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Futuristic Big Data Interview Questions and Answers

Big Data is set to be the game changer for not one or two industries, but when taken to its logical end, for mankind. When developed to its potential, Big Data can revolutionize banking, justice, forensics, disease management and simply anything we can think of. The market for Big Data is never going to slow down or cease at any time in the foreseeable future since there is so much to be done to take Big Data to what it can fully do.


1st Round: Big Data Basic interview questions and answers:


Q1. Spell out a few interesting facts about Big Data?

Ans. Big data is big, and there is no doubt about it. These are some of the facts about Big Data:

  • Net users generate (create or send) 200 billion mails every day.
  • Half a billion tweets are sent every day.
  • Gartner estimates that data volume will grow by at least 800 percent over the next five years.
  • By 2020, each person on this planet will be consuming about 5200 GB of data.
  • By 2025, global data is expected to reach 163 ZB, according to IDC.
Q2. How much data is sufficient to get valid outcome?

Ans.  This is like asking how much alcohol a person must consume to get on a high. It varies from one person to another. A number between too less or too much has to be found. The same goes for data because different businesses work differently and use and measure data in different ways. It is finally up to the individual. The ideal volume is the one that enables you to get the right results.

Q3. Explain the four features of Big Data?

Ans.  The four features of Big Data are indicated by the four V’s to help understand the value of data and improve operational efficiency:

  • Volume
  • Velocity
  • Variety
  • Veracity
Q4. Describe logistic regression?

Ans. Logistic Regression is a technique with which the binary result from a linear amalgamation of predictor variables is predicted. It is also known as logit model.

Q5. Describe the method by which A/B testing works?

Ans.  A highly versatile method for zeroing in on the ideal online promotional and marketing strategies for any organization, A/B testing can be used to figure out everything from mails to search ads to website copy. The core objective is figuring out any modification to a

webpage to make the best use of the result of an interest.

Q6. Which three modes can Hadoop run on?

 Ans. Following are the models:

  • Standalone mode
  • Pseudo Distributed mode (Single node cluster)
  • Fully distributes mode (Multiple node cluster)
Q7. Which are the important tools useful for Big Data analytics?

Ans. Important tools useful for Big Data Analytics.

  • NodeXL
  • KNIME
  • Tableau
  • Solver
  • OpenRefine
  • Rattle GUI
  • Qlikview


Q8. Explain collaborative filtering?

Ans. Collaborative filtering is a set of technologies that predicts what a particular consumer will like depending on the preferences of several individuals. We could call it a technical word for asking suggestions from individuals.

Q9. Explain block in Hadoop Distributed File System (HDFS)?

Ans.  This is how block in Hadoop Distributed File System is understood: A file that is stored in HDFS breaks down all file systems into a set of blocks and HDFS oblivious of what is stored in the file. It is necessary for a block size to be 128MB in Hadoop. This value can be altered for individual files.

Q10. Define checkpoint

Ans.  The checkpoint is the main part of maintaining filesystem metadata in HDFS. The HDFS creates checkpoints of file system metadata by connecting fsimage with the edit log. This new version of fsimage is named as Checkpoint.

Q11. What are Active and Passive Namenodes?

Ans.  While Active NameNode runs and works in the cluster; Passive NameNode has comparable data like active NameNode.

Q12. For what purpose is JPS used?

Ans. The JPS command is one that is used to check if NodeManager, NameNode, ResourceManager and Job Tracker are working on the machine.

Q13. To what use do you put missing data?

Ans.  Missing data is a situation in which no data is stored for the variable and the data collection is insufficient. Data analysts should analyze data and determine if it is sufficient and what to with it.

Q14. Mention key components of a Hadoop application

Ans. Key components of Hadoop Application:

  • HDFS
  • YARN
  • MapReduce
  • Hadoop Common
Q15. What responsibilities does the role of a data analyst carry?

Ans. A data analyst:

  • Assists marketing executives in understanding the performance of each product or service by various criteria such as age, region, gender, season or such others
  • Tracks external trends in relation to demography or geographic location of the market to help understand the status of products in each region
  • Bring about greater understanding between the customers and the business


2nd Round: Big Data Technical Interview Questions and answers:

Q1. In what way is Hadoop related to Big Data? What are Hadoop’s components?

Ans: Hadoop by Apache is an open-source framework that is used to store, process, and analyze complex unstructured data sets with which one can derive insights and actionable intelligence for businesses.

These are the three main components of Hadoop -

  • MapReduce – This is a programming model which processes large datasets parallel to each other.
  • HDFS – HDFS is a distributed file system that stores data storage without prior organization. It is Java-based.
  • YARN – This is a framework that manages resources and handles requests from distributed applications.
Q2. Why is Hadoop required for Big Data Analytics?

Ans: Since Big Data is huge and unstructured data, is becomes unwieldy and difficult to analyze and explore in the absence of analysis tools. Hadoop, in offering storage, processing, and data collection capabilities, fills this purpose. Hadoop stores data in its raw forms without using any schema and gives the option of adding any number of nodes.

Another advantage of Hadoop is that since it is open-source and is run on commodity hardware; it is relatively inexpensive for the purpose it serves.

Q3.   Which command is used for shutting down all the Hadoop Daemons together?

Ans: ./sbin/stop-all.sh

Q4. Describe the components of YARN?

Ans: These are the two main components of YARN (Yet Another Resource Negotiator):

  • Resource Manager
  • Node Manager
Q5. Explain the various features of Hadoop. 

Ans: Listed in many Big Data Interview Questions and Answers, the answer to this is-

  • It is Open-Source- Open-source frameworks come with a source code that is available and accessible by all over the World Wide Web. It is something like the doc files that we share online, which anyone with the permission can edit. What this feature enables is for the code snippets to be edited, rewritten, and modified according to user and analytics requirements.
  • It is scalable – Hadoop runs on commodity hardware; yet, it allows the addition of extra hardware resources to new nodes.
  • Its data is recoverable – One of the core features of Hadoop is that its data can be recovered. This is done by splitting blocks into three replicas across clusters. With Hadoop, users can recover data from node to node in cases of failure. It also enables recovery of tasks/nodes automatically during such instances.
  • Hadoop is extremely user-friendly – Users that are new to Data Analytics will swear by the user friendliness that Hadoop brings. It is the ideal framework to use, as its user interface is very simple. Also, clients don’t need to handle distributed computing processes, since the framework takes care of it.
  • It has Data Locality – With the Hadoop Data Locality feature, computation is moved to data instead of data to computation. Data, on the other hand, is moved to clusters rather than being brought to the location where MapReduce algorithms are processed and submitted.
Q6. Which are the different tombstone markers used for deletion purposes in HBase?

Ans: These are the three main tombstone markers used for deletion in HBase:

  1. Family Delete Marker, which marks all the columns of a column family.
  2. Version Delete Marker, which marks a single version of a single column.
  3. Column Delete Marker, which marks all the versions of a single column.


HR Round:

Which are the common challenges faced by Hadoop developers?

What difference did you bring into a project involving Big Data that you worked on?

What future do you see for Hadoop and Big Data over the next five to 10 years?

Do you believe that Big Data can change the face of human life? In what ways do you think this can be done and when do you think we can achieve it?

Conclusion:

With the world set to see critical changes in the areas covered by Big Data; it is not surprising that Big Data professionals are set to be in very high demand. Big Data is the real engine that powers everything on the www. Technology futurists are foreseeing a world powered by Big Data, Machine Learning, Artificial Intelligence and data science that will be so dramatically different from the one in which we live that no facet of human life is going to remain the same. Big Data can change everything from healthcare to banking and from genetics to the environment. There is no better time to be in Big Data than now because this is an opportunity to be at the forefront of revolutionary changes that this technology could bring to mankind.