A skilled file clerk candidate would demonstrate awareness about alphanumeric systems and their major benefits. This sort of system works well to manage large amounts of data, improve access to files, and minimize search time. Please note that we are not your career or legal advisor, and none of the information provided herein guarantees a job offer.
Post a job. Find resumes. Help Center. Find jobs. Post a Job. No-hassle virtual interviewing free on Indeed There's no software to download or meeting links for you to manage. Here's how it works. Step 1. Step 2. Step 3. Describe a time when you created a filing system to manage the office paperwork. See answer. Q: Describe a time when you created a filing system to manage the office paperwork. A: This question allows the file clerk applicant to express their problem-solving abilities.
What to look for in an answer: Ability to work with alpha-numeric systems Creative problem-solving abilities Calm and methodical demeanor. Q: How confident are you with the software used in the role of a file clerk? A: File clerks working with digital files need to be able to effectively use the software required for the job. What to look for in an answer: Required number of years of experience for the position High-level of knowledge and aptitude about the software Willingness to stay updated on current software.
Q: How do you ensure accuracy in your data entry after performing repetitive work? A: This question is very important as the applicant will need to have a strategy for dealing with brain fatigue.
What to look for in an answer: Experience with meticulous and repetitious tasks Methods for avoiding brain fatigue Confidence in their ability to produce accurate work.
Answer: There are a number of distributed file systems that work in their own way. There are two phases of MapReduce operation. MapReduce is a programming model in Hadoop for processing large data sets over a cluster of computers, commonly known as HDFS.
It is a parallel programming model. Hadoop distributed file system HDFS uses a specific permissions model for files and directories.
Following user levels are used in HDFS —. For each of the user mentioned above following permissions are applicable —. Above mentioned permissions work differently for files and directories. The basic parameters of a Mapper are. Hadoop and Spark are the two most popular big data frameworks.
But there is a commonly asked question — do we need Hadoop to run Spark? Watch this video to find the answer to this question. The interviewer has more expectations from an experienced Hadoop developer, and thus his questions are one-level up.
Here we bring some sample interview questions for experienced Hadoop developers. Answer: To restart all the daemons, it is required to stop all the daemons first. The Hadoop directory contains sbin directory that stores the script files to stop and start daemons in Hadoop. Answer: The jps command is used to check if the Hadoop daemons are running properly or not. This command shows all the daemons running on a machine i. In this method, the replication factor is changed on the basis of file using Hadoop FS shell.
The command used for this is:. In this method, the replication factor is changed on directory basis i. Answer: The NameNode recovery process involves the below-mentioned steps to make Hadoop cluster running:. Thus, it makes routine maintenance difficult. For this reason, HDFS high availability architecture is recommended to use. This is due to the performance issue of NameNode.
Usually, NameNode is allocated with huge space to store metadata for the large-scale file. The metadata is supposed to be a from a single file for optimum space utilization and cost benefit. In case of small size files, NameNode does not utilize the entire space which is a performance optimization issue. If the data does not reside in the same node where the Mapper is executing the job, the data needs to be copied from the DataNode over the network to the mapper DataNode.
Now if a MapReduce job has more than Mapper and each Mapper tries to copy the data from other DataNode in the cluster simultaneously, it would cause serious network congestion which is a big performance issue of the overall system. Hence, data proximity to the computation is an effective and cost-effective solution which is technically termed as Data locality in Hadoop. It helps to increase the overall throughput of the system.
Data locality can be of three types :. Hadoop is not only for storing large data but also to process those big data. Hadoop uses a specific file format which is known as Sequence file. The sequence file stores data in a serialized key-value pair. Sequencefileinputformat is an input format to read sequence files. Big Data world is expanding continuously and thus a number of opportunities are arising for the Big Data professionals. So, if you want to demonstrate your skills to your interviewer during big data interview get certified and add a credential to your resume.
If you have any question regarding Big Data, just leave a comment below. Our Big Data experts will be happy to help you. Expecting to prepare offline with these Big Data interview questions and answers? Interviews always create some tensed situation and to make you feel easy about them you have provided some nice and important programming interview questions which will be very useful for people who are preparing for interviews.
Going to save this for sure. Hello, Thank you for this interview questions.. This will be very helpful.. You cover each and every thing very clearly.. Please provide interview question for AWS.. I used to follow you blog since long time. Thank you once again. Hi ,This blog is teally very helpful…i need your suggestion.
I have total 6. I want to switch company in big data developer how can I tell them real project experience…. You have only one option for this. You can meet any of your friends working on big data technologies and know about their project.
Can we change the block size in Hadoop after i have spun my clusters? If yes how could we achieve this and how much effort is required? How can we decommission and commission a data node answer with commands will really help? How about connections being made to Big Data? Some Data Manipulation questions etc? How can we connect to Big Data from assuming C , Java etc? Great read! Thank you for such useful insights.
Visit here for latest tech courses on Talend Big Data training. Nice blog. I think other web-site proprietors should take this website as an model, very clean and excellent user genial style and design, let alone the content.
You are an expert in this topic! No company can operate without data in modern times. With large volumes of data being created each second from transactions, customer logs, sales figures, and company stakeholders, data is the key fuel that steers a company forward. All these inbound data collects into piles and forms a huge set of data known as Big Data. Whizlabs Education INC. All Rights Reserved.
The certification names are the trademarks of their respective owners. Logo are registered trademarks of the Project Management Institute, Inc. All rights reserved. Sign in Join. Sign in. Log into your account. Sign up. Password recovery. Recover your password. Forgot your password? Get help. Create an account. Whizlabs Blog. Social media contributes a major role in the velocity of growing data. Variety — Variety refers to the different data types i.
Veracity — Veracity refers to the uncertainty of available data. Veracity arises due to the high volume of data that brings incompleteness and inconsistency.
Value — Value refers to turning data into value. By turning accessed big data into values, businesses may generate revenue. Tell us how big data and Hadoop are related to each other. How is big data analysis helpful in increasing business revenue? Explain the steps to be followed to deploy a Big Data solution. Answer: Followings are the three steps that are followed to deploy a Big Data Solution — i. Data Ingestion The first step for deploying a big data solution is the data ingestion i.
Steps of Deploying Big Data Solution ii. Data Storage After data ingestion, the next step is to store the extracted data. Data Processing The final step in deploying a big data solution is the data processing. Why is Hadoop used for Big Data Analytics? Analyzing unstructured data is quite difficult where Hadoop takes major part with its capabilities of Storage Processing Data collection Moreover, Hadoop is open source and runs on commodity hardware.
What is fsck? Hence, data redundancy is a common issue in HDFS. On the contrary, the replication protocol is different in case of NAS. Thus the chances of data redundancy are much less. Data is stored as data blocks in local drives in case of HDFS. In case of NAS, it is stored in dedicated hardware. What is the Command to format the NameNode? Experience-based Big Data Interview Questions If you have some considerable experience of working in Big Data world, you will be asked a number of questions in your big data interview based on your previous experience.
So, get prepared with these best Big data interview questions and answers — Do you have any Big Data experience? If so, please share it with us. Do you prefer good data or good models? Will you optimize algorithms or code to make them run faster? How do you approach data preparation? How would you transform unstructured data into structured data?
This is one of the most frequently asked data analyst interview questions, and the interviewer expects you to give a detailed answer here, and not just the name of the methods. There are four methods to handle missing values in a dataset. In the listwise deletion method, an entire record is excluded from analysis if any single value is missing. It creates plausible values based on the correlations for the missing data and then averages the simulated datasets by incorporating random errors in your predictions.
Normal Distribution refers to a continuous probability distribution that is symmetric about the mean. In a graph, normal distribution will appear as a bell curve. Time Series analysis is a statistical procedure that deals with the ordered sequence of values of a variable at equally spaced time intervals. Time series data are collected at adjacent periods.
So, there is a correlation between the observations. This feature distinguishes time-series data from cross-sectional data. This is another frequently asked data analyst interview question, and you are expected to cover all the given differences! Happens when the model learns the random fluctuations and noise in the training dataset in detail. This happens when there is lesser data to build an accurate model and when we try to develop a linear model using non-linear data. Here, A11 cell has the lookup value, A2:E7 is the table array, 3 is the column index number with information about departments, and 0 is the range lookup.
Answer all of the given differences when this data analyst interview question is asked, and also give out the syntax for each to prove your thorough knowledge to the interviewer. Give the right location where the file name and its extension follow the dataset. An outlier is a data point that is distant from other similar points.
They may be due to variability in the measurement or may indicate experimental errors. Example: An ice cream company can analyze how much ice cream was sold, which flavors were sold, and whether more or less ice cream was sold than the day before. Sampling is a statistical method to select a subset of data from an entire dataset population to estimate the characteristics of the whole population.
Hypothesis testing is the procedure used by statisticians and scientists to accept or reject statistical hypotheses. There are mainly two types of hypothesis testing:. It states that there is no relation between the predictor and outcome variables in the population. H0 denoted it. It states that there is some relation between the predictor and outcome variables in the population.
It is denoted by H1. Univariate analysis is the simplest and easiest form of data analysis where the data being analyzed contains only one variable. Univariate analysis can be described using Central Tendency, Dispersion, Quartiles, Bar charts, Histograms, Pie charts, and Frequency distribution tables.
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