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Hadoop training kit from lcc infotech
- 1. Big Data Learn the basics of the Hadoop Distributed File System (HDFS) and MapReduce framework and how to write programs against its API, as well as discuss design techniques for larger workflows. This training also covers advanced skills for debugging MapReduce programs and optimizing their performance, plus introduces participants to related projects in Distribution for Hadoop such as Hive, Pig, and Oozie. The course/training is designed specifically for CEO, CTO to Managers, Software Architect to an Individual Developers and Testers to enhance their skills in BigData world. You will learn when the use of Hadoop is appropriate, what problems Hadoop addresses, how Hadoop fits into your existing environment, and what you need to know about deploying Hadoop. After completing the training, attendees can leverage our Hadoop Certification Exam Simulator for Developer as well as Administrator to clear the Hadoop Certification. Since launch 150+ attendees already cleared the exam with the help of our simulator. Hadoop is one of the top Job trends right now. There are various top most MNCs like IBM, Microsoft, Oracle, Accenture and many more companies have all incorporated Hadoop. Few other companies like Amazon, Ebay, Yahoo, Hortonworks, and Facebook are looking for Hadoop professionals. Many of the companies are finding enough IT professionals with certain skills like Hadoop. That spells high pay. You have a query about, what are the prerequisites to learn Hadoop? There is no strict prerequisite to start learning Hadoop. However, if you want to become expert in Hadoop and make excellent career, you should have at least basic knowledge of Java and Linux. If you don’t have any idea on Java or Linux? Don’t worry, you still can start learning Hadoop. The best way would be parallel spend some time on Java and Linux too. We can train and help you on learning Basics of Java and Linux. Holding Java is an added advantage, but it is not strictly prerequisite for working or learning Hadoop. Tools like Hive and Pig that are built on top of Hadoop offer their own high-level languages for working with data on your cluster. Industry Where Hadoop is Being Used: Energy & Utilities Financial Services Government Healthcare & Life Sciences Media & Entertainment Retail E-Commerce Consumer
- 2. Product Technology Telecommunications Start ups(They are trying their each & every resource should have Hadoop knowledge) Faculty profile:- They are having the training and consulting experience for more than 14 years with the intention of dramatically increasing profit, productivity, and the performance of people by building high scale computing solutions. They have been developing Hadoop based technology for the past 5 years. Our Trainer’s recent innovation, while working as the principal architect, was recognized by the Fast Company magazine as the most innovative healthcare big data platform in the world and was featured in the magazine. Our Trainer holds US patents related to healthcare big data technology. They have architected, developed and brought one of the most innovative electronic medical record systems in the US and Indian market. Why Hadoop? Big Data is defined as high volume, velocity and variety information assets that demand cost- effective, innovative forms of information processing for enhanced insight and decision making. High Amount of the data extracted from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals, to name a few are unstructured. All of this unstructured data is Big Data. Organizations are discovering that important decisions can be made by sorting through and analyzing Big Data. As the highest amount of this data is "unstructured/unorganized", it must be formatted / structured in a way that that makes it suitable for data mining and subsequent analysis. Apache Hadoop is open source core platform for structuring / organizing Big Data, and solves the problem of making it useful / helpful for analytics purposes.
- 3. Course Curriculum : Courses:- Hadoop Training:- We provide Apache Hadoop training & Our training programs are highly interactive, hands-on and are scheduled to meet the demands of working professionals. Training Highlights Prepare you to be a Hadoop expert Every student builds and play with their own Hadoop cluster Our multi-node clusters are available for each student to practice after the training. Evening classes for working professionals Hands-on training with real-world Hadoop use cases Audience profile:- Excellent written and oral communication skills in English Innovative and creative thinking and strong initiative Minimum three years related field work experience 1. Big Data and conventional approaches What is Big Data conventional approaches Problems with conventional approaches 2. Hadoop introduction Open source, developed / backed by top communities Different flavors comparison Use-cases HDFS Map-Reduce 3. HDFS concepts Architecture Distributed storage High Availability Fault-tolerance and Reliable data storage Scalability 4. Map-Reduce concepts Architecture High performance parallel data processing Network and disk transfer optimization (Data Locality) Scalability Fault tolerance
- 4. 5. Hadoop setup on single node Standalone mode Pseudo-distributed mode 6. HDFS hands-on 7. Map-Reduce hands-on 8. Cloud Computing 9. Hadoop Cluster setup 10. Work-Shops on real use-cases 11. Advance Map-Reduce concepts 12. Hadoop cluster optimization 13. Hadoop Problems and Troubleshooting 14. Hive Basics Installation Hive hands-on meta-store and configurations 15. Pig Basics Installation Hands-on 16. HBase Basics Installation HBase hands-on 17. Flume Basics Installation Hands-on
- 5. We present real world scenario-based training developed by the software architects and builders of highly scalable solutions based on Apache Hadoop with unmatched depth and expertise so that you can be assured you are learning from the experts. We offer the following courses designed for software developers, architects and cluster administrators. Example Hadoop Administration Consultant:- Should have 4+ years of IT experience and 1+ years of Hadoop Administration experience Hadoop cluster administration that includes adding and removing cluster nodes Recovering Name node. Importing and exporting data from HDFS Management of Hadoop log files Had done Hadoop cluster maintenance, monitoring and trouble shooting Experience in day to day production support of Hadoop infrastructure like HDFS maintenance, backups, manage and review Hadoop log files. Hands-on experience on building large scale systems utilizing Big Data Technologies Installation and configuration of Hadoop/HBase cluster Linux/UNIX commands, Shell scripting, vi editor. Willingness to learn new tools and technology. Design and develop solutions using Hadoop to tackle big data, information retrieval, and analytics problems. Experience with Core Java and SQL Hadoop Administration Consultant:- Job Description Data loading and optimization (various formats) to Hadoop. Management of Hadoop log files. Recovery of nodes. Maintenance of Hadoop configuration files. Hadoop cluster maintenance, Performance monitoring and trouble shooting Linux/UNIX development. Usage of tools such as Ambari, HCatalog, HBase, Oozie, Hive etc. Use Teradata adapters to Hadoop to manage Hadoop environment with the Teradata relational database. Interface with Teradata Engineering staff as needed to resolve complex technical issues Transfer knowledge and expertise to other TERADATA professional services associates. Provide technical expertise to data warehouse clients that will contribute to innovative business solutions.
- 6. Sr. Hadoop Administration:- Requirements Strong understanding of SQL in accessing and manipulating data Strong understanding of system architecture. Understanding of Unix operating system Strong understanding of general programming concepts Advanced analytical and problem solving skills Experience with the following software required: Unix, shell scripting, Netezza Hadoop/MapReduce Infrastructure and associated Apache projects, Apache Hadoop project skills, Oracle, MySQL, Java, HBase, Hive, Pig, Mahout, etc Experience with the following software desired: Exposure to Business Intelligence tools (Tableau/Business Objects), Application Development experience preferred, No-SQL Database experience a plus Manager - Projects - Hadoop Admin Job Description:- Candidate must have experience of atleast 1+ year in installing and setting up a Hadoop cluster in Production Environment. Must have knowledge of various Hadoop Distributions, pros and cons of each distribution. Must have knowledge in implementing security features for Hadoop cluster and has understanding of Distributed Computing concepts. Should be capable of installing, configuring and administering on any of the Linux distributions. Should have basic knowledge of setting up CRON jobs and monitoring Oozie jobs. Hadoop Professional:- Job Description Data loading and optimization (various formats) to Hadoop. Management of Hadoop log files. Recovery of nodes. Maintenance of Hadoop configuration files. Hadoop cluster maintenance, Performance monitoring and trouble shooting Linux/UNIX development. Usage of tools such as Ambari, HCatalog, HBase, Oozie, Hive etc. Use Teradata adapters to Hadoop to manage Hadoop environment with the Teradata relational database. Interface with Teradata Engineering staff as needed to resolve complex technical issues Transfer knowledge and expertise to other TERADATA professional services associates. Provide technical expertise to data warehouse clients that will contribute to innovative business solutions.
- 7. Team Lead :- Hadoop Stack Job Description: 2+ years of hands-on experience with the Hadoop stack (Map Reduce Programming Paradigm, HBase, Pig, Hive, Sqoop) Experience with key-value store technologies such as Cassandra and documents based storages like Mongo DB would be a plus 2+ years of hands-on experience with some level of administration, configuration management, monitoring, debugging, benchmarking and performance tuning of Hadoop/Cassandra 4+ years hands-on experience with open source software platforms and languages (e.g. Java, Linux, Apache, Perl/Python/PH Previous experience with RDBMS, SQL, database performance tuning, high scale application handling is highly desirable Hands-on writing Map Reduce Job and scheduling and monitoring Map Reduce jobs Desired Profile: Good development experience in Hadoop Good communication skills Experience with optimizing performance of front-end applications SEO best-practice experience Understanding of data warehousing and business intelligence technologies Experience with architecture and design of analytics platforms Experience in AWS is a plus Excellent problem solving and analytical skills Hadoop Developers and Architects - Job Description Hands on experience in application development using Java/J2EE, Perl, JSP, XML Experience with job/workflow scheduling and monitoring tools like oozie, Zookeeper Programming lang like Python, Ruby, RoR, BI Tools like Informatica, Pentaho, Talend Hadoop Developer and Architect :- Position Summary:- Our divisions objectives is architecting and implementing Hadoop System. We provide highly available Hadoop Cluster Environment. We are currently looking for Developer, SA (software architect), DBA (database administrator), and Network Architect. Developer for Hadoop This position is responsible for the design and implementation Hadoop platform and service. Task includes develop and customize Hadoop and related Service.
- 8. A successful candidate must have experience on designing and implementing Hadoop platform and service. Software Architect for Hadoop Cluster The Hadoop software architect designs and implements Hadoop systems using open source and/or commercial Haddop management software as well as designing highly scalable software applications for clients. A successful candidate must have deep understanding of Distribute File System, MapReduce, NoSQL(Cassandra, MongDB, CouchDB), Scheduling and Program Languages (Java). Desired Skills & Experience:- A successful candidate must meet one or more of the following requirements: MapReduce Data Programming Framework Distributed File System Data caching & Data processing Optimization skill Distrubuted Processing (Hive, Pig, Sqoop, ZooKeeper) NoSQL (Cassandra, MongoDB, CouchDB) Linux system administration (RedHat, Ubuntu, CentOS) Shell programming in bash, ksh, perl, expect, php Server / Storage (Dell, IBM, HP, EMC, Netapp, Cisco) must have Rack n Stack experience Storage management experience with EMC, Hitachi, NetApp - especially Network storage clustering experience: DRBD, NFS, iSCSI, SAN.