Big data is the new CRAZE. Reports suggest that investments in big data have surpassed $57 billion in 2017, and are expected to rise by 10% for the next three years.
Customers are happy – those who have applied advanced capabilities to predictive analytics, machine learning, customer analytics, customer profiles, inventory management and tracking, and more – as big data implementation across many verticals has resulted in measurable positive results.
A substantial part of the Apache project, Hadoop is an open source, Java-based programming software framework that is used for storing data and running applications on different clusters of commodity hardware. Be it any kind of data, Hadoop acts as a massive storage unit backed by gargantuan processing power and an ability to tackle virtually countless tasks and jobs, simultaneously.
In this blogpost, we are going to discuss top 10 Hadoop interview questions – cracking these questions may help you bag the sexiest job of this decade.
There are 3 layers in Hadoop and they are as follows:
Hadoop distribution includes a generic application programming interface for drawing MapReduce jobs in programming languages like Ruby, Python, Perl, etc. and this is known as Hadoop streaming.
Begin by clicking on stop-all.sh and then on start-all.sh
OR
Write sudo hdfs (then press enter), su-hdfs (then press enter), /etc/init.d/ha (then press enter) and finally /etc/init.d/Hadoop-0.20-name node start (then press enter).
Use multiple nodes and the distcp command to ensure smooth copying of files between HDFS clusters.
In case, a node executes a task slower, the master node has the ability to start the same task on another node. As a result, the task that finishes off first will be accepted and the other one will be rejected. This entire procedure is known as “speculative execution”.
Here, WAL stands for “Write Ahead Log (WAL)”, which is a file located in every Region Server across the distributed environment. It is mostly used to recover data sets in case of mishaps.
FSCK command is your to-go option to do file system check in HDFS. This command is extensively used to block locations or names or check overall health of any files.
Follow
hdfs fsck /dir/hadoop-test -files -blocks –locations
A block divides the data, physically without taking into account the logical equations. This signifies you can posses a record that originated in one block and stretches over to another. On the other hand, InputSplit includes the logical boundaries of records, which are crucial too.
The article has been sourced from – www.besthadooptraining.in/blog/top-100-hadoop-interview-questions
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Big data is expanding, and by next year almost a majority of businesses will be attracted towards the brighter prospect of this cutting edge technology. Even this year saw an enormous increase in volume, variety, velocity of data, which assures that the next year will witness more data, more numbers.
Data science pundits have predicted some of the leading trends that would be in the forefront in the big data revolution 2018. Come, let’s take a look:
In marketing, the analysis of data is a highly established one but the marketers nowadays have a massive amount of public and proprietary data about the preferences, usage, and behavior of a customer. The term ‘big data’ points out to this data explosion and the capability to use the data insights to make informed decisions. Understanding the potential of big data presents various technical challenges but it also needs executive talent devoted to applying the solutions of big data. Today, the marketers are widely embracing big data and are confident in their use of analytics tools and techniques. Let us learn about the ways in which Big data and analytics can improve the marketing efforts of various businesses around the around.
Previously, marketers had to frequently make guesses as to which sector of population comes under their ideal market segment but this is no longer the scenario today. The companies can exactly see who is buying and even extract more details about them with the help of big data. The other details include which buttons they generally click while on a website, which websites they visit frequently, and which social media channels they utilize.
Many retailers have introduced loyalty card systems that track the purchases of a customer, but these systems can also track which promotions and incentives are most effective in encouraging a group of customers or a single customer to make another purchase.
Because big data allows companies to optimize and monitor their marketing campaigns for performance, this implies they can allocate their budget for marketing for the highest return-on-investment (ROI).
Marketers can personalize their offers to customers in real time with the combination of big data and machine learning algorithms. Think about the Amazon’s “customers also bought” section or the recommended list of TV shows and movies from Netflix. The organizations can personalize what promotions and products a particular customer views, even down to sending personalized offers and coupons to the mobile phone of a customer when he walks into a physical location. The role of Personalized Merchandising in the ecommerce industry will continue to increase in the years to come.
Companies can conduct quantitative and qualitative market research much more inexpensively and quickly than ever before. The tools for online survey mean that customer feedback and focus groups are inexpensive and easy to implement, and data analytics make the results easier to take action.
For the past several years, sales teams, in order to rate their hottest leads, have made use of lead scoring. But, with the help of predictive analytics, a model can be generated and it can successfully predict sales and buyer behavior.
Previously, the return-on-investment for a blog post used to be highly difficult to measure. But, with the help of big data and analytics, the marketers can effortlessly analyze which pieces of content are highly effective at moving leads via a sales and marketing funnel. Even a small firm can afford to use tools for implementing content scoring which can highlight the content pieces that are highly responsible for closing sales.
Data can provide more information about your customers which includes who they are, what they want, where they are, how often they purchase on your site, and how, when they prefer to be contacted, and various other major factors. The organizations can also examine how users interact not only with their website, but also their physical store to enhance the experience of the user.
New tools for social monitoring have made it easy to gather and examine data about the competitors and their efforts regarding marketing as well. The organizations that can utilize this data will have a distinct competitive advantage.
With the help of big data, organizations can monitor their brand mentions very easily across different social channels and websites to locate unfiltered testimonials, reviews, and opinions about their company and products. The savviest can also utilize social media to offer service to the customers and create a trustworthy brand presence.
It is quite difficult to track direct ROI and impact with traditional advertising. But, big data can help organizations to make optimal marketing buys across various channels and to optimize their marketing efforts continuously through analysis, measurement, and testing.
At this point, talent and leadership are the major things that big data needs. In most of the companies, the marketing teams don’t have the right talent in place to leverage analytics and data. Apart from people who possess analytical skills to understand the capability of big data and where to use it, companies require data scientists who can extract meaningful insights from data and the technologists who can develop include new technologies. Due to this, there is a high demand for experienced analytics talent today.
In spite of all the promise, there exist certain limits to the usefulness of big data analytics in its present state. Among them, the major one is the major one is the analytics tools’ and techniques’ complex “black box” nature which makes it hard to trust and interpret the output of the approaches of big data and to assure others of the accuracy and value of the insights generated by the tools. The difficulty of gathering and understanding data also limits the capability of marketing companies to more fully leverage big data. Beyond this, the marketers are identifying many hurdles to expanding their utilization of big data tools and they include lack of sufficient technology investment, the inability of senior team members to leverage big data tools for decision-making, and the lack of credible tools for measuring effectiveness.
Cloud computing is also playing a major role in marketing with the Cloud Marketing process. Cloud Marketing is a process that outlines the efforts of a company to market their services and goods online via integrated digital experiences. Once the data analytics tools become available and accessible to even the smallest businesses, there will be a much higher impact of big data on the marketing sector as there will be much broader utilization of data analytics. This can only be a boon as organizations enhance their marketing and reach their customers in innovative and new ways.
This article was produced by Savaram Ravindra, a content contributor at Mindmajix and not by the editorial team of DexLab Analytics, a leading Hadoop training institute in Gurgaon.
Author’s Bio: Savaram Ravindra was born and raised in Hyderabad, popularly known as the ‘City of Pearls’. He is presently working at Mindmajix.com. His previous professional experience includes Programmer Analyst at Cognizant Technology Solutions. He holds a Masters degree in Nanotechnology from VIT University. He can be contacted at savaramravindra4@gmail.com. Connect with him also on LinkedIn and Twitter.
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Big data and business analytics are like two sides of the same coin. Here, though the coin represents digital transformation – but reports from consulting and services firm HCL Technologies are pointing that many companies are not being able to harness these new-age technologies to their fullest capacities resulting in a loss of digital transformation efforts.
When asked Anand Birje, the corporate vice president and head of HCL’s digital and analytics domain, he has this to say, “Over the past four or five years, enterprises were pushed hard to do anything in the field of analytics, big data and digital transformation. They were being pushed because there was this fear about what their competitors might be doing, so there was this feeling that they had to do something digital.”
Continue reading “For Long-term Digital Transformation Plan, Big Data is the Key”
According to a market research report, Global Hadoop market – industry analysis, share, size, growth, trends and forecast, which was once estimated at a value worth USD 1.5 billion in 2012, is now expected to hit $13.95 Billion mark this year, 2017 with a CAGR of 54.9%.
The advent of Hadoop platform stemmed out from the growing urge to manage problems that resulted owing to a lot of data – mostly a concoction of structured and unstructured data – that failed to fit properly in the traditional data storage and management systems, like tables. The play of analytics got intense, more complicated – both computationally and logically – hence the need for Hadoop is more than ever. This is similar to what Google was doing while it was on an endeavor to examine its user behaviors and index web pages, with a view to enhance its own performance algorithms.
Continue reading “Here’s ALL About Global Hadoop Market and Investment Report 2017”
Keen to have a sweeping view of data science and machine learning as a whole?
Want to crack who is playing tricks with data and what’s happening in and around the budding field of machine learning across industries?
Looking for ways to know how aspiring, young data scientists are breaking into the IT field to invent something new each day?
Hold your breath, tight. The below report showcases few of our intrinsic findings – which we derived from Kaggle’s industry-wide survey. Also, interactive visualizations are on the offer.
A lot of ways are there to nab who’s working with data, but in here we will fix our gaze on the demographic statistics and the background of people who are working in data science.
To kick start our discussion, according to the Kaggle survey, the average age of respondents was 30 years old subject to some variation. The respondents from India were on an average 9 years younger than those from Australia.
Anyone who uses code for data analysis is termed as a data scientist. But how true is this? In the vast realm of data science, there are a series of job titles that can be pegged. For instance, in Iran and Malaysia, the job title of data scientist is not so popular, they like to call data scientists by the name Scientist or Researcher. So, keep a note of it.
While “compensation and benefits” ranked a little lower than “opportunities for professional developments”, the best part remains it can still be considered a reasonable compensation.
Check out how much a standard machine learning engineer brings home to in the US
So, what’s going on in your mind? Should you get your hands on the next formal degree? Normally, most of the data scientists have obtained a full-time master’s degree, even if they haven’t they are at least data analytics’ certified. But professionals who come under a higher salary slab are more likely to possess a doctoral degree.
Largely, logistic regression is used in all the work areas except the domain of Military and Security, because in here Neural Networks are being implemented extensively.
Python was once the most used data analytics tool, but now it is replaced by R.
The original article can be viewed in Kaggle.
Kaggle is an iconic platform for data scientists, allowing ample scope to connect, understand, discover and explore data. For years, Kaggle has been a diverse platform to drag in hundreds of data scientists and machine learning enthusiasts, and is still in the game.
For excellent data science certification in Gurgaon, look no further than DexLab Analytics. Opt for their intensive data science and machine learning certification and unlock a string of impressive career milestones.
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A constructive mock interview and resume building session is a game-changer. Imbibing in-demand analytic skills is tough, but gearing up to crack high-flying job interviews is tougher. And DexLab Analytics addressed that point by curating an intensive resume building workshop on 20th October 2017. The session was headed by Mr. Tanmoy Ganguli, Program Director, DexLab Analytics at the Gurgaon centre in three time slots: 2-4 PM, 4-6 PM, 6-8 PM.
Mock interviews prepare you for the real interview challenge. They enable the candidates to gain some notion about what sort of things they are going to experience during real interviews, while helping them deal with hard times. Often, these kinds of preparatory interview workshops are organized by data science training institutes in Gurgaon that seek ways to train their students to explore the wide vistas of job opportunities across various industry domains. DexLab Analytics is one such pioneering institute that takes the initiative to cater for the needs of its aspiring students, and these kinds of resume building sessions work wonders.
Over a period of time, DexLab Analytics has garnered a lot of good reputation based on the level of training they provide. The trainers working here are industry experts possessing all the needful knowledge regarding this particular field of study, hence learning from them would be fun. Their intensive data analyst courses and workshops are prepared in tune with the latest industry trends and development taking place, hence are high-on-value.
The best part of the story here is that the intensive resume building workshop was conducted by none other than our very own honorable program director, Mr. Tanmoy Ganguli. He has been in this industry for years, and possesses incredible expertise in the domains of SAS, Credit Risk Modelling and Regression Models. Being a key influencer, the sessions presided by him are a sure not-to-miss things for students.
Resume building and mock sessions drastically reduce the anxiety levels. They equip the candidate with the needful interview questions that might be asked in the actual one. The interviewer and the trainer who conducts such events feed the candidate with needful responses that precisely tackles a candidate’s potentials and shortcomings. No one is perfect; hence the mock interview sessions help the candidates in becoming a better person, both knowledge-wise and skill-wise.
So, if you are one of them who want to pull up your career dreams of bagging the highest-paying job in the world of analytics, DexLab Analytics would be the right place for you. Right from imparting crucial skill-based knowledge to providing needful advice regarding how to crack a job interview, the event organized by DexLab Analytics is the best way to gather extensive knowledge to nail the best job in town!
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Big data is a very powerful term nowadays. It seems to be a large amount of data. Big data means large amount of structured, unstructured, semi-structured data. We get data continuously from various data sources.
Just have a look on how we get data.
Nowadays we are living in a techno era in which we need to use technology so that’s why we are generating data. If you are doing any type of activity like – driving car, having some shakes in CCD, surfing internet, playing games, emails, social media, electronic media, everything plays a crucial role to develop big data. Continue reading “Revising the Basics of Big Data Hadoop”