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 companies are inclined towards the use of big data in order to functionally run their operations. From data analysts, data scientists to Big Data Engineer, the positions are numerous 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.
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.
The five V’s of big data are;
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.
Various tools are used for the purpose of importing, sorting as well as analyzing data. Some of these tools are;
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.
Clustering is the process of grouping of similar objects into sets which are known as clusters. Clustering is an essential part in data mining. It is also used in statistical data analysis. Some of the popular clustering methods include partitioning, hierarchical, density-based as well as model based.
Also, objects clustered in one group are most likely different than the objects clustered in another group.
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.
It is obvious that this question would have no specific answer since it is an objective answer. With these kind of big data interview questions, the interviewer wants to hear from you about your experience. They also want to know about your working techniques and whether you would be fit for the job role that you are interviewing for or not.
Make sure to give a detailed answer to these kind of big data interview questions. Share all your past experiences and also add stories to your answer so that the answers sound interesting. Give details about all the major tasks that you underwent while at your previous job. And also state all the projects that you were a part of and made contributions to.
But you need to be careful about the fact that you do not make your answer go overboard. This question is generally asked during the starting of the interview itself. So you need to be very careful by answering 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.
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.
Undoubtedly, Hadoop and Big Data go hand in hand. The functioning of Hadoop depends on Big data. And the processing of Big Data is dependent on Hadoop. Basically, Hadoop is the gateway for modelling all other applications for 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.
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.
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.
Deploying Big Data Selection comprises of three steps;
The three major components of Hadoop are:
HDFS — It is a java based distributed file system. It is basically used for data storage. And it requires no prior organization.
MapReduce — It is a programming model. MapReduce processes large data sets in parallel.
YARN — Yarn is a framework that manages resources as well as handles requests from all the distributed applications.
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.
Scalability: Hadoop runs on commodity hardware. But even then, additional hardware resources can be added to new nodes.
User-Friendly: The user interface of Hadoop is very simple. Therefore the framework of Hadoop is perfect. Clients do not have to handle distributed computing processes anymore because the framework 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.
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!