Winter Internship / Training 2016 – 2017 Program

“Big Data Hadoop Implementation over RedHat Linux Platform Using Python ” @ INR 15,500/- only (BigData Hadoop + Python + RHCE (Free))
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“Can you Believe YOU CAN deploy your OWN Super Computing Cluster”
Admin Contact: +91 9351009002
Email: training@linuxworldindia.org

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How to Apply – Application Link :

http://www.linuxworldindia.org/winter-training-application-form.php

Global Trainings Included –

1. BigData Hadoop
2. Python Core Level
2. RedHat Certified System Administrator (RHCSA)
3. RedHat Certified Engineer (RHCE) Latest version 7

For More Program on Winter Training. Click Below link :

http://www.linuxworldindia.org/linuxworldindia-winter-internship-industrial-training.php

Willing to utilize your Winter Short Vacations or Winter Breaks in the best possible manner which will help you in securing your job?

LinuxWorld Informatics Pvt. Ltd. has Initiated Winter Training Program for a span of 4 Weeks / 6 Weeks / 8 Weeks wherein you would be learning the most demanding technology in the market.

What you will learn in this Big Data Hadoop Course?

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  1. Master the fundamentals of Hadoop Distributed File System (HDFS), Mapreduce and big data analysis
  2. Master the architecture of Hadoop 2.7  and installation of Cloudera Hadoop
  3. Advance concepts of MapReduce and coding complex MapReduce exercises
  4. Setup of Hadoop cluster on amazon ec2 instances
  5. In depth knowledge on Hadoop eco-system projects like Hive, Pig, Scoop, Oozie, Flume,etc. and doing complex analytical exercises
  6. Extend Pig and Hive by writing user defined functions (UDFs)
  7. Learn Impala for doing advancedBig Data analytics operations
  8. AVRO data formats
  9. Administrator, Maintain, Monitor, Troubleshoot Hadoop jobs and Hadoopclusteras well learn using cloudera Manager for handling day to day activities
  10. Master Spark components, RDD and understand difference between Hadoop and Spark
  11. Running Spark on a Cluster, Writing Spark Applications using Python, Java, Scala
  12. Learn how ETL tools connects with Map Reduce, Hive and Pig
  13. Master the art of Hadoop Testing using MR unit and other testing tools
  14. Learn Hadoop online for stack integration testing, roles and responsibilities of Hadoop tester, unit testing of MapReduce, Hive, Pig, automation testing using Oozie
  15. Learn test plan creation and testing strategies for large scale Hadoop project and data validation using Query surge tool
  16. Introduction to HBase Architecture
  17. You will work on 9 real life projects on Big Data Analytics and you will be provided with more than 70 datasets containing 1 billion data points
  18. Prepare for the Hadoop Certification

To more visit –

Making Your Private Cloud DevOps Ready

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For enterprises, implementing new software development processes like DevOps and continuous integration/continuous deliver, or CI/CD, means giving application developers a more agile, responsive and efficient cloud infrastructure.

For cloud operators, however, delivering that infrastructure can be a big challenge.

AppFormix recently joined with Rackspace in a webinar addressing the challenges operators face in delivering a DevOps-friendly infrastructure.

Kicking off the webinar was Rackspace Senior Director of Product Management Bryan Thompson, who leads the product team for Rackspace private cloud. Powered by Openstack, the world’s de facto standard for Infrastructure as a Service, Rackspace’s private cloud offers a single platform for managing containerized apps, virtual apps and bare metal apps across private, public and hybrid clouds.

Rackspace essentially offers “OpenStack as a Service” and simplifies for customers the process of setting up, configuring, monitoring and scaling OpenStack.

Rackspace is dedicated to supporting new software development processes like DevOps and CI/CD, Bryan said; the goal is to enable self-service capability for developers and eliminate the traditional bottlenecks encountered when allocating resources for testing, deployment and production at scale. The key to accomplishing this goal is helping operators overcome performance-hampering challenges of cloud management. He gave three examples of such challenges.

  • Very short life cycles of compute instances — Operators are adapting to a new paradigm managing “cloudy” and container-based workloads and volatile virtual machines. Applications and tiers of this cloud-native model are designed to scale up and grow very rapidly, then be torn down when not needed. In these agile environments, especially when using containers, application life cycles may be only minutes long. The life cycles of compute instances can be so short, in fact, that traditional monitoring tools are insufficient — the instance has come and gone before it can even be monitored and reported, especially if human intervention is required. Automated, real-time monitoring is needed to provide accurate, useful and actionable insight into these workloads.
  • Limited visibility to demand for capacity planning — With dynamic, versatile workloads to manage, operators need to be proactive in guaranteeing certain levels of service, availability and performance to their end customers. They need reliable capacity planning tools that offer visibility into all resources in the cloud stack to help predict when and where additional resources will be needed, before constraints occur.
  • Lack of access to real-time telemetry and performance data of physical and virtual infrastructure — In a DevOps world, the ability to deliver the experience end users demand requires infrastructure transparency of the entire cloud stack—down to the processor level. Operators need access to this information, of course, but also they need to be able to share it with developers so developers may consume infrastructure analytics within their applications and schedule workloads to achieve maximum performance.

Fortunately, through its partnership with AppFormix, Rackspace is able to address these challenges and more. The AppFormix cloud service optimization platform is now built in to every Rackspace private cloud, empowering operators with a data-driven cloud and all of its game-changing benefits.

DevOps benefits from data-driven private clouds

Also during our webinar, we explored how a data-driven cloud offers powerful solutions.

First, let’s define “data-driven cloud.”  A data-driven cloud is one that uses real-time, continuous analysis and measurement against totally customizable and configurable SLAs. An example is  Rackspace Private Cloud, which now includes the AppFormix cloud service optimization platform that delivers all of the game-changing benefits of a data-driven cloud.

With a data-driven cloud, operators have the ability to:

Know which parts of their infrastructure are healthy and which are not

AppFormix provides real-time monitoring of every aspect of the cloud stack, right down to the processor level. This includes visibility into every virtual and physical resource at your disposal. The user-friendly interface and customizable dashboard provide a comprehensive list of metrics based on industry best practices. SLAs are completely configurable.

Empower developers with visibility and control

AppFormix offers a dashboard that operators can share with developers via a self-service user experience. Developers then have access to process-level monitoring, with real-time and historical views of their resources and the ability to drill down to deeper and deeper levels of specificity about performance. Both operators and developers can create project-level reports with a click; the report content and the recipients are customizable, and data can be exported in any format. In addition, operators and developers have access to advanced alarming and notification capabilities and can establish static and dynamic thresholds based on their preferences.

Make well-informed capacity decisions

With AppFormix, operators know the true capacity levels of their infrastructure, any time and all the time. AppFormix also enables operators to model potential changes to see what impacts will be on capacity, availability and performance.

If this sounds great on a theoretical level, below are some “real-life” examples of what a DevOps-ready private cloud can do.

  1. Troubleshoot when a user is experiencing slowness;
  2. Real-time notification of events;
  3. Maximize infrastructure ROI using utilization reports;
  4. Determine if there is capacity for a new or expanding project;
  5. Improve availability with configurable policy for SLA.

To learn even more, check out our on-demand webinar, Making Your Private Cloud DevOps Ready with AppFormix and Rackspace.

Big Data Technologies – Most Mandatory Proficiencies to Grab a Career

Anyone running out of job ? Seriously?… No more worries about employment when you have Big Data around.  Presenting to my readers the tips and mandatory skills to glow with bright Data jobs in your hands in this Data world.

Today the Big data technologies are one of the newest technologies in the market and it will be a clever idea to grab the jobs of these trending technologies before it is too late. We should groom up with all the skills and land into these high demanding job profiles of big data technologies at its newest phase before these jobs become too common in the market. So get all the knowledge possible with big data technologies and hurry up to get hired.

Mathematical Analysis

111Big data is all about calculations. Always people with an educational background in mathematics and analytics are preferred to be working in data analytics. So seeing into the career scope of present age it is advisable for our new generations to strengthen their mathematics and real-time practices by undergoing degrees in mathematics, engineering and statistics.

Hadoop

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The last two years in the industry has proved the demand and it is clear that for the present and coming years Hadoop is going to rule the industry. Seeing the speed how the software vendors are initiating Hadoop in their enterprises, it is clear that Hadoop’s existence in the market will be a long story. Since the field of big data is really the strongest, so using Hadoop is immensely important in the technologies dealing with huge sets of unstructured data. Dealing big data with Hadoop requires great expert technicians of Hadoop. It’s an opportunity to fit into the demand of the industry by learning core skills of Hadoop like HDFS, MapReduce, Oozie, Hive, Flume, Pig, Hbase, and YARN.

Programming Languages

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Coders have got no expiry dates. This is because, whichever technologies you go, you will always be in need of programmers. Because programming gives life to software embedded inside hardware. In this big data industry, if you have an experience in programming of different languages like C,C++, Java, Python, etc then  your demand will never really going to die.

Spark

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Like Hadoop Spark has got the strength of fast performance, making it possible for applications to run 100 times faster.  The increasing of the in-memory stack can be an alternative to the processor analytics of Hadoop. In these big data world, Spark needs a huge number of manpower who is proficient with the core components of it.

Machine Learning

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In this big data world, artificial intelligence is getting a forward push to develop and raise newer and exciting humanoids. With the enhancement of artificial technology, more scientists and engineers are in a high requirement in order to meet the workforce. Hence, machine learning is a must required skill in order to get a job in artificial intelligence in this big data era.

NoSQL

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Today the NoSQL databases are working on the operating sides of the big data industry. NoSQL databases are used with high priority in the websites and mobiles along with the Hadoop commands. Same like Hadoop, this technology also stands in the similar level of demand in the tech planet.

 

 

 

 

 

SQL

nmIn this competitive era of big data technology, learning SQL holds a lot of demand. Although NoSQL is under the spotlight, but still, SQL is on a stable demand in the market and still is gaining a lot of funding and implementation in the industry today. So seeing the firm demand  of SQL it is on priority to brush up your SQL skills sooner.

Tableau or QlikView

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Working with data needs the ability to visualize, discovering the shape, size, structure and arrangement of data. Data visualization is a must for you to become a data artist and make all kinds of creativity you will assure on data. Experts in tableau and Qlikview with the ability for data visualization mainly focusing on to business intelligence and software visualizations are on priority requirement in the tech house today.

Resourcefulness wins Forever

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Technologies come, technologies evolve and technologies go. New jobs will get introduced and after a certain age, its demand reduces. But creativity never dies. If you develop your creative skills, then no matter which technology runs in the market, you will always manage to find a way to get into it and you will never ever go unemployed.

Big data Hadoop Winter Training in Jaipur

Big data Hadoop

Big data Hadoop is an advance technology that is use to produce and store giant data base in petabyte and zettabyte. World top most companies like Google, Facebook, Amazon etc. are using this technology to generate, store, manage and analysis large number of unstructured data. Hadoop is core platform for structuring big amount of data, and it solves the formatting problems. The storage method is known as Hadoop Distribution File system.

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Big data is the huge sets of data base that business to assist specific goals and setups. Big data can comprise many different kinds of data in many different formats. Hadoop is a tool of Big data that is use to handle huge unstructured data amount. It includes various main components, including a MapReduce set of functions and a Hadoop distributed file system (HDFS).

Hadoop technology is an open source framework coded in java. Software applications developed on Hadoop technology are run on gigantic data or information sets distributed across clusters. MapReduce is an operational model and application software framework for programming applications for Hadoop. MapReduce algorithm is capable to process applications and simultaneously run on different system.

Advantage of Big data Hadoop Technology:

  • Capable to store enormous data of any kind of data.
  • Highly Scalable
  • Fault tolerance
  • flexible
  • Cost Effective
  • Better Operational Efficiency

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Big data Hadoop Training

LinuxWorld Informatics Pvt. Ltd. is providing training on Big data Hadoop technology for all computer science students. Big data Hadoop certification is good option for both Fresher and experienced to get awesome career prospects. We providing an opportunity for students to improve their technical skills: Training offers a practical and professional environment where they can develop soft skills. The major advantage of this training is students get to learn from the basic steps of technology, and also work on live project in supervision of our well experienced industrial professionals.