WorksheetsBig Data, MapReduce, and Cloud Computing Interview Questions
Total questions: 25
Worksheet time: 13mins
What is the primary reason for the transition from "Scale-Up" to "Scale-Out" architecture in Big Data? [+3]
To use more expensive, high-performance hardware
To achieve better cost-effectiveness for datasets ranging from 100TB to 1PB
To reduce the number of servers needed for processing
To simplify the network connectivity between clients and servers
Which of the following is considered "Unstructured Data"?
Zip codes and phone numbers
Dates and addresses
Audio and social media data
XML and markup languages
According to the "3 Vs" of Big Data, "Velocity" refers to:
The physical size of the data stored
The speed at which data is being accumulated
The variety of data types like structured and unstructured
The accuracy and reliability of the data source
In the history of computing, which machine is recognized as the world’s first electronic digital programmable computer used for cryptanalysis? [+3]
ENIAC
Analytical Engine
Colossus
Stone Tablet
How does a "Parallel Cluster" architecture differ from a traditional "Client-Server" architecture? [+2]
It requires a central server to pull data for processing
It processes data where the data is stored to reduce I/O costs
It relies on high network traffic to move data to the CPU
It uses only high-end carrier-class servers
Which case study mentioned that 35% of its sales come from product recommendations? [+3]
Netflix
Google Ads
Amazon
"Prescriptive Analytics" is best described as: [+3]
Learning from the past to predict what will happen
Analyzing why something happened in the past
Taking predictions and turning them into actions or policies
Simply collecting data from SNS and blogs
What percentage of enterprise data is typically estimated to be "Unstructured"?
20%
50%
80% or more
100%
In a Big Data platform, "Fault Tolerance" is primarily achieved through: [+3]
Using the most expensive hardware available
Replicating data multiple times across different servers
Removing old data to make room for new data
Moving data to a central processing server
Which technology allows for "near-infinite scalability" and is a key driver for Big Data?
RDBMS
Cloud Computing
Traditional EDW
Local Ledgers
In the MapReduce model, what occurs during the "Shuffle and Sort" phase? [+4]
Data is read from the HDFS and converted into key-value pairs
Results from Mappers are consolidated and sent to Reducers based on keys
The final output is written to the HDFS
Users manually assign tasks to different slave nodes
Why is "Data Locality" important in MapReduce? [+4]
It moves data to the fastest central processor
It runs computation on the node where the data already resides to save bandwidth
It ensures data is only stored in one location
It helps in converting structured data to unstructured data
Which Big Data use case involves identifying connections between "nodes" and "edges"? [+3]
Sentimental Analysis
Associative Analysis (Graph Analytics)
Classification
Predictive Maintenance
What is the main "Bottleneck" in the Reduce stage of MapReduce? [+1]
The number of keys is too small
It can only start after all mappers have completed
It cannot run in parallel
It only works with Java
In Cloud Computing, which service model provides the application platform or middleware as a service?
Infrastructure as a Service (IaaS)
Software as a Service (SaaS)
Platform as a Service (PaaS)
Database as a Service (DBaaS)
Which "Workload Pattern" in Cloud Computing is characterized by a seasonal peak in demand? [+3]
On and Off
Growing Fast
Unpredictable Bursting
Predictable Bursting
What is the primary disadvantage of using multiple MapReduce cycles for a single job?
It requires too many developers
Expensive Disk I/O because intermediate results are written to disk
It cannot be used for word counts
It only works on-premises and not on the cloud
Which of the following is a key benefit of using "Platform as a Service (PaaS)" in cloud computing?
Enhanced security for on-premises data
Lower costs for data storage
Reduced complexity in application development
Complete control over the hardware
What is the primary characteristic of "Structured Data"?
It requires complex algorithms for analysis
It is typically unorganized and free-form
It is often found in text documents
It is easily searchable and organized
Which analytics type focuses on predicting future outcomes based on historical data?
Predictive Analytics
Diagnostic Analytics
Descriptive Analytics
Prescriptive Analytics
What is the primary purpose of Data Warehousing in the context of Big Data?
To ensure data security and compliance
To store data in a non-structured format
To facilitate real-time data processing
To provide a centralized repository for analysis and reporting
Which of the following is a common tool used for data visualization in Big Data analytics?
Tableau
TensorFlow
Apache Hadoop
MySQL
What is the main advantage of using "Data Lakes" over traditional data warehouses? [+3]
Data Lakes can only store structured data
Data Lakes allow for the storage of both structured and unstructured data
Data Lakes are more expensive to maintain
Data Lakes require less storage space
Which of the following best describes "Edge Computing"? [+3]
Using only local servers for data processing
Storing data in the cloud for later analysis
Processing data closer to the source of data generation
Processing data in a centralized data center
What is the primary purpose of "Data Governance" in an organization? [+3]
To reduce the cost of data storage
To automate data processing tasks
To ensure data quality and compliance with regulations
To increase the amount of data collected
