completion sequence and average waiting time for. i) Round robin scheduling with CPU quantum of 2 time units. ii) FCFS.

3. Explain CPU Scheduling Algorithms with examples?

4. Explain about Scheduling Criteria.

5. Evaluate FCFS CPU Scheduling algorithm for given Problem Problem and Average Turn Around Time and Average Response Time  

Process	P1	P2	P3	P4
Process Time	24	3	5	6

6. Evaluate SJF CPU Scheduling algorithm for given Problem and Average Turn Around Time and Average Response Time  

Process	P1	P2	P3	P4
Process Time	8	4	9	5
Arrival Time	0	1	2	3

7. Evaluate Round CPU Scheduling algorithm for given Problem Time slice =3 ms.

Process	P1	P2	P3	P4
Process Time	10	5	18	6
Arrival Time	5	3	0	4

8. Explain in detail Inter Process Communication? 

9. With a neat sketch explain process state diagram.

10.  Write the difference between user level thread and kernel level thread?            

11. What are the criteria for evaluating the CPU scheduling algorithm?      

12. What is a process? Explain Process Control Block.

Unit-3

1. What is critical section problem? Explain with example?   

2. What is Semaphore? Explain producer consumer problem using semaphore?      

3. Define process synchronization and explain any one method of synchronization?           

4. What is Monitor? Explain with any example using monitor?        

5. Explain the solution for Dining-Philosophers Problem    

6. What are the methods for handling deadlock.  

7. Write about deadlock and starvation?

8. Explain about Deadlock Avoidance?     

9. Explain how recovery from deadlock? 

10. Explain Dead lock detection (Banker’s Algorithm) with Example?           

11. Write about Deadlock Prevention Methods?  

12. What is synchronization? What are the different synchronization mechanisms? Explain in detail.

13. Discuss about the following   

A)           Semaphore        

B)           Monitor

 

Data Analytics MCQ Unit-I

UNIT- I

 1.   _______________ is high volume, high velocity and high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.

[A]      Data mining

[B]      Big data

[C]      Data warehouse

[D]     Business Intelligence

2.   The important 3V’s in big data are_______________________.

[A]      volume, vulnerability,variety

[B]      volume, velocity and variety

[C]      variety,vulnerability,volume

[D]     velocity,vulnerability,variety

 

3.   ________ refers to the evolving types and growing sources of data, including semi-structured and unstructured data.

[A]      Velocity

[B]      Variety

[C]      Volume

[D]     Value

4.   _________ in the context of big data refers to the speed of data acquisition and processing.

[A]      Variety

[B]      Volume

[C]      Velocity

[D]     Value

 

5.   Which of these is NOT one of the 4 V’s?

[A]      Volume

[B]      Velocity

[C]      Variety

[D]     Voice

6.   Big data is an evolving term that describes any voluminous amount of data that has the potential to be mined for information.

[A]      Structured

[B]      Semi-structured

[C]      Unstructured

[D]     All the above

 

7.   Variety refers to ______________.

[A]      structured data

[B]      unstructured data

[C]      semi-structured data

[D]     all the above

 

 8.   Which of the following term is appropriate to data that involve volume, variety, velocity?

[A]      Large Data

[B]      Big Data

[C]      Dark Data

[D]     None of the above

 

9.   Which of the following is not a major data analysis approaches?

[A]      Data Mining

[B]      Predictive Intelligence

[C]      Business Intelligence

[D]     Text Analytics

 

10.  _______________ concerns all data which can be stored in database SQL in table with rows and columns

[A]      Semi-structured data

[B]      Unstructured data

[C]      Structured data

[D]     None of the above

 

11.  _______________ is information that doesn’t reside in a relational database but that does have some organizational properties that make it easier to analyze.

[A]   Structured data

[B]   Unstructured data

[C]   Semi-structured data

[D]  None of the above

12.  _________ refers to information that either does not have a predefined data model or is not organized in a predefined manner.

[A]   Structured data

[B]   Semi-structured data

[C]   Unstructured data

[D]  None of the above

 

 13.  ___________Is the discovery and communication of meaningful patterns in data.

[A]   Structured data

[B]   Semi-structured data

[C]   Analytics

[D]  None of the above

 

14.  Analytics often favors ____________ to communicate insight.

[A]   Data Cleansing

[B]   Data Integration

[C]   Data Replication

[D]  Data visualization

 

15.  Point out the wrong statement.

[A]   The big volume indeed represents Big Data

[B]   The data growth and social media explosion have changed how we look at the data

[C]   Big Data is just about lots of data

[D]  All of the mentioned

16.  Data Analysis is a process of?

[A]   inspecting data

[B]   cleaning data

[C]   transforming data

[D]  All of the above

17.  Which of these is NOT a type of Analytics?

[A]   Predictive Analytics

[B]   Result Analytics

[C]   Prescriptive Analytics

[D]  Descriptive Analytics

18.  ____________ uses data to determine the probable future outcome of an event or a likelihood of a situation occurring.

[A]   Descriptive analytics

[B]   Prescriptive analytics

[C]   Predictive Analytics

[D]  None of the above

 19.  ___________ looks at past performance and understands that performance by mining historical data to look for the reasons behind past success or failure.

[A]  Descriptive analytics

[B]   Prescriptive analytics

[C]   Predictive Analytics

[D]  None of the above

20.  ___________ goes behind predicting future outcomes by also suggesting actions to benefit from the predictions and showing the decision maker the implications of each decision option.

[A]   Descriptive analytics

[B]   Prescriptive analytics

[C]   Predictive Analytics

[D]  None of the above

 

21.  ______________ refers to computer based techniques used in spotting, digging-out and analyzing business data.

[A]   Data mining

[B]   Big data

[C]   Data warehouse

[D]  Business Intelligence

 

22.  __________________ is defined as the capability that enables the mobile workforce to gain business insights through information analysis using applications optimized for mobile devices.

[A]   Data mining

[B]   Big data

[C]   Data warehouse

[D]  Mobile Business Intelligence

23.  __________ is the potential for a loss related to our data.

[A]   Cost risk

[B]   Schedule risk

[C]   Data risk

[D]  Performance risk

24.  Which of the following is type of data risk?

[A]   Data Security

[B]   Data Privacy

[C]   Bad data

[D]  All of the above

25.  Which of following is/are the Big Data Technologies

[A]   Operational Big Data Technologies

[B]   Analytical Big Data Technologies

[C]   Both of the above

[D]  None of the above

 26.  ___________ is a technique in which a network of remote servers is hosted on the Internet.

[A]   Data Analytics

[B]   Cloud Computing

[C]   Big Data

[D]  Data warehouse

27.  The big data are collected from a wide variety of sources.

[A]  True

[B]   False

[C]   Cannot say

[D]  Undefined

28.  Crowd sourcing involves obtaining work, information, or opinions from a large group of people who submit their data via ________________.

[A]   Internet          

[B]   social media        

[C]   smartphone apps        

[D]  all of the above

 29.  Cloud Computing is ________ of data analytics

[A]   dependent

[B]   independent

[C]   proportional

[D]  None of the above

30.  Big data is used to uncover___________________________.

[A]   hidden patterns&unknown correlations

[B]   market trends & customer preferences

[C]   other useful information

[D]  all the above

Data Analytics MCQ Unit-II

 

UNIT- II

 

1.   _____________ is an interdisciplinary field of scientific methods, process and systems to extract knowledge or insights from data in various forms, either structured or unstructured.

[A]      Data mining
[B]      Data science
[C]      Data warehouse
[D]     None of the above

 

2.   _____________is the technology which uses the transformed and loaded historical data to get or create the reports.

[A]      Data mining
[B]      Big data
[C]      Business Intelligence
[D]     None of the above

 

3.   The process of conversion of data often through the use of scripting languages to make it easier to work with is known as _______________.

[A]      Big data
[B]      Business Intelligence
[C]      Data wrangling
[D]     None of the above

 

4.   A _____________ is a storage repository that holds a vast amount of raw data in its native format until it is needed and refined elsewhere.

[A]      Big data
[B]      Data lake
[C]      Data wrangling
[D]     None of the above

 

5.   In ________________ data is stored at the leaf level in an untransformed or nearly untransformed state.

[A]      Big data
[B]      Data lake
[C]      Data wrangling
[D]     None of the above

 

6.   In _______________ data is transformed and schema is applied to fulfill the needs of analysis.

[A]      Big data
[B]      Data lake
[C]      Data wrangling
[D]     None of the above

 

7.   A____________ is a database which is kept separate from the organization’s operational database

[A]      Big data
[B]      Data warehouse
[C]      Data wrangling
[D]     None of the above

 

8.   A _______________ is constructed by integrating data from multiple heterogeneous sources that support analytical reporting, structured and decision making.

[A]      Big data
[B]      Data warehouse
[C]      Data wrangling
[D]     None of the above

 

9.   The view over an operational data warehouse is known as a ________________.

[A]      data lake
[B]      virtual warehouse
[C]      data wrangling
[D]     None of the above

 

10.              ____________ contains a subset of organization-wide data

[A]      Data lake
[B]      Virtual warehouse
[C]      Data Mart
[D]     None of the above

 

11.  An_________________ collects all the information and the subjects spanning an entire organization.

[A]      Data lake
[B]      enterprise warehouse
[C]      Data wrangling
[D]     None of the above

 

12.  ______________ involves gathering data from multiple heterogeneous sources.

[A]      Refreshing
[B]      Data extraction
[C]      Data cleaning
[D]     None of the above

 

13.  ______________ involves finding and correcting the errors in data

[A]      Data extraction
[B]      Data cleaning
[C]      Data transformation
[D]     None of the above

 

 

14.  ______________ involves converting the data from legacy format to warehouse format.

[A]      Data extraction
[B]      Data cleaning
[C]      Data transformation
[D]     None of the above

 

15.  ______________ involves sorting, summarizing, consolidating, checking integrity and building indices and partitions.

[A]      Data extraction
[B]      Data loading
[C]      Data transformation
[D]     None of the above

 

16.  ______________ involves updating from data sources to warehouse.

[A]   Data extraction
[B]   Data cleaning
[C]   Refreshing
[D]  None of the above

 

17.  ____________ describes a resource for purposes such as discovery and identification.

[A]   Structural metadata
[B]   Administrative metadata
[C]   Descriptive metadata
[D]  None of the above

 

18.  ____________ indicates how compound objects are put together.

[A]  Structural metadata
[B]   Administrative metadata
[C]   Descriptive metadata
[D]  None of the above

 

19.  ____________ provides information to help manage a resource.

[A]   Structural metadata
[B]   Administrative metadata
[C]   Descriptive metadata
[D]  None of the above

 

20.  ____________ contains the data ownership information, business definition and changing policies.

[A]   Operational metadata
[B]   Administrative metadata
[C]   Business metadata
[D]  None of the above

 

21.  ____________ includes currency of data and data lineage.

[A]   Administrative metadata
[B]   Operational metadata
[C]   Business metadata
[D]  None of the above

 

22.  ____________ includes dimension algorithms, data on granularity, aggregation and summarizing.

[A]   Administrative metadata
[B]   Operational metadata
[C]   The algorithms for summarization
[D]  None of the above

 

23.  _______ is an agile, iterative data science methodology to deliver predictive analytics solution and intelligent applications efficiently.

[A]   ASP
[B]   PSP
[C]   DSP
[D]  None of the above

 

24.  _____________ is an environment for building scalable machine learning algorithms.

[A]   Python
[B]   Apache Mahout
[C]   SQL
[D]  None of the above

 

25.  _____________ is a cluster-computing framework for data analysis.

[A]  Apache Spark
[B]   Python
[C]   SQL

[D]  None of the above

 

26.  _____________ is the massive parallel processing database for Apache Hadoop.

[A]   Python
[B]   SQL
[C]   Impala
[D]  None of the above

 

27.  _____________ is a computational platform for real-time analytics,

[A]   Python
[B]   Apache Storm
[C]   SQL
[D]  None of the above

 

28.  _____________ is a NoSQL database known for its scalability and high performance.

[A]   Python
[B]   SQL
[C]   MongoDB
[D]  None of the above

 

29.  _____________ is a JavaScript library for building interactive data visualization within your browser.

[A]   Apache Spark
[B]   SQL
[C]   D3
[D]  None of the above

 

30.  _____________ is the product of Google’s Brain Team coming together for the purpose of advancing machine learning.

[A]   Apache Spark
[B]   SQL
[C]   Tensor Flow

[D]  None of the above