Interview Questions

Big Data Interview Questions that you Can‚Äôt Miss to Prepare!8 min read

March 4, 2020 6 min read
big data interview questions

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Big Data Interview Questions that you Can‚Äôt Miss to Prepare!8 min read

Read­ing Time: 6 min­utes

Data is empow­er­ing every­thing around us. It is the era of big data sci­ence and ana­lyt­ics and that is why the demand for skilled data pro­fes­sion­als has increased mas­sive­ly. There­fore, we are pro­vid­ing you with a list of most fre­quent­ly asked big data inter­view ques­tions and answers. So that you can pre­pare for the big data and be assured of success.

More and more com¬≠pa¬≠nies are inclined towards the use of big data in order to func¬≠tion¬≠al¬≠ly run their oper¬≠a¬≠tions. From data ana¬≠lysts, data sci¬≠en¬≠tists to Big Data Engi¬≠neer, the posi¬≠tions are numer¬≠ous to choose from if you want to start a career in the field of big data.

Being well pre­pared for the big data inter­view ques­tions and answers will give you an edge over the oth­er appli­cants. This arti­cle has a list of ques­tions rang­ing from the most basic to the most advanced ones.

1. What do you understand by Big Data?

Big data is a col­lec­tion of com­plex unstruc­tured or semi-struc­tured large data sets. These sets help a com­pa­ny in gain­ing action­able insights. These insights help the busi­ness­es under­stand their work­ing in a deep­er sense. The data col­lect­ed ana­lyzes and uncov­ers pat­terns and infor­ma­tion which oth­er­wise might not be available.

2. Define the five V‚Äôs of Big Data?

The five V‚Äôs of big data are;

  • Vol¬≠ume: It is the data vol¬≠ume in Petabytes which gives infor¬≠ma¬≠tion about the amount of data which grows at a high rate.
  • Vari¬≠ety: The data types curat¬≠ed from Big Data pro¬≠cess¬≠ing are of var¬≠i¬≠ous kinds. For instance, data for¬≠mats of text, audio and videos.
  • Veloc¬≠i¬≠ty: Veloc¬≠i¬≠ty is sim¬≠ply the rate at which the data grows.
  • Verac¬≠i¬≠ty: High vol¬≠ume of data often brings in incon¬≠sis¬≠ten¬≠cy and incom¬≠plete¬≠ness. There¬≠fore, veloc¬≠i¬≠ty indi¬≠cates this uncer¬≠tain¬≠ty in data.
  • Val¬≠ue: Busi¬≠ness can also gen¬≠er¬≠ate rev¬≠enue by con¬≠vert¬≠ing the accessed big data into values.

Know that this is one of the most com­mon ques­tions asked in the inter­view. How­ev­er it depends on you as to how you wish to answer the ques­tion, depend­ing upon the response of the inter­view­er. You can men­tion only the names if that is what asked. Or you could explain the five V’s fur­ther in detail if the recruiter is inter­est­ed in hear­ing from you further.

3. Mention some of the best tools used for Big Data?

Var¬≠i¬≠ous tools are used for the pur¬≠pose of import¬≠ing, sort¬≠ing as well as ana¬≠lyz¬≠ing data. Some of these tools are;

  • Apache Spark
  • Apache Hive
  • Cas¬≠san¬≠dra
  • Apache Flume
  • Apache Pig
  • Mon¬≠goDB
  • Apache Splunk
  • Apache Hadoop
  • MapRe¬≠duce
  • Apache Sqoop

4. Explain how big data analysis is helpful in increasing business revenue?

With this answer, you can actu­al­ly explain to the recruiter as to why you think big data is impor­tant. The first and fore­most rea­son is that it explains the dif­fer­ences between the busi­ness­es and that is how they increase the rev­enue. Big data ana­lyt­ics also helps busi­ness­es ana­lyze the needs and pref­er­ences of the cus­tomers through big data solu­tions, on the basis of which they launch new products.

5. Define what is clustering?

Clus¬≠ter¬≠ing is the process of group¬≠ing of sim¬≠i¬≠lar objects into sets which are known as clus¬≠ters. Clus¬≠ter¬≠ing is an essen¬≠tial part in data min¬≠ing. It is also used in sta¬≠tis¬≠ti¬≠cal data analy¬≠sis. Some of the pop¬≠u¬≠lar clus¬≠ter¬≠ing meth¬≠ods include par¬≠ti¬≠tion¬≠ing, hier¬≠ar¬≠chi¬≠cal, den¬≠si¬≠ty-based as well as mod¬≠el based.

Also, objects clus¬≠tered in one group are most like¬≠ly dif¬≠fer¬≠ent than the objects clus¬≠tered in anoth¬≠er group.

6. How would you justify Big Data Analytics as important?

Big Data ana­lyt­ics has been use­ful and impor­tant for busi­ness­es because it helps busi­ness­es equip data. This equip­ment and data stor­age helps them to iden­ti­fy and not miss the new oppor­tu­ni­ties. Because of this fac­tor, busi­ness­es do not end up mak­ing absurd decisions.

More­over, busi­ness­es tend to make smarter deci­sions and moves. As a result, there are effi­cient oper­a­tions and high­er prof­its for the business.

7. Do you have any experience in Big Data Analytics? If so, then explain about it.

It is obvi¬≠ous that this ques¬≠tion would have no spe¬≠cif¬≠ic answer since it is an objec¬≠tive answer. With these kind of big data inter¬≠view ques¬≠tions, the inter¬≠view¬≠er wants to hear from you about your expe¬≠ri¬≠ence. They also want to know about your work¬≠ing tech¬≠niques and whether you would be fit for the job role that you are inter¬≠view¬≠ing for or not.

Make sure to give a detailed answer to these kind of  big data inter¬≠view ques¬≠tions. Share all your past expe¬≠ri¬≠ences and also add sto¬≠ries to your answer so that the answers sound inter¬≠est¬≠ing. Give details about all the major tasks that you under¬≠went while at your pre¬≠vi¬≠ous job. And also state all the projects that you were a part of and made con¬≠tri¬≠bu¬≠tions to.

But you need to be care¬≠ful about the fact that you do not make your answer go over¬≠board. This ques¬≠tion is gen¬≠er¬≠al¬≠ly asked dur¬≠ing the start¬≠ing of the inter¬≠view itself. So you need to be very care¬≠ful by answer¬≠ing this one.

All of the oth­er answers that shall be asked to you in the inter­view will be based on the answer you give for this ques­tion. There­fore, do not just stick to one aspect of your pre­vi­ous experience.

8. Would you prefer good data or good models? Give reasons for your choice.

Most can­di­dates pre­fer to answer this ques­tion accord­ing to their expe­ri­ence. Just be sure to nev­er choose both options as your answer because this answer would lack prac­ti­cal­i­ty. It is hard to have both good data as well as mod­els in actuality.

If you answer the ques­tion from your expe­ri­ence, you will also have valid rea­sons to prove your choice of the answer. This way you would be able to give a detailed answer and not sound absurd.

9. How are Big Data and Hadoop related?

Undoubt¬≠ed¬≠ly, Hadoop and Big Data go hand in hand. The func¬≠tion¬≠ing of Hadoop depends on Big data. And the pro¬≠cess¬≠ing of Big Data is depen¬≠dent on Hadoop. Basi¬≠cal¬≠ly, Hadoop is the gate¬≠way for mod¬≠el¬≠ling all oth¬≠er appli¬≠ca¬≠tions for Big Data.

10. Specify what are the essential Hadoop tools that are required for effective working of Big Data?

Hadoop has a num­ber of essen­tial tools that help in enhanc­ing the per­for­mance of big data. Ambari, “HBase, ZooKeep­er, Mahout, Flume, Hadoop Dis­trib­uted File Sys­tem, Sqoop, Pig are some of the examples.

11. Why do you think Hadoop is needed?

The main rea­son why Hadoop is need­ed is because it brings scal­a­bil­i­ty. It gets easy to build solu­tions for a spe­cif­ic amount of data. On the oth­er hand, get­ting solu­tions for increas­ing the amount of data is complex.

12. How do you think Apache Hadoop resolves the challenge of big data storage?

The strong file sys­tem of Hadoop, HDFS enables solv­ing all ends of the data stor­age. HDFS is stored as a bina­ry so it does not have any schema and is high­ly com­pressed in nature. In fact, the file sys­tem also main­tains redun­dan­cy. Due to this, there is data reli­a­bil­i­ty even in con­di­tions when the machine fails.

13. Mention the steps taken to deploy a Big Data Selection?

Deploy¬≠ing Big Data Selec¬≠tion com¬≠pris¬≠es of three steps;

  • Inges¬≠tion of Data
  • Data Stor¬≠age
  • Data Pro¬≠cess¬≠ing

14. What are the components of Hadoop?

The three major com­po­nents of Hadoop are:

HDFS ‚ÄĒ It is a java based dis¬≠trib¬≠uted file sys¬≠tem. It is basi¬≠cal¬≠ly used for data stor¬≠age. And it requires no pri¬≠or organization.

MapRe¬≠duce ‚ÄĒ It is a pro¬≠gram¬≠ming mod¬≠el. MapRe¬≠duce process¬≠es large data sets in parallel.

YARN ‚ÄĒ Yarn is a frame¬≠work that man¬≠ages resources as well as han¬≠dles requests from all the dis¬≠trib¬≠uted applications.

15. Define the various features of Hadoop.

This ques­tion is also one of the most asked big data inter­view ques­tions. The var­i­ous fea­tures of Hadoop are;

Open-Source: Open Source frame­works are inclu­sive of source codes. These source codes are avail­able as well as acces­si­ble all over the World Wide Web. These code snip­pets can also be rewrit­ten, edit­ed or mod­i­fied. This depends on the require­ments of the users and the analytics.

Scal¬≠a¬≠bil¬≠i¬≠ty: Hadoop runs on com¬≠mod¬≠i¬≠ty hard¬≠ware. But even then, addi¬≠tion¬≠al hard¬≠ware resources can be added to new nodes.

User-Friend¬≠ly: The user inter¬≠face of Hadoop is very sim¬≠ple. There¬≠fore the frame¬≠work of Hadoop is per¬≠fect. Clients do not have to han¬≠dle dis¬≠trib¬≠uted com¬≠put¬≠ing process¬≠es any¬≠more because the frame¬≠work takes care of it.

Data Recov­ery: Hadoop splits blocks into three repli­cas across clus­ters, there­by allow­ing the recov­ery of data. It allows the users to recov­er data from node to node. The recov­ery is need­ed in cas­es of fail­ure. Hadoop recov­ers these tasks and nodes auto­mat­i­cal­ly in such circumstances.

Data Local­i­ty: Data Local­i­ty is the fea­ture of Hadoop which moves com­pu­ta­tion to data instead of mov­ing data to com­pu­ta­tion. Data is there­by moved to clus­ters instead of being brought to a loca­tion where­in MapRe­duce algo­rithms are processed as well as submitted.

16. What are Edge Nodes in Hadoop?

The gate­way nodes in Hadoop which act as the inter­face between the exter­nal net­work and the hadoop clus­ter are the Edge Nodes. The run­ning of client appli­ca­tions and clus­ter admin­is­tra­tion tools in Hadoop is done by Edge nodes. These are then used as stag­ing areas for data trans­fers to the Hadoop clusters.

The world of Big Data is extend­ing con­tin­u­ous­ly. And so are the job oppor­tu­ni­ties for big data pro­fes­sion­als. With this set of big data inter­view ques­tions and answers, you will have an idea about the kind of ques­tions that are asked. And also the kind of answers that you should be giv­ing while inter­view­ing for big data job profiles.

Good luck with your inter­view! If you are ful­ly pre­pared, there’s no stopping!

Sumedha is a Post Graduate in English. She has the penchant for creating a variety of content that is attention grabbing.