DP 203: Data Engineering on Microsoft Azure
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Hadoop can be contagious. It’s implementation in one organization can lead to another one elsewhere. Thanks to this piece of technology being so robust and cost-effective, handling humongous data seems much easier now. The ability to include HIVE in an EMR workflow is yet another awesome point. It’s incredibly easy to boot up a cluster, install HIVE, and be doing simple SQL analytics in no time. Let’s take a look at why Hadoop can be so incredible.
As it is a known fact that only 20% of data in organizations is structured, and the rest is all unstructured, it is very crucial to manage unstructured data which goes unattended. Hadoop manages different types of Big Data, whether structured or unstructured, encoded or formatted, or any other type of data and makes it useful for decision making process. Moreover, Hadoop is simple, relevant and schema-less! Though Hadoop generally supports Java Programming, any programming language can be used in Hadoop with the help of the MapReduce technique. Though Hadoop works best on Windows and Linux, it can also work on other operating systems like BSD and OS X.
Hadoop is a scalable platform, in the sense that new nodes can be easily added in the system as and when required without altering the data formats, how data is loaded, how programs are written, or even without modifying the existing applications. Hadoop is an open source platform and runs on industry-standard hardware. Moreover, Hadoop is also fault tolerant – this means, even if a node gets lost or goes out of service, the system automatically reallocates work to another location of the data and continues processing as if nothing had happened!
Hadoop has revolutionized the processing and analysis of big data world across. Till now, organizations were worrying about how to manage the non-stop data overflowing in their systems. Hadoop is more like a “Dam”, which is harnessing the flow of unlimited amount of data and generating a lot of power in the form of relevant information. Hadoop has changed the economics of storing and evaluating data entirely!
Hadoop has a very robust and a rich ecosystem that is well suited to meet the analytical needs of developers, web start-ups and other organizations. The Ecosystem consists of various related projects such as MapReduce, Hive, HBase, Zookeeper, HCatalog, Apache Pig, which make it very competent to deliver a broad spectrum of services.
Did you ever wonder how to stream information into a cluster and analyze it in real time? Hadoop has the answer for it. Yes, the competencies are getting more and more real-time. It also provides a standard approach to a wide set of APIs for big data analytics comprising MapReduce, query languages and database access, and so on.
Loaded with such great features, the icing on the cake is that Hadoop generates cost benefits by bringing massively parallel computing to commodity servers, resulting in a substantial reduction in the cost per terabyte of storage, which in turn makes it reasonable to model all your data. The basic idea behind this is to perform cost-effective data analysis present across world wide web!
With reinforcing its capabilities, Hadoop is leading to phenomenal technical advancements. For instance, HBase will soon become a vital Platform for Blob Stores (Binary Large Objects) and for Lightweight OLTP (Online Transaction Processing). It has also begun serving as a strong foundation for new-school graph and NoSQL databases, and better versions of relational databases.
Hadoop is getting cloudier! In fact, it is synchronizing with cloud computing in several organizations to manage Big Data. Hadoop will become one of the most required apps for cloud computing. This is evident from the number of clusters offered by cloud vendors in various businesses. Thus, it will reside in the cloud soon!
Now you know why Hadoop is gaining so much popularity!
The importance of Hadoop is evident from the fact that there are many global MNCs that are using Hadoop and consider it as an integral part of their functioning. It is a misconception that social media companies alone use it. In fact, many other industries now use Hadoop to manage BIG DATA!
It was Yahoo!Inc. that developed the World’s biggest application of Hadoop on February 19, 2008. In fact, if you’ve heard of ‘The Yahoo! Search Webmap’, it is a Hadoop application that runs on over 10,000 core Linux cluster and generates data that is now extensively used in each query of Yahoo! Web search.
Facebook, which has over 1.3 billion active users and it is Hadoop that brings respite to Facebook in storing and managing data of such magnitude. Hadoop helps Facebook in keeping track of all the profiles stored in it, along with the related data such as posts, comments, images, videos, and so on.
Linkedin manages over 1 billion personalized recommendations every week. All thanks to Hadoop and its MapReduce and HDFS features!
Hadoop is at its best when it comes to analyzing Big Data. This is why companies like Rackspace use it.
It plays an equally competent role in analyzing huge volumes of data generated by scientifically driven companies like Spadac.com.
All in all, this is a great framework for advertising companies as well. It keeps a good track of the millions of clicks on the ads and how the users are responding to the ads posted by the big Ad agencies!
Got a question for us? Mention them in the comments section and we will get back to you.
|Big Data Hadoop Certification Training Course|
Class Starts on 8th April,2023
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|Big Data Hadoop Certification Training Course|
Class Starts on 3rd June,2023
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I have 6+ years experience as a core C++ developer. I have learned Java, DBMS, DS, Algorithms, etc. of my own interest. I don’t have any “project experience” in these since I cannot control what my project leads decide for the project.
This creates a significant problem in job change since everyone asks for experience, which I cannot have unless I get to work on them! I want to explore other areas besides C++, which I cannot currently do, because of this problem.
Moreover, I cannot even join as a fresher because obviously one cannot just knock off 6+ years from one’s resume, without making the recruiter suspicious. Even explicitly telling them to disregard my work experience in C++ and hire me as a Java fresher doesn’t impress them.
Will same story repeat if I take this Hadoop training? Obviously, this course is not counted as “work experience”, so will employers ask me to come with Hadoop experience (or at least Java and DBMS experience) before I get these Hadoop jobs?
Hi MaskedMan, With Hadoop it will not be the same, as Hadoop is a new technology. It is the best opportunity for you to learn Hadoop and move into the Big Data space. These days, recruiters are looking for professionals with IT experience with Hadoop know-how, which you will get from Edureka. I advise you not to delay any more and quickly learn the same. During the training at edureka, you will not only learn the theoretical concepts but also do a lot of practical and projects. This will add much more value to your resume. You can call us at US: 1800 275 9730 (Toll Free) or India: +91 88808 62004 to discuss in detail. You can find more course information at http://www.edureka.in/hadoop
There are some fascinating points in time in this write-up but I do not know if I see all of them center to heart. There is some validity but I will take hold opinion until I look into it further. Excellent post , thanks and we want additional!