Question 1

What is Big Data?

Accepted Answer

Big Data refers to all the data sets that are so large that it is not possible to manage them with conventional data-processing application software. Big Data consists of structured and unstructured data sets such as videos, photos, audio, websites, and multimedia content.

Question 2

Where is Big Data used and processed in the real-world?

Accepted Answer

Many businesses deal with large volumes of content like sets such as videos, photos, audio, websites, and multimedia content, open-ended surveys, etc. Here are a few examples of real-world applications of Big Data:   
 Banking and Securities:  Big Data is used to monitor financial market activity, perform risk analysis, track user behavior, and catch illegal trading activity.

Communications, Media and Entertainment:  Big Data is used to collect, analyze, and utilize consumer insights and understand patterns of real-time, media content usage to create better content.

Healthcare Providers:  The use of Big Data in the public health sector helps create visual data for faster and efficient analysis of healthcare information used in the tracking of diseases.

Education:  The use of Learning Management Systems in schools and universities helps students and teachers track progress regularly. Big Data is also used to analyze teacher effectiveness and performance. Big Data also studies study patterns by analyzing click patterns to track boredom during remote learning sessions.

Question 3

How does Big Data work?

Accepted Answer

There are three activities to look at when working with big data:

Data Integration:  This involves collecting and merging data from various sources and molding it into something that can be analyzed to provide insights.

Data Management:  A lot of Big Data is unstructured, so it needs to be saved in repositories from where it can be easily retrieved.

Data Analysis:  The Big Data investment return includes details on buying patterns and customer choices. AI and machine learning tools help in analyzing and representing the large data sets.

Question 4

What are the 5 Vs in Big Data?

Accepted Answer

Volume:  It is the size and amount of big data that companies analyze and manage.    
 Value:  The value of big data comes from effective operations carried out because of insight discovery and pattern recognition.

Variety:  the diversity and range of different data types, including unstructured data, semi-structured data and raw data

Velocity:  This refers to the speed at which companies receive, store and manage data.

Veracity : It refers to the accuracy of data and information assets.

Question 5

How is Hadoop and Big Data related?

Accepted Answer

Hadoop is an open-source software program that helps deal with Big Data. Hadoop stores, processes, and analyzes complex unstructured data sets to derive actionable insights.

Question 6

How does the role of a data scientist differ from that of a data engineer?

Accepted Answer

A Data Scientist builds and train predictive models using data stored in the systems built and managed by Data Engineers.

Question 7

What are the different types of Big Data?

Accepted Answer

Structured Data:  It is a type of data that can be processed, stored, and retrieved in a certain format. Structured data contains organized information like phone numbers, social security numbers, ZIP codes, employee information, and salaries.

Unstructured Data:  Data sets such as audio, video, social media posts, digital surveillance data, and satellite data fal under this category. They have no specific structure or form.

Semi-structured Data:  It consists of emails, XML and other markup languages, zipped files, binary executables, etc. integrated from different sources, and web pages. It consists of structured and unstructured data formats and is unspecified yet important.

Question 8

How does Network File System (NFS) differ from Hadoop Distributed File System (HDFS)?

Accepted Answer

HDFS is a file system in which data is distributed among many data nodes or networked computers. NFS is a file system or protocol which allows its client to access the file over the network. HDFS is used to store and process big data. On the other hand, NFS can store and process a small amount of data.

Question 9

What is Distributed Cache?

Accepted Answer

Distributed Cache is a service of the Hadoop MapReduce framework used to cache the files whenever required by the applications. The service can cache read-only text files, archives, and jar files. These can be accessed and read on each data node where map/reduce tasks are running.

Question 10

Which modes can Hadoop run on?

Accepted Answer

Standalone mode:  The default mode in which Hadoop runs. It uses the local file system for all the input and output and is the fastest Hadoop modes.   
 Pseudo Distributed mode:  It is also known as single node cluster. All NameNode and DataNode reside on the same machine in this node.

Fully distributes mode:  It is the production mode of Hadoop that runs multiple nodes. It is also known as the multiple node cluster.

Question 11

When is Map Reduce used with Big Data?

Accepted Answer

Hadoop MapReduce is a software framework that helps with distributed computation on big data sets in parallel. MapReduce is used for querying and selecting data in the Hadoop Distributed File System (HDFS). It is also a good choice for iterative computation with large quantities of data that need parallel processing.

Question 12

How can cross-validation help with prevention of overfitting?

Accepted Answer

Overfitting is a modelling error. Cross-validation is a method that divides data into multiple small test data sets, so that these can be used to tune the model.

Question 13

How does using a zookeeper help with serialization and process coordination?

Accepted Answer

Zookeeper is a technology that helps manage a large set of hosts. It is a distributed coordination service that helps with a simplified distributed coordination process among all nodes. It also takes care of serialization as it encodes the data according to specific rules to keep the application running consistently.

Question 14

What command is used to copy data from the local system onto HDFS?

Accepted Answer

The command used for copying data from the Local system to HDFS is:   
hadoop fs –copyFromLocal [source][destination]

Question 15

How can you skip bad records in Hadoop?

Accepted Answer

Hadoop has an option of skipping lousy input records while processing map inputs. SkipBadRecords class in Hadoop’s optional mode of execution can detect and neglect bad records in multiple attempts. This feature ensures that there is minimum data loss, which is acceptable when we handle large amounts of data.

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