Big Data Analytics using Hadoop
Master concepts of big data Hadoop such as HDFS (Hadoop Distributed File System), Map Reduce, Hadoop Eco System components working on live streaming data.
- 120+ hours
- 665 Learners
- 24x7 Online LMS
Hadoop has been leading open source Big Data framework
73% of organizations have already invested or plan to invest in big data by 2016
The Big Data industry is expected to grow to $48.4 billion by 2018, as per Forbes estimates
Become equipped to process thousands of gigabytes of livestreamed data.
Learn via demo sessions on Hadoop tools like Sqoop,Oozie, Hue.
Find opportunities as Data Scientists, Big Data Engineers, Business Analytics Specialist etc. Big Data Specialists earn salaries anywhere between 6-15 lakh pa.
Course coverage caters to both fresher’s with Hadoop and also people who have some knowledge of Hadoop and related concepts
Understand a larger breadth of Hadoop concepts, and in greater detail.
Learn from industry experts through a course created by a veteran associated with HP, Yahoo, and such brands.
Who Should Attend
- IT professionals
- IT professionals looking for a change to cloud technologies
- Fresher looking for opportunities in cloud technologies
- Software Professionals
- Analytics Professionals
- ETL developers
- Project Managers
- Testing Professionals
The course will groom students with a variety of skills, tools and techniques to understand data, real time data and examine business problems , bring about key business solutions in a structured manner. Some of these include:
- Concepts of Hadoop Distributed File System and MapReduce framework
- Setting up a Hadoop Cluster
- Data Loading Techniques using Sqoop and Flume
- Program in MapReduce using MRv1
- Writing Complex MapReduce programs
- Performing Data Analytics using Pig and Hive
- Implementing HBase, MapReduce Integration, Advanced Usage and Advanced Indexing
- New features in Hadoop 2.0 – YARN, HDFS Federation, Name Node High Availability
- IntroductionChallenges of Processing Big DataDistributed SystemsHistory of HadoopHadoop OverviewEcosystem of HadoopHDFS and MapReduce ParadigmProcessing PipelineBig Data TechnologiesUse CasesFeatures of HadoopSummary
- IntroductionHadoop Installation and ConfigurationHive Installation and ConfigurationPig Installation and ConfigurationSqoop Installation and ConfigurationOozie Installation and ConfigurationFlume Installation and ConfigurationHbase Installation and ConfigurationHue Installation and Configuration
- IntroductionHDFS Configuration FilesData Storage in HDFSBlocks and SplitsMetadata FilesName Node – DemoHDFS Data Storage – DemoReliability and Rack AwarenessHigh AvailabilityData Replication – DemoReliable Storage – DemoHDFS ClientData Node – DemoHDFS Clients - DemoSummary
- IntroductionHDFS CommandsBasic HDFS Commands - DemoRead Anatomy in HDFSWrite Anatomy in HDFSAdditional HDFS Commands - DemoHDFS File System APIHDFS File System API - DemoHDFS Permission ManagementPermission Management – DemoSummary
- MapReduce 1 ArchitectureMR and Traditional ApproachArchitecture 1Introduction to YARNArchitecture 2Summary
- IntroductionExecuting a MapReduce Program - DemoDatatypes and APIsMapReduce ConceptsMapper – DemoMapReduce – DemoCombiners – DemoPartitioners – DemoDebug logs & Printing in MR Jobs – DemoPath Filters – DemoSplits – DemoNamed Output – DemoWrite MapReduce Keys and Values - DemoIdentity Reducers – DemoCounters in HadoopMapReduce Counters – DemoInput and Output FormatsAbout MR UnitMR Unit – DemoSummary
- IntroductionJob FlowJob SubmissionJob InitializingJob SchedulingMap Task ExecutionSort and ShuffleReduce Task ExecutionJob CleanupJob Failure – DemoStaggering Job – DemoSchedulerSummary
- Serialization - IntroductionUses of SerializationSerialization TechniquesSummaryCompression - IntroductionUses of CompressionCompression TechniquesSummary
- Introduction SequenceCustomization of Input Format APIsInput Format and Record Readers – DemoDistributed CacheDistributed Cache – DemoMap Side JoinsSideways JoinsMap Side Joins – DemoReduce Side JoinsReduce Side Joins – DemoSequence File FormatSequence File Creation – Demo Running MapReduce Jobs – Demo SummarySequence File with MapReduce -DemoHadoop StreamingHadoop Streaming – DemoConfiguring Development Environment using Eclipse – DemoRunning MapReduce Jobs – DemoSummary
- IntroductionHive vs RDBMSHive ArchitectureHive ComponentsHive Schema ModelHive Integration with HadoopHive Query LanguageTransformations in HiveHive Database Creation – DemoHive Tables – DemoHive Queries - DemoAdvanced Hive Partitioning – DemoBucketing – Demo SummaryAdvanced Concepts – DemoManage an XML or JSON files – DemoUse a predefined Serde – DemoSummary
- IntroductionMapReduce and PigModes of Execution in PigPig ClientPig Datatypes and OperatorsSQL vs Apache PigPig UsageLoading Data in Pig – DemoPig Dialects – DemoTransformations in Pig – DemoDebugging in Pig – DemoOther capabilities in Pig - Demo
- IntroductionCategories of NoSQL DatabasesHbase EvolutionHbase vs RDBMSHbase ArchitectureHbase ComponentsColumn FamilyHbase FundamentalsHbase StorageHbase ClientBasic CRUD OperationBasic CRUD Operation – DemoZookeeperZookeeper – DemoSummary
- Apache Sqoop - IntroductionSqoop UsageWorking with Sqoop – DemoAdvanced SqoopHive Integration – DemoHbase Integration – DemoSqoop Scripts - DemoApache Oozie - IntroductionOozie ClientBasic Workflow SetupTypes of Oozie ActionsControl StatementsDefining a WorkflowRun MapReduce with Oozie – DemoSummaryIntroductionHue User InterfaceWorking with Hive using HueWorking with Pig using HueMonitoring an Oozie Job using HueApache Hue – DemoSummary
- IntroductionApache Flume IntroductionFlume Core ComponentsLaunch FlumeApache Flume – DemoApache Spark and Storm IntroductionStorm ConceptsSpark Streaming ConceptsDeployment ArchitectureSummary
- Real Time Deployment - IntroductionSystem ArchitectureLogical Deployment OverviewPhysical Deployment OverviewSummaryBig Data Software and Tools - IntroductionStreaming ToolsNOSQL ToolsWorkflow ToolsAdministration ToolsOther Ecosystem ToolsSummary
With 2.5 quintillion bytes of data being created every day, Hadoop is changing the way companies manage their data. 73% of companies in India have already invested in Big Data, creating huge demand for Big Data Hadoop professionals.
Currently, only webinar instructor led version is available.
At Manipal ProLearn, you will be taught on the Hadoop 2.0 architecture, which is the latest stable version. The newest components like YARN, HDFS Federation and Name Node High Availability are included in this version.
During the course of this program you will learn all the concepts of Hadoop - from programming to admin. You will also be exposed to various tools through meticulously designed demos that teach you how the tools are effective in real business scenarios.
Learners interested in taking up this course are required to have basic knowledge of programming languages like Java. However, if you are not familiar with these programming languages, we can give you language training as well. You need to complete the programming language training within course access period of 3 months ofBig Data Hadoop. Once you complete the Java essential training, only then you will be introduced to the Hadoop course. You can find all the study materials related to programming language on our EDUNXT.MANIPALPROLEARN.COM.
The course duration is 90 days and you need to spend just 1 to 1½ hours every day for 90 days to become a pro in Big Data Analytics using Hadoop.
You can enjoy 3 months of access to all the course material. During these months you can download PDFs, watch recorded webinars and interact with the faculty, as and when required.
Big Data Hadoop online (webinar instructor led) training classes are the most convenient way to learn the course. You can attend the classes from the comfort of your home and can access all the study material on the EDUNXT.MANIPALPROLEARN.COM at any time during the duration of the course. Since all the live webinars are recorded, you can easily download and watch the webinar, if you miss any.
The course curriculum comprises 15 modules. We also provide demo as well as live data projects for hands-on experience. Learners will also get 4 projects/problem statements to solve along with Live Data Analytics which will help them understand how to analyse live feed from Facebook, Twitter etc. The online course contains video lectures that are thought by an industry veteran with more than 16 years’ experience in companies like HP, Infosys, etc.
The price mentioned on the page is inclusive of all taxes and you do not have to pay anything over and above that.
As soon you pay for the course, you will be provided with a login and password to access the EDUNXT.MANIPALPROLEARN.COM. You can find all the information and study material related to your course on the EDUNXT.MANIPALPROLEARN.COM. You can access this platform 24x7, download PDF files of study material and chat with faculty, when in doubt.
Besides the 15 course modules, learners will also be provided with a Virtual Management (VM) software which can be used to try the Hadoop concepts. It is downloadable, and thereafter, accessible lifetime. It doesn’t require any net connectivity, once downloaded. All tools like Pig, Sqoop, Oozie etc are pre-installed within the VM for the students to practice offline.
The advantage of the VM software is that it is a packaged software which doesn’t require command lines to be written to install the tools on it. They already come pre-installed in the VM and are ready to be used once the VM is downloaded.
Your system should have 4GB RAM core 2 duo processor. We can also provide remote access to our Hadoop Cluster, in case your system falls short of these requisites.
We will help you to setup the VM software in your System with local access. Manipal ProLearn’s Virtual Machine (VM) software can be installed on Mac or Windows machine. The detailed installation guides are provided on the EDUNXT.MANIPALPROLEARN.COM.
4 mbps internet connection is required for seamless access of the webinars.
The webinars are generally conducted on weekends and can be attended from anywhere. You don’t need to travel to any particular location for the same.
The webinars generally last for 2 hours. These are 2 way interactive sessions during which you will get live lectures from the esteemed faculty and also get a chance to clarify your doubts and ask questions, during the webinar. The exact timing of the webinar is shared 3 days in advance, via e-mail.
No sweat. In case, you are unable to attend the live webinar, you can go through the recorded version available on the EDUNXT.MANIPALPROLEARN.COM at a later point in time.
The exam window is activated 1 month after the course purchase. You will get 3 attempts to clear the certification. Please note that there should be a minimum gap of 7 days between each attempt. The exam attempts should be made within the remaining time of 2 months course access.
Yes. There is. Even after clearing the assessment in the first attempt, you can go for the remaining 2 attempts. The best grade among the 3 assessments will be considered as the final grade for certification.
The exam fee is included in the fee. You will not be charged anything extra for it.
The minimum mark that you need to pass is 50%.
No worries at all. If you are not able to pass the exam in first attempt, you will get two more attempts and we will not charge you anything. Just note that there should be a minimum gap of 7 days before taking the re-exam.
With a certification in Big Data using Hadoop, you can find jobs as Data Scientists, Big Data Engineers, and Business Analytics Specialist etc.
After completion of the course, you will become an expert in setting a Hadoop cluster, loading data using techniques of Sqoop and other Hadoop tools and how to implement in H base, among others.
Sorry, but you have access to the course only for 3 months, starting from the day of enrolment. However, the VM software provided has lifetime validity along with all the other downloadable reading content.
You can pay through your debit card or net banking in one shot. You can also pay by Credit Card from all the leading banks. EMI Option can be availed when using credit card (interest will have to be borne by you).
The Big Data Analytics using Hadoop certificate offered by Manipal ProLearn, on the successful completion of the course, is industry recognised and valid globally.
You can download the e-certificate as soon as you complete your assessment. No hard copy certificate will be provided.
Manipal ProLearn is a leading online professional certification provider in India and has tie ups with multiple corporates and recruitment firms. While we do forward the resumes of our qualified learners, we do not guarantee job placements. Having said that, if you follow the course meticulously and practice your skills on our VM environment, you will have a very good chance of landing a job anywhere.