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What Job Opportunities Are Available For Apache Hadoop Experts?

Posted on by Imarticus Learning

Everyone talks about Apache Hadoop but no one talks about the scope of employment in the field. As you must have already learned, Hadoop as an application software aids a variety of processes across business sectors in the world. Its development tools are primarily used to store and process Big Data.

In that regard, there are several different types of job roles you can take up. As an Apache Hadoop expert, you can either join a software company that develops the tools or an application company that takes advantage of those tools.

The following are some of the most common types of jobs you can do once you learn Hadoop and master it.

Job Opportunities for Apache Hadoop Experts

A quick look at some of the career paths available in the field.

Apache Hadoop Developer

This is the most common job you can get once you finish your Hadoop training and gain some experience. Your role will basically entail the building of data storage and processing infrastructures. Since different companies follow different processes and have different products and services to sell, building a unique one for each of them is important.

For example, a Hadoop developer working at a bank will need to focus on extra security. Hadoop Spark and Hive are some of the technologies you will need to be skilled at.

Data Analyst

If you are going to deal with Big Data, you might as well be an analyst. Don’t see this role as an entry-level job. Data analysts with Hadoop training are in high demand these days as they can oversee the architecture and its output.

You have to be proficient in SQL. Huge to be able to work on SQL engines like Hive. If you are still studying, make sure you carve out a specialization as part of your Hadoop training.

Tester

Most software application jobs have this role of a tester who detects bugs in systems and helps developers with solutions. Testers are important in a Hadoop environment too as they can help detect issues in a newly built infrastructure. Some companies even have an entire team of expert testers who provide continuous suggestions and testing results to better an ongoing infrastructure build.

The good part about being a Hadoop System Tester is that you can switch to this role from any field. Are you a software tester at TCS? Learn Hadoop, get trained, and become a Hadoop tester.

Data Modeller

In this job, you will be a supporting member of the Hadoop development team in a company. A modeler’s responsibilities include system architecture and network designing so that a company’s processes align with the newly created infrastructure for Big Data.

Years of experience in this field can open gates for employment in large corporations. Here you can participate in decision-making rounds.

Senior IT Professionals

The Hadoop environment doesn’t just need people with technical Hadoop skills. It also needs innovators and world analyzers who can provide wise suggestions in the entire process involving a Hadoop setup. It could be in the development phase, processing phase, or output phase.

These professionals have decades of experience in research and development as well as a fair understanding of Apache Hadoop. If you are a senior IT professional who realizes the significance and relevance of the field in the modern world, you can learn Hadoop and slightly shift your career path.

Apart from these five job opportunities, there are several roles that you can take up if you have some qualifications in the field. So, start your Hadoop training and get a job today!

Boost your Career and Secure a Job During the Pandemic by Availing our Great Fightback Offers today!

Posted on by Imarticus Learning

Imarticus Learning introduces the ‘Great Fight Back Offer’ where you can sign up for selected courses and avail of good discounts for a limited period from 26th April-30th April 2021. Sign up today and avail of up to 30% Flat Off on placement-oriented, future-skill professional training programs.

 Covid-19 has changed the ways we lived. We are living amidst new normalcy, and we hope it fades out soon. Before we can unmask and return to normal, safety and health has to be a priority for all. The latter priorities being livelihood!

Yes, patterns of the industries have shifted, and employment and recruitment processes have changed. The parameters and eligibility criteria are moving to different alignment rapidly!

Does it put a question in the mind of what to do to advance and keep up the pace?

Well, the answer is simple to update and upgrade your skills. Those looking for an advance in their respective careers can look for new-age career programs. While those falling short of opportunities can consider shifting their career into a different industry.

Learn Data AnalyticsA practical approach and expert advice can work wonders for any task as it lays down a strategic path to be followed.

Upgrade for New Age Career with Imarticus

Imarticus Learning has transformed many careers by enabling aspirants to acquire in-demand skills using an ‘Industry-First approach.’ The idea is to prepare a talent pipeline for the jobs of tomorrow!

With the growing commercial and technological advancements in the global markets, Finance, Analytics, Technology, and Marketing are the industries that tend to secure the top-most position in terms of job opportunities.

These industries are rapidly becoming one of the most lucrative careers in the business world. Finance and Analytics Courses play a significant role in data evaluation for businesses to streamline decision-making processes. Technology simply helps to implement the strategy coming in through management.

‘The Great Fight Back Offer’

Why let Covid ruin your career when you can upgrade and become a skilled new-age professional! With the online learning mode of Imarticus, you get the facility to learn at home, thus, remaining safe and ensure productivity in the spare time.

Register today and empower your career prospects most affordably!

5 Reasons to Learn Hadoop!

Posted on by Imarticus Learning

Big Data Analytics is ruling the world. Organizations across the world have realized the potential of Big data analytics to push their business decisions to be more informed and data-driven. Data analytics has become imperative in terms of uncovering the hidden patterns, deriving correlations, understanding business information, and learning the market trends.

Hadoop is open-source software that facilitates the storage and processing of a large amount of data. It is scalable and reliable and can be used on distributed computing that does not share any common memory or discs. So, is it good to learn Hadoop? Let us look at the top five reasons to learn Hadoop.

  1. Bright Career Prospects

More than 90% of the companies have invested in big data and they are in the hunt for talents to manage the data for them. This unveils a big career path ahead for big data and Hadoop trained professionals. If you are looking for a lucrative career in big data, you should get Hadoop training to brighten up your future employment prospects.

  1. Many Choice of Profiles

There are many different profiles related to Hadoop depending upon your proficiency, learning skills, and experience. You will be amazed at the designations available – have a look at some of them:

  • Hadoop Admin
  • Hadoop Developer,
  • Data Engineer
  • Data Analyst
  • Data Scientist
  • Big Data Architect
  • Software Engineer
  • Senior Software Engineer
  1. Constant Increase in the Demand

Big data and its applications are ever-increasing, and this works in favor of Hadoop professionals too. Big data has now become the basic requirement for effective business strategy formulation and hence, the companies are on a constant lookout for talents who can collect, process, and interpret data. The demand is only going to increase in the coming years. Getting Hadoop training will help you to be future-ready.

  1. Accelerated Career Growth

As mentioned earlier, there are many different profiles associated with Hadoop. Depending upon your skills, experience level, and your willingness to learn, you can easily move up your career ladder and secure a more challenging and rewarding position.

The fact that many global market leaders are big recruiters of data professionals the scope of data science-related jobs is as vast as the sea. Also, unlike many other jobs where the supply of talents is far exceeding the demand, there is a serious shortage of skillful professionals in data analytics. This increases the chances of employability by many folds.

  1. It Promises Good Pay

The fact that Hadoop is the leader in big data job postings gives you a taste of the situation. There is a serious lacuna in terms of good talents, and companies are ready to pay fat salaries for the right talent. All you need to do is to sharpen your skills and keep yourself updated all the time.

Conclusion

You now know the top reasons to learn Hadoop. Ease of learning and high demand makes it a hot pick among aspiring data professionals. Hadoop skills will earn you brownie points and help you get your dream job.

How Python Is Used in Hadoop?

Posted on by Imarticus Learning

Perks of using Python

A lot of unstructured data is produced each day, the companies and firms use big data and its applications to extract meaningful information from the raw data. A distributed file system is used for parallel processing of data and to enhance fault tolerance. The Hadoop ecosystem offers a Hadoop distributed file system (HDFS) which is widely used by companies and firms.

Hadoop is a database framework that allows users to process big data. While the Hadoop framework is originally written in java then why companies are willing to hire candidates fluent in python? Let us find out the importance of python in Hadoop in this article.

It is possible to write the codes for the Hadoop framework in python and it is compatible with the Hadoop distributed file system. All the analysis applications can be performed with the Hadoop framework coded in python. Python is easy to learn and use and yet is powerful in performing big data applications.

It has a big library of in-built functions which can be used as and when required. Python is a predictive language that has less syntax and semantic constraints as compared to other languages.

A lot less time is wasted in coding in Python due to its predictive nature and that’s why companies and firms are looking for candidates fluent in python, individuals who can solve big data problems with the help of python in a more efficient way. Python has a lot of remarkable applications such as Instagram, Google, Quora, etc. Facebook uses python with HDFS for data extraction and its parallel processing.

The libraries of python fit right in the slot for big data analytics. It makes coding convenient and fast. Users choose among various python frameworks available in the market for working with Hadoop such as Hadoop streaming API, Dumbo. Pydoop, etc.

These frameworks help to enable Hadoop with the help of python and using its services. Real-time computation can be done through python. Python has lists, tuples, dictionaries, etc. as data structures. These data structures can be used for high-end evaluation of big data.

The codes written in python are scalable and scalability is one of the main features of big data. Python is used a lot nowadays for application and web development. Python has an in-built mechanism and algorithm to deal with unstructured data and for doing the processing of that unstructured data. For example, NumPy is an in-built function in the python library that supports complex operations and scientific computing.

There are many other functions that support data analytics. When used in Hadoop, python increases efficiency and fault tolerance. Python boasts a strong user base throughout the world, there is an active community of people working on python which will help you by giving their approach to any particular problem.

A lot of research material and learning guide can be found on python as it is a globally used language. Big data and its applications are also being used by firms to enhance their business and predict trends and solutions. For this Hadoop training is being used and if we are getting such scalable language with an advanced library and is also easy to use, we are bound to use it!

Conclusion

So, each day new languages are coming but that doesn’t mean you have to learn them all. If you are working on the Hadoop platform then python is by far the most suited language for it. You can code much faster in python as compared to other programming languages and also with the chance of getting fewer errors and warnings due to its interactive and predictive nature. Hadoop and python have shown a lot of compatibility in big data use cases across the globe by firms and companies. This article highlights the importance of python in Hadoop.

Apache Spark or Hadoop: Which one is Better?

Posted on by Imarticus Learning

With the advent of the internet, data and its distribution have been in the prime focus. With millions of interconnected devices capable of distributing data anywhere in the world at any time, data and its usage is likely to grow in geometric progression. Such large sets of data, big data, has to be analyzed to learn about patterns and trends associated with it.

Data analysis has taken the business world to the next level and now the focus is on creating tools that could process the data faster and better. Apache Spark and Hadoop are two technological frameworks introduced to the data world for better data analysis. Though Spark and Hadoop share some similarities, they have unique characteristics that make them suitable for a certain kind of analysis. When you learn data analytics, you will learn about these two technologies.

Hadoop

Apache Hadoop is a Java-based framework. It is an open-source framework that allows us to store and analyze big data with simple programming. It can be used for data analysis across many clusters of systems and the result is generated by a combined effort of several modules like Hadoop Common, Hadoop Distributed File System (HDFS), Hadoop YARN and Hadoop MapReduce.

Hadoop: Advantages and Disadvantages

Advantages Disadvantages
Stores data on distributed file and hence, data processing is faster and hassle-free It is more suitable for bigger files. It cannot support small files effectively.
It is flexible and allows data collection from different sources such as e-mails and social media. It features a chain form of data processing. So it is not a choice for machine learning or other solutions based on Iterative learning.
It is highly scalable The security model is low/disabled. Data can be easily accessed/stolen
It does not need any specialized system to work, so it is inexpensive It is based on the highly exploited language – Java; so easier for hackers to access sensitive data.
It replicates every block and stores it and hence, data can be recovered easily. It supports only batch processing.

Spark

This framework is based on distributed data. Its major features include in-memory computation and cluster computing. Thus, the collection of data is better and faster. Spark is capable of hybrid processing, which is a combination of various methods of data processing.

Spark: Advantages and Disadvantages

Advantages Disadvantages
Dynamic data processing capable of managing parallel apps It does not have a file management system.
It has many built-in libraries for graph analytics and machine learning algorithms. Very high memory consumption, so it is expensive

 
It is capable of performing advanced analytics that supports ‘MAP’ and ‘Reduces’, graph algorithms, SQL queries, etc. It has less number of algorithms
Can be used to run ad-hoc queries and reused for batch-processing It requires manual optimization
Enables real-time data processing It supports only time-based window criteria, not record based window criteria
Supports many languages like Python, Java, and Scala Not capable of handling data backpressure.

Spark vs Hadoop

Feature Spark Hadoop
Speed fast slow
Memory needs more memory needs less memory
Ease of use Has user-friendly APIs for languages like Python, Scala, Java, and Spark SQL Have to write a MapReduce program in Java
Graph Processing good Better than Spark
Data processing supports iterative, interactive, graph, stream and batch processing Batch processing only

Conclusion

Both Spark and Hadoop have their strength and weaknesses. Though appears to be similar, they are suitable for different functions. Choosing Spark or Hadoop Training depends on your requirement – if you are looking for a big data framework that has better compatibility, ease-of-use, and performance, go for Spark. In terms of security, architecture, and cost-effectiveness, Hadoop is better than Spark.

What Are The Tips To Prepare For a Hadoop Interview?

Posted on by Team Imarticus

The popularity of big data has been growing at an immense rate opening the doorway to a spectrum of jobs that require skilled professionals. Noteworthy among these is the job of a Hadoop developer; challenging, technical and well paid, Hadoop is known to be one of the best segmentation of big data and analysis and a developing platform for candidates interested in a career in data science.
Learn Hadoop to pursue a career as a Hadoop analyst, Hadoop developer, or a Hadoop Architect, Hadoop tester among other job roles on the Hadoop platform. If you are looking for a career in this domain, it is highly essential to understand that a Hadoop developer not just created codes in programming but is also expected to have an expertise of multitasking while as his job, which includes programming in Java, writing scripts, reviewing log files, scheduling jobs across clusters on Hadoop amongst others.
Basic skill set for a Hadoop interview
Hadoop works with a number of other software like Ambari, HBase, Hive, Pig and more, therefore, knowledge of technologies is essential. While it is important to also have an idea about other visualization and ETL tools, SQL, gateway and edge nodes, basic cloud computing, some of the must-have skills an interviewee needs to possess during Hadoop training include JAVA, Hadoop Framework, Pig, HDFS, MapReduce, and Floop.
Tips to prepare for a Hadoop interview
Cracking a successful Hadoop interview does not essentially mean having specified skillsets but also ensuring that all of the interviewee’s questions are addressed. While Hadoop in big data is a relatively new concept, here are a couple of tips to help you prepare better for an upcoming Hadoop interview.
Knowledge of Programming Languages
Java experience is as important as it can since Hadoop is a software-based on Java. If your career path monitors progress from C++ to Java, nothing like it. Knowledge of other programming languages like OOAD, JS, Node.js, and HDFS only add to your skillset and make your resume stand out from the rest of the candidates.
Big Data experience
If you have experience working with big data, a Hadoop interview would be fairly easy to crack, since Hadoop is mostly built for the working of big data.
Technical Expertise
To crack a Hadoop interview, you not just need hard skills for Hadoop but also various other technologies that include Flume, Sqoop, Hive, Pig and more. These technologies often seem smaller, however, they make data processing easier on Hadoop.
Interview domains that are essential to prepare for
Along with a good grasp of relevant skill sets, listed below a couple of interview domains every interviewee needs to prepare for-
Practical experience
Theoretical knowledge is important, however, most interviewees are tested on practical knowledge. Expertise in the practical field subjects candidates to various degrees of exposure otherwise impossible by merely learning theories.
Communication Skills
Hadoop experts have to communicate with people in various other job roles, that often include engineers, analysts or even architects. In cases like these, good communication goes a long way.
Knowledge of domain
The interviewee is expected to know the A-Z of Hadoop along with its basic functionalities. You may be expected to back your interview answers with sufficient theoretical or analytical examples.
Conclusion
Big data is growing at an immense rate and more professionals are getting enthusiastic to work in the field. An extensive Hadoop training can go a long way in helping a big data enthusiast to master the best skills in the market and make it big as a professional.
For more such information, feel free to visit – Imarticus Learning

Future of Big Data Hadoop Developer in India

Posted on by Imarticus Learning

In this era of electronic and digital devices, most people are using Big Data, ML, AI and such without really understanding what goes on to provide those services. Data is at the very center of any application and the sheer volumes of data generated, the variety of sources and formats, the need to manage, clean, prepare and draw inferences for business purposes and making decisions is being used extremely widely. And this spawning of data, means the projects involve Big Data and that technology has to evolve and changes to manage it. This also indirectly implies the need for Hadoop developers. The relationships are symbiotic and spur growth in each other’s needs.

Why Choose Big Data Hadoop As a Career

• Since data is an asset people trained on handling the large amounts of data performing analytics on it and providing the right gainful assets for business decisions are also fast being considered invaluable assets.
• Those employees who do not re-skill to include managing Big Data face the risks of getting laid off. For example, TCS, Infosys, and many other data giants laid off nearly 56,000 people in just one year.
• 77% of the companies and verticals across industries are adapting to use Big Data. Thus many are recruiting data analysts and scientists. Even the non-IT sector!
• The payouts are second to none in the category and a large number of aspirants are taking up formal Hadoop careers, both newbies and those changing careers mid-way.
• Data is growing and will continue to be used even in the smallest of devices and applications creating a demand of personnel to handle Big Data.

The Hadoop Career Choice

Pros:
• Big data applications and demand for trained personnel shows tremendous growth.
• Job scope is unending since data continues to grow exponentially and is used by most devices today.
• Among the best technology for managing Big Data sets Hadoop scores as the most popular suite.
• The salaries and payouts globally are better than for other jobs.
• Most verticals and industries, a whopping 77%, are switching tracks to use Big Data.
• Hadoop is excellent at handling petabytes of Big Data.
Cons:
• Your skills need to be of practical nature and constantly updated to keep pace with evolving technology.
• You need a combination of skills that may require formal training and is hard to assimilate on your own before you land the job.

How to Land that Dream job

Today it would be exceptional if a company does not use Hadoop and data analytics in one form or the other. Among the ones that you can easily recollect are New York Times, Amazon, Facebook, eBay, Google, IBM, LinkedIn, Spotify, Yahoo!, Twitter and many more. Big Data, Data Analytics, and Deep Learning are widely applied to build neural networks in almost all data-intensive industries. However, not all are blessed with being able to learn, update knowledge and be practically adept with the Hadoop platform which requires a comprehensive ML knowledge, AI deep learning, data handling, statistical modeling and visualization techniques among other skills.
One can do separate modules or certificate Big-Data Hadoop training courses with Imarticus Learning who provide such learning as short-term courses, MOOCs, online classrooms, regular classrooms, and even one-on-one courses. Choices are aplenty with materials, tutorials and options for training being readily available thanks to high-speed data and visualization made possible by the internet.
Doing a formal Hadoop training course with certification from a reputed institute like Imarticus Learning helps because: 
• Their certifications are widely recognized and accepted by employers.
• They provide comprehensive learning experiences including the latest best practices, an updated curriculum, and the latest training platforms.
• Employers use the credential to measure your practical skills attained and assess you are job-prepared.
• It adds to your resume and opens the doors to the new career.
• Knowledge in Big Data is best imbibed through hands-on practice in real-world situations and rote knowledge gained of concepts may not be entirely useful.
The best courses for Big data Hadoop and Advanced Analytics are available at the IIMs at Lucknow, Calcutta, and Bangalore at the IITs of Delhi and Bombay. This is an apt course for people with lower experience levels since their curriculum covers a gamut of relevant topics in-depth with sufficient time to enable you to assimilate the concepts.
The Big data training courses run by software training institutes like Imarticus are also excellent programs which cost more but focus on training you, with the latest software and inculcating practical expertise. Face-to-face lab sessions, mandatory project work, use of role-plays, interactive tutoring and access to the best resources are also very advantageous to you when making the switch.
Job Scope and Salary Offered:
Persons with up to 4 years experience can expect salaries in the range of 10-12 lakhs pa at the MNCs according to the Analytics India Magazine. Yes, the demand for jobs in this sector will never die down and is presently facing an acute shortage.
Hadoop Course Learning:
You can use online resources and do it yourself using top10online courses.com. However, formal training has many advantages and is recommended. Join the Hadoop course at a reputed institute like Imarticus Learning.
Hadoop has a vast array of subsystems which are hard to learn for the beginner without formal training. The course helps you assimilate the ecosystem and apply these systems to solving real-world industry-related problems in real-time through assignments, quizzes, practical classes and of course do some small projects to show off your newly acquired skills. The best part is that you have certified trainers leading convenient modes and batches to help you along even if you are already working.
The steps that follow are the Hadoop progressive tutorial in brief.
• Hadoop for desktop installation using the Ambari UI and HortonWorks.
• Choose a cluster to manage with MapReduce and HDFS.
• Use Spark, Pig etc to write simple data analysis programs.
• Work on querying your database with programs like Hive, Sqoop, Presto, MySQL, Cassandra, HBase, MongoDB, and Phoenix.
• Work the ecosystem of Hadoop for designing applications that are industry-relevant.
• Use Hue, Mesos, Oozie, YARN, Zookeeper, and Zeppelin to manage your cluster.
• Practice data streaming with real-time applications in Storm, Kafka, Spark, Flume, and Flink.
• Start building your project portfolio and get on GitHub.
Conclusion:
In parting, India and the bigger cities like Bangalore, Hyderabad, and Mumbai are seeing massive growth in the need for Hadoop developers. You will also benefit from a Hadoop training course in Data Analytics and it is worth it when your certification helps you land the dream career you want. So don’t wait. Take that leap into Hadoop today!