About The Big Data Hadoop Course
Because of the creation of different technology, devices, and communication means for social networks, the quantity of data created by humanity keeps growing each year. The volume of data produced by us since the beginning of 2003 is 5 billion gigabytes. Should you stack up the information using disks it might fill a whole football field. This data is then produced in 2 days, which has moved up to ten minutes in 2013. These rates are still growing enormously. Though all of this information created is significant and could be helpful when processed, but neglected.
Big data means an innovative technology to store a big amount of data; it’s an assortment of large datasets that can’t be treated using traditional computing techniques. Big information is not just information; rather it is an entire subject that involves various tools, techniques, and frameworks.
Who are we? ProICT LLC, is a registered online training provider found and led by the group of IT working professionals and experts. Our trainers are not only highly experienced and knowledgeable but also current IT working Professionals leading IT companies in USA, UK, Canada and other countries. We are ready to share our knowledge and years of working experience with other professionals to assist and guide them get ahead in career.
What is Big Data Hadoop?
Hadoop is an open-source software framework to do the data storing and running applications on clusters of commodity hardware. It offers massive storage for all kinds of data, enormous processing power and the opportunity to handle virtually unlimited concurrent tasks or jobs. Because the web is increasing in size every moment from dozens to millions of pages, automation was needed. Web crawlers were created while many studies brought up matters of large-scale data storing. With search engines, start-ups coming up to play the lead role in data storing the need of such a technology became more and more evident. In The Year 2006, Cutting became a member of Yahoo and started with him the Nutch project in addition to ideas developed by Google’s early use of electronic distribution of data storage and processing. The Nutch project was divided – the remaining crawler portion continued to be as Nutch, and also the distributed computing and processing portion grew to become Hadoop (named after Cutting’s son’s toy elephant). In 2008, Yahoo released Hadoop being an open-source project. Today, Hadoop’s framework and ecosystem of technology are managed and maintained by the non-profit Apache Software Foundation (ASF), a worldwide community of software developers and contributors has come contributing to its growth.
Challenges in Big Data Hadoop:
Hadoop is not a factor. It’s a word we use to mean “that big data stuff” like Spark, MapReduce, Hive, HBase, and so forth. There are plenty of pieces.
Diverse Workloads: You don’t only potentially have to balance a Hive: Tez workload against a Spark workload, however, many workloads tend to be more constant and sustained than the others.
Partitioning: YARN is a cluster-wide form of the procedure scheduler and queuing system that you simply ignore within the operating system from the computer, phone, or tablet you are using at this time. You may well ask it to complete stuff. Also, it balances it from the other things it’s doing, and then distributes the job accordingly. Clearly, this is essential. There is, however, a pecking order — and what you frequently determine the number of sources you receive. Also, streaming works and batch jobs may require different amounts of service. You might have no choice but to deploy several Hadoop clusters, which you have to manage individually. Worse, what goes on when workloads are cyclical?
Priorities: Though your business might want to provision single,000-node Spark cluster, it does not mean you will need to provision 1,000 nodes. Is it possible to obtain the sources you’ll need?
Types of Big Data Hadoop
Who should enroll for this course?
There’s no strict prerequisite to beginning learning Hadoop. But you ought to have a minimum of fundamental understanding of Java and Linux. For those who have no knowledge of the identical don’t be concerned, the easiest way could be to spend a couple of hours on learning Java and Linux too. If you wish to write your personal MapReduce code, that can be done in almost any language (e.g. Perl, Python, Ruby, C, etc.) that supports studying from standard input and connecting standard output with Hadoop Streaming. Hadoop projects come with many different roles like Architect, Developer, Tester, Linux/Network/Hardware Administrator and most of which require explicit understanding of Java and a few don’t. Although Hadoop can operate on Home windows, it had been built initially on Linux and Linux may be the preferred way of both installing and managing Hadoop. Getting a good knowledge of making your way around inside a Linux covering may also help you tremendously in digesting Hadoop, especially about most of the HDFS command line parameters.
Learning Objectives: In this module, you will learn Apache Pig, types of use cases where we can use Pig, tight coupling between Pig and MapReduce, and Pig Latin scripting, Pig running modes, Pig UDF, Pig Streaming & Testing Pig Scripts. You will also be working on healthcare dataset.
Learning Objectives: In this module, you will understand advanced Apache Hive concepts such as UDF, Dynamic Partitioning, Hive indexes and views, and optimizations in Hive. You will also acquire in-depth knowledge of Apache HBase, HBase Architecture, HBase running modes and its components.
Learning Objectives: This module will cover advance Apache HBase concepts. We will see demos on HBase Bulk Loading & HBase Filters. You will also learn what Zookeeper is all about, how it helps in monitoring a cluster & why HBase uses Zookeeper.
Learning Objectives: In this module, you will learn what is Apache Spark, SparkContext & Spark Ecosystem. You will learn how to work in Resilient Distributed Datasets (RDD) in Apache Spark. You will be running application on Spark Cluster & comparing the performance of MapReduce and Spark.
Learning Objectives: In this module, you will understand how multiple Hadoop ecosystem components work together to solve Big Data problems. This module will also cover Flume & Sqoop demo, Apache Oozie Workflow Scheduler for Hadoop Jobs, and Hadoop Talend integration.
Hadoop is an Apache project (i.e. an open source software) to store & process Big Data. Hadoop stores Big Data in a distributed & fault tolerant manner over commodity hardware. Afterwards, Hadoop tools are used to perform parallel data processing over HDFS (Hadoop Distributed File System).
As organisations have realized the benefits of Big Data Analytics, so there is a huge demand for Big Data & Hadoop professionals. Companies are looking for Big data & Hadoop experts with the knowledge of Hadoop Ecosystem and best practices about HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop & Flume.
Edureka Hadoop Training is designed to make you a certified Big Data practitioner by providing you rich hands-on training on Hadoop Ecosystem. This Hadoop developer certification training is stepping stone to your Big Data journey and you will get the opportunity to work on various Big data projects.
Big Data is one of the accelerating and most promising fields, considering all the technologies available in the IT market today. In order to take benefit of these opportunities, you need a structured training with the latest curriculum as per current industry requirements and best practices.
Besides strong theoretical understanding, you need to work on various real world big data projects using different Big Data and Hadoop tools as a part of solution strategy.
Additionally, you need the guidance of a Hadoop expert who is currently working in the industry on real world Big Data projects and troubleshooting day to day challenges while implementing them.
There are no such prerequisites for Big Data & Hadoop Course. However, prior knowledge of Core Java and SQL will be helpful but is not mandatory. Further, to brush up your skills, Edureka offers a complimentary self-paced course on "Java essentials for Hadoop" when you enroll for the Big Data and Hadoop Course.
Edureka’s Big Data & Hadoop Training includes multiple real-time, industry-based projects, which will hone your skills as per current industry standards and prepare you for the upcoming Big Data roles & Hadoop jobs.
Industry: Stock Market
TickStocks, a small stock trading organization, wants to build a Stock Performance System. You have been tasked to create a solution to predict good and bad stocks based on their history. You also have to build a customized product to handle complex queries such as calculating the covariance between the stocks for each month.
MobiHeal is a mobile health organization that captures patient’s physical activities, by attaching various sensors on different body parts. These sensors measure the motion of diverse body parts like acceleration, the rate of turn, magnetic field orientation, etc. You have to build a system for effectively deriving information about the motion of different body parts like chest, ankle, etc.
Industry: Social Media
Socio-Impact is a social media marketing company which wants to expand its business. They want to find the websites which have a low rank web page. You have been tasked to find the low-rated links based on the user comments, likes etc.
A retail company wants to enhance their customer experience by analysing the customer reviews for different products. So that, they can inform the corresponding vendors and manufacturers about the product defects and shortcomings. You have been tasked to analyse the complaints filed under each product & the total number of complaints filed based on the geography, type of product, etc. You also have to figure out the complaints which have no timely response.
A new company in the travel domain wants to start their business efficiently, i.e. high profit for low TCO. They want to analyse & find the most frequent & popular tourism destinations for their business. You have been tasked to analyse top tourism destinations that people frequently travel & top locations from where most of the tourism trips start. They also want you to analyze & find the destinations with costly tourism packages.
A new airline company wants to start their business efficiently. They are trying to figure out the possible market and their competitors. You have been tasked to analyse & find the most active airports with maximum number of flyers. You also have to analyse the most popular sources & destinations, with the airline companies operating between them.
Industry: Banking and Finance
A finance company wants to evaluate their users, on the basis of loans they have taken. They have hired you to find the number of cases per location and categorize the count with respect to the reason for taking a loan. Next, they have also tasked you to display their average risk score.
Industry: Media & Entertainment
A new company in Media and Entertainment domain wants to outsource movie ratings & reviews. They want to know the frequent users who is giving review and rating consistently for most of the movies. You have to analyze different users, based on which user has rated the most number of movies, their occupations & their age-group.
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