Big Data - Hadoop - Training in chennai
Big data by its very definition means large data sets that it is almost awkward to work with using normal database management tools and businesses are leveraging big data. So various Challenges that impact this definition are capture, storage, search, sharing, analytics, visualizing and requires massively parallel software running on tens, hundreds or even thousands of servers.
Big Data Analytics
Big Data Analytics is relatively early in its adoption cycle. The following opinions from well-known market research and analysis firms elucidate what?s in store for Business Analytics. ''Analytics will define the difference between the losers and winners going forward'' : McKinsey. ''The challenge is that companies have far more data than people have time, and the amount of data that is generated every minute keeps increasing. In the face of accelerating business processes and a myriad of distractions, real -time operational intelligence systems are moving from 'nice to have' to 'must have for survival.' The more pervasively analytics can be deployed to business users, customers and consumers, the greater the impact will be in real time on business activities, competitiveness, innovation and productivity.'' : Gartner. This course on Big Data Analytics for Business is a combination of essential fundamentals, practical techniques, hands-on sessions on Hadoop, and case studies to cement all this together. Data is now generated by more sources and at ever increasing rates. Examples include Social Media sites, GPS based tracking systems, point of sale equipment, etc. The ability to process such data can provide that essential edge required for business success. Demand for Big Data professionals is rapidly increasing. Knowledge of Big Data can provide an advantage leading to faster professional advancement. This course on Big Data Analytics for Business is a combination of essential fundamentals, practical techniques, hands-on sessions on Hadoop, and case studies to cement all this together.
Five Job Roles for Hadoopers in BigData
Hadoop developer responsibilities involve actual coding/programming of Hadoop applications. Ideally the candidate should have at least 2 years of experience as a programmer. Hadoop developer roles and responsibilities are synonymous to a software developer or application developer - refers to the same role but in the Big Data domain.
Hadoop Developer Job Description
Hadoop Developer is a consultant with prior experience in building and designing applications using procedural languages in the Hadoop space. Most of the job portals like dice.com, monster.com define Hadoop Developer Job Description as “A person comfortable in explaining design concepts to customers as well being capable of managing a team of developers."
Hadoop Developer Roles and Responsibilities
- Defining job flows
- Managing and Reviewing Hadoop Log Files
- Manage Hadoop jobs using scheduler
- Cluster Coordination services through Zookeeper
- Support MapReduce programs running on the Hadoop cluster.
In most job sites like Monster,Dice, and Glassdoor you will find that the Hadoop developer job description will list the requirements for these specific skills:
- Ability to write MapReduce jobs
- Experience in writing Pig Latin scripts
- Hands on experience in HiveQL
- Familiarity with data loading tools like Flume, Sqoop
- Knowledge of workflow/schedulers like Oozie
A Hadoop architect roles and responsibilities include planning and designing next-generation "big-data" system architectures. He/She is also responsible for managing the development and deployment of Hadoop applications. Must have subject matter expertise and hands on delivery experience working on popular Hadoop distribution platforms like Cloudera, HortonWorks, and MapR.
Hadoop Architect Job Description
The Hadoop Architect Job Description defines the link between the needs of the organization, thee big data scientists and big data engineers as the Hadoop Architect is responsible for managing the complete life cycle of a Hadoop solution.
Hadoop Architect Roles and Responsibilities
The major Hadoop Architect Roles and Responsibilities include -
- Creating Requirement Analysis and choosing the platform
- Designing he technical architecture and application design.
- Deploying the proposed Hadoop solution.
- Extensive knowledge about Hadoop Architecture and HDFS
- Java Map Reduce
- Hive, Pig
A Hadoop tester's role is to troubleshoot and find bugs in Hadoop applications. Like in any software development lifecycle, a tester plays an important role in making sure the application is working as expected under all scenarios. Similarly a Hadoop Tester makes sure - the MapReduce jobs, the Pig Latin scripts, the HiveQL scripts are working.
Hadoop Tester Roles and Responsibilities
- Responsible for constructing positive and negative test cases in Hadoop/Pig/Hive components to arrest all bugs.
- Report defects to the development team or manager and driving them to closure.
- Consolidate all the defects and create defect reports
- Knowledge of Java to test MapReduce Jobs
- Knowledge of JUnit, MRUnit framework for testing
- Hands on knowledge of Hive, Pig
In the Hadoop world, a Systems Administrator is called a Hadoop Administrator. Hadoop Admin Roles and Responsibilities include setting up Hadoop clusters. Other duties involve backup, recovery and maintenance. Hadoop administration requires good knowledge of hardware systems and excellent understanding of Hadoop architecture.
Hadoop Admin Roles and Responsibilities
The listing of Hadoop admin jobs on popular job portals like Dice.com, Glassdoor.com, and Monster.com define Hadoop Admin Roles and Responsibilities as follows –
- Hadoop administration includes ongoing administration of the Hadoop infrastructure.
- Keeping a track of Hadoop Cluster connectivity and security
- Capacity planning and screening of Hadoop cluster job performances.
- HDFS maintenance and support
- Setting up new Hadoop users.
- Strong scripting skills in Linux environment
- Hands on experience in Oozie, HCatalog, Hive
- Knowledge of HBase for efficient Hadoop administration
For lack of a better term - Data Scientist is believed to be the "Sexiest" Hadoop job description of the 21st century. Data scientists thrive on solving real world problems with real data. They are very good at using different techniques for analysing data from different sources to help business make intelligent decisions. They need to have both skills of a software engineer and an applied scientist.
Data Scientist Roles and Responsibilities
- Plan and Develop big data analytics projects based on business requirements.
- Work with application developers to extract data relevant for analysis
- Contribute to data modeling standards, data mining architectures and data analysis methodologies.
- Solid understanding of data manipulation and data analytics
- Strong foundation in skills used in data science e.g. Pig, Hive, SQL
- Knowledge in SAS, SPSS, R is helpful