Why Is Hadoop Training Important?

"The growing importance of Hadoop around the world has made Hadoop training an important topic. It is important that you understand the concept of Hadoop before you start off with your training program"

In the recent times, an increased demand for Hadoop has been seen around the world. Thus, if you are interested in knowing more about Hadoop and you are keen to get Hadoop Training then you've come to the right place. There are various online programs which are known for teaching the online audience about the art of Hadoop at the convenience of their home. By making use of online video training offers, such institutions are known for imparting the knowledge pertaining to Hadoop so that the online audience can utilize the skills and make good use of the Hadoop knowledge in progressing in their respective fields.

One of the highlights of Hadoop Training is the fact that it teaches an individual about the wide array of aspects which are attached to the big data. Such training programs help teach the online audience about the analytics and the reporting skills which are considered to be imperative in terms of effectively understanding the big data, all of which helps in improving the performance of the business on a holistic level. It is important that a person makes good and effective use out of these Hadoop Training programs which the Hadoop community around the world is increasing and trending at a phenomenal pace and the leading names in the IT sector are looking for professionals who are equipped with the necessary skillset.

Such Hadoop Training programs help the individual realize the importance that is being placed on big data around the world. It analyzes the insights of the data which ensure that the reporting and dashboard is managed effectively. Considering the growing importance and the potential job market for individuals who poses sound knowledge regarding Hadoop and big data, it is imperative that the opportunity of equipping oneself with the Hadop Training should be capitalized as soon as possible.

Understanding the importance of big data, compiling and organizing it in a systematic way and making sure that the big data is kept in such a way that it makes sense to a larger segment of the audience is a skill that is effectively imparted on the online audience in the Hadoop training programs. This helps save the organization a lot of hassle, money and time. Whereas on the personnel point of view, such skills ensure that their chances of being employed are higher than usual.

Thus, if you are looking to equip yourself with the latest trends in the field if IT, then Hadoop is what you should be effectively seeking out for. It is important for you to choose an online course that thoroughly covers the dynamics of the program on a holistic level, making sure that you get the understanding of Hadoop in a way that helps you make good use of your skills.

Benefits of Big Data Processing

Ability to process 'Big Data' brings in multiple benefits, such as-
• Businesses can utilize outside intelligence while taking decisions
Access to social data from search engines and sites like facebook, twitter are enabling organizations to fine tune their business strategies.

• Improved customer service
Traditional customer feedback systems are getting replaced by new systems designed with 'Big Data' technologies. In these new systems, Big Data and natural language processing technologies are being used to read and evaluate consumer responses.

• Early identification of risk to the product/services, if any
 
• Better operational efficiency
'Big Data' technologies can be used for creating staging area or landing zone for new data before identifying what data should be moved to the data warehouse. In addition, such integration of 'Big Data' technologies and data warehouse helps organization to offload infrequently accessed data.

Power of Hadoop

Apache Hadoop is an open source software project based on JAVA. Basically it is a framework that is used to run applications on large clustered hardware (servers). It is designed to scale up from a single server to thousands of machines, with a very high degree of fault tolerance. Rather than relying on high-end hardware, the reliability of these clusters comes from the software's ability to detect and handle failures of its own.

Credit for creating Hadoop goes to Doug Cutting and Michael J. Cafarella. Doug a Yahoo employee found it apt to rename it after his son's toy elephant "Hadoop". Originally it was developed to support distribution for the Nutch search engine project to sort out large amount of indexes.

In a layman's term Hadoop is a way in which applications can handle large amount of data using large amount of servers. First Google created Map-reduce to work on large data indexing and then Yahoo! created Hadoop to implement the Map Reduce Function for its own use.

Map Reduce: The Task Tracker- Framework that understands and assigns work to the nodes in a cluster. Application has small divisions of work, and each work can be assigned on different nodes in a cluster. It is designed in such a way that any failure can automatically be taken care by the framework itself.

HDFS- Hadoop Distributed File System. It is a large scale file system that spans all the nodes in a Hadoop cluster for data storage. It links together the file systems on many local nodes to make them into one big file system. HDFS assumes nodes will fail, so it achieves reliability by replicating data across multiple nodes.

Big Data being the talk of the modern IT world, Hadoop shows the path to utilize the big data. It makes the analytics much easier considering the terabytes of Data. Hadoop framework already has some big users to boast of like IBM, Google, Yahoo!, Facebook, Amazon, Foursquare, EBay etc. for large applications. Infact Facebook claims to have the largest Hadoop Cluster of 21PB. Commercial purpose of Hadoop includes Data Analytics, Web Crawling, Text processing and image processing.

Most of the world's data is unused, and most businesses don't even attempt to use this data to their advantage. Imagine if you could afford to keep all the data generated by your business and if you had a way to analyze that data. Hadoop will bring this power to an enterprise.

6 Reasons You Must Switch Career to Big Data Now

Big Data has got a lot of young professionals excited about the sterling career prospects and rightly so due to the sheer promise that this new domain holds. Getting a foothold in this exciting arena can take your career places, for sure. First let’s put things into perspective about Big Data. Read on.

These nuggets of information will convince you of the preponderance and inevitability of Big Data:

• Data production will be 44 times greater in 2020 than it was in 2009 – wikibon
• Bad data or poor data quality costs US businesses $600 billion annually – TDWI

According to TechCrunch study, we shall see an overwhelming proliferation of smartphones in the near future and it is estimated that we will have over 6 Billion of them by 2020. Also, did you know that by improving the data accessibility by a mere 10% can raise the bottom line of a Fortune 1000 company by as much as $65 million! Here is another eye opener – today only about 0.5% of the data at our disposal is every analyzed or utilized according to research from MIT Technology Review. So just imagine the potential of what we can do with Big Data in the near future.

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Seven reasons why you should switch over to a career in Big Data now:

1. Big Shortage of Skilled Professionals

As per a report from the International Data Corporation (IDC) there is a serious shortage of skilled workforce in the Big Data sphere. People with deep analytical expertise will be needed to the tune of 181,000 by 2018 and the need for people with skills in data management and interpretation could be five times this number, as per this IDC Report.

It would be prudent to expect that the Big Data market would be worth at least $46.34 billion by 2018 since that is what IDC has forecast. There will be huge upside in the various related fields of Big Data like software, services and infrastructure in the next five years. The rate at which Hadoop will grow will also be quite astounding.

2. The Massive IoT is just around the corner

The Internet of Things is on the cusp of a major boom. IoT is the set of devices, sensors, objects and all kinds of things that will be connected to the Internet in the grand scheme of things. There will be a lot of machine to machine data exchange in the not so distant future.

So it would be safe to say that the data of future would not be limited to the spreadsheet data that we are so used to. There will be all kinds of data and all this needs processing and analyzing capabilities on an unprecedented scale. Most of this data will be unstructured or semi-structured at best and there is an urgent need of technologies and skills to make sense of it all.

3. Big Data equals Big Money

This is a no-brainer – Big Data Training means big bucks. For the professionals with the right skills the salary can go through the roof and there is always another competing organization that is ready to top the already exorbitant salary that the Big Data professional is earning.

According to a salary survey from O’Reilly Media it has been proven that Big Data sits at the very top of the salary ladder. The job search portal Indeed says that the average salary that a Big Data professional can command is about $114,000 per annum!

4. Rapid Growth in Career

With Big Data growing at such a torrid pace how could your Big Data career possibly grow any slower? The trick for Big Data professionals is to learn and get trained in the next big thing in Big Data. This could be a new technology or a process that is finding much favour among the giants in the Big Data sphere like Google, Amazon, Facebook, IBM and the ilk.

In the field of Big Data, the professionals who show much promise can expect rapid promotions, blitzkrieg career growth and

5. Job Satisfaction: Never a dull moment at office

The job of Big Data professionals might look like any other nine-to-five job for the uninitiated but those working in this domain know better. Merit wins big time in this field and you need to explore ways to add value to the company that you are working with in hitherto unheard ways. The technology can do only so much but it is the sheer human ingenuity that adds the ultimate value and improves the revenue and profits of any organizations. Expect a lot of unguided exploration, exciting discoveries, newer ways of doing things and ‘aha moments’ at your office if you are in this promising Big Data field.

6. Vast Field with Big Job Opportunities

In the world of Big Data we are presently playing on a chessboard so big we are not able to see the entire board. Hadoop is just the tip of the iceberg. Expect newer technologies to come real thick and fast. Also organizations regardless of their industries need professionals with diverse skills sets. Here are some of the job titles that companies are looking out for:

• Big Data Engineer
• Business Analyst
• Analytics Engineer
• Machine Learning Specialists
• Hadoop Developer
• Information Architect
• Statisticians and Mathematicians
• Data Visualization Experts
• Database Administrator
• Hadoop Architect
• Data Scientist
• IT Security Analysts
• Business Managers
• Software Testers                  

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Know More About Apache Hadoop Software Training and Big Data Technology

As a regular Internet visitor, you might have come across many websites. Have you ever thought of that no two websites are alike in structure, layout, color theme, graphics, texts and presentation of contents? This is because of the handiwork of website developers using assorted software solutions, and web designing and development technologies. As of today, the World Wide Web network is bubbling with more than 634 million websites and growing. Newer additions in technologies and software applications get invented by experts and offered for use for web developers constantly. Apache Hadoop Software is one such latest sophisticated solution; another is Big Data technology to handle huge data sets inside websites.

Here is an overview of Apache Hardware and where you can get suitable training for making use of this software solution. It is too technical to explain the intricacies of Apache Hardware here. Suffice it to understand what is what about this software and where it is useful. In the Internet World, there are many software solutions developed and distributed for free as Open Source and for a price. Apache Hadoop is Open Source software.

Apache Hadoop is mainly used to support data-intensive web applications. Simply it can divide software applications relating to huge data clusters, into small fragments for easy understanding, recording and repeated usage. For programming Apache Hadoop the ideal computer programming language is Java; many other languages can also be used provided they are streamlined to implement the parts of Apache Hadoop software. With more and more end-users for this software solutions coming, they become contributors for refining with latest additions of Apache Hadoop platform.

Apache Hadoop is gaining rapid popularity, as this is used by many world-renowned websites like Google, Yahoo, Facebook, Amazon, Apple, IBM etc. These big names denote the importance of this sophisticated software for commercial use, in today's intensive competition of Internet Marketing. No wonder many web developers and individual software developers are keen in getting online training in this technically-advanced software solution.

Here it is important to learn how Big Data technology is clubbed with Apache Hadoop software training. There are several commonly used software applications to create, handle, manage, control, and maintain data-bases all over the corporate world in computers. Your head will be reeling how much of data is created and transmitted every day, with these common data-creation software. Yet when compared to Big Data technology, which operates in petabytes for creation of complex data sets, these are dwarfed in size.

A few examples where Big Data technology is put into use will help understand the magnanimity of it. Internet Search Indexing, scientific researches such as genomics, atmospheric science, biological, biochemical, astronomy, medical records, military surveillance, and photography archives, social networks and big ecommerce websites etc. are some of the end users for Big Data technology.

An Insight Into Big Data Analytics Using Hadoop

he large heap of data generated everyday is giving rise to the Big Data and a proper analysis of this data is getting the necessity for every organization. Hadoop, serves as a savior for Big Data Analytics and assists the organizations to manage the data effectively.

Big Data Analytics

The process of gathering, regulating and analyzing the huge amount of data is called the Big Data Analytics. Under this process, different patterns and other helpful information is derived that helps the enterprises in identifying the factors that boost up the profits.

What is it required?

For analyzing the large heap of data, this process turns very helpful, as it makes use of the specialized software tools. The application also helps in giving the predictive analysis, data optimization, and text mining details. Hence, it needs some high-performance analytics.

The processes consist of functions that are highly integrated and provides the analytics that promise high-performance. When an enterprise uses the tools and the software, it gets an idea about making the apt decisions for the businesses. The relevant data is analyzed and studied to know the market trends.

What Challenges Does it Face?

Numerous organizations get through various challenges; the reason behind is the large number of data saved in various formats, namely structured and unstructured forms. Also the sources differ, as the data is gathered from different sections of the organization.

Therefore, breaking down the data that is stored in different places or at different systems, is one of the challenging tasks. Another challenge is to sort the unstructured data in the way that it becomes as easily available as the accessibility of structured data.

How is it used in Recent Days?

The breaking down of data into small chunks helps the business to a high extent and helps in the transformation and achieving growth. The analysis also helps the researchers to analyze the human behavior and the trend of responses toward particular activity, decoding innumerable human DNA combinations, predict the terrorists plan for any attack by studying the previous trends, and studying the different genes that are responsible for specific diseases.

Top Two Concerns of Big Data Hadoop Implementation

In general, data can be classified into three categories. Any data which can be stored in databases can be called as Structured data. For example, transaction records of online purchase can be stored in databases. Hence, it can be called as Structured data. Some data can be partially stored in databases which can be called as Semi-Structured data. For example, the data on the XML records can be partially stored in databases and it can be called as Semi Structured Data.

The other forms of data which will not fit into these two categories are called as Unstructured Data. To name a few, data from social media sites, web logs cannot be stored analysed and processed in databases, therefore it is categorised as Unstructured Data. The other term used for Unstructured Data is Big Data.

According to NASSCOM, Structured Data accounts for 10% of the total data that exists today in the Internet. It accounts for 10% of semi-structured data and the remaining 80% of data comes under Unstructured Data. In general, organizations use analysis of Structured and Semi Structured Data using traditional data analytics tools. There was no sophisticated tools available to analyse the Unstructured Data till the Map Reduce framework which was developed by Google. Later, Apache developed a framework called "Hadoop" which analyses all these Data and reveals information which will be of great help for business to take better decisions.

Hadoop has already proved its importance in several areas. For example, according to NASSCOM, many organizations have started using Big Data analytics. National Oceanic and Atmosphere Administration (NOAA), National Aeronautics and Space Administration (NASA) and several pharmaceutical and energy companies have started using big data analytics extensively to predict their customer behaviour.

According to a recent research from Nemertes group, organizations perceive value in Big Data analytics and planning to have a better leverage in reaping the benefits of Big Data Analytics. The New York Times is using Big Data tools for text analysis, and Walt Disney Company use them to correlate and understand customer behaviour in all of its stores and theme parks. Indian IT companies such as TCS, Wipro, Infosys and other key players have also started to reap the immense potential which Big Data continues to offer.

This clearly shows that Big Data is an emerging area and many companies have started to explore new opportunities. Meanwhile, usage Big Data is proving to be worthwhile but at the same time it may also be noted that privacy and data protection concerns have also risen.

The concern about Big Data analytics is very much valid from the viewpoint of privacy. Let me give a very simple example. Nowadays I am very much sure that most of us use Social media such as Face book, Twitter and many other social forums and most of us watch videos on YouTube. Imagine these websites using Big Data Analytical tools to identify your activity on the Internet, to analyse data, your search behaviour and the content you have watched in social media. Through Big Data your activity on the Social Media Forum can be clearly identified. This is a blatant violation of your privacy. Further, just imagine the organization is sharing the data from the analysis to a few marketing agencies, this in turn creates more privacy issues.

Why Big Data and Hadoop Training Is a Must for Organizations

Business is never been a cake walk and it consists of lots of information, data and other skills. With the technological advancements professionals and learners need to keep themselves updated and match the pace. For an example, sorting and tracking Big Data requires enough skilled man power.

If sources are to be believed, there are institutes which have started offering Big Data and Hadoop Training. Both professionals and newbie learners are looking for these trainings for their career betterment.

This article is about why Big Data and Hadoop Training are important and where one can avail these courses? Well, to start with, Big Data is one terminology that explains a huge volume of data. Big Data is both structured and unstructured data which enter to any business on day to day basis. At the same time, one can easily differentiate the numbers of data they can actually count on. Most important thing is that what the organizations will do with those data.

Companies prefer analyzing those data and get all the insights which can lead them to take the better decisions and accomplish the business moves with the right strategy. Thus Big Data plays an important role for any organization for the development of that particular organization. At the same time, Hadoop is an open source software platform for collecting data and running various applications in bulk for serving hardware.

Hadoop is the one of the efficient sources that offers huge data storage of different kinds of data. This open source platform has the ability of enormous processing authority and has the capability to control limitless synchronized jobs.

Are you looking for Big Data and Hadoop training? Then you have landed on the right article. As per different sources, there are different organizations which have started offering different Hadoop courses for Hadoop Developer, Hadoop Admin and Hadoop Data Analytics. Thus, enrollment can be done according to the preference areas and as per the professional requirements.

All you need to do is just contact the institute and ask for the preferred courses and these short-term strategic professional courses will be just the best in shaping your career graph. Most of these organizations have their own Live Support and Drop a Query form for the sake of communication.

Become a Certified Big Data Practitioner and Learn About the Hadoop Ecosystem

A report by Forbes estimates that big data & Hadoop market is growing at a CAGR of 42.1% from 2015 and it will touch the mark of $99.31 billion by 2022. Another report from Mckinsey estimates a shortage of some 1.5 million big data experts by 2018. The findings of both the reports clearly suggest that market for big data analytics is growing worldwide at a massive rate and this trend looks to benefit IT professionals in a big way. After all, a big data hadoop certification is about gaining in-depth knowledge of the big data framework and becoming familiar with the Hadoop ecosystem.

More so, the objective of the training is to learn the use of Hadoop and Spark, together with gaining familiarity with HDFS, YARN and MapReduce. The participants learn to process and analyze big datasets, and also gain information in regard to data ingestion with the use of Sqoop and Flume. The training will offer the knowledge and mastery of real-time data processing to trainees who can also learn the ways to create, query and transform data forms of any scale. Anyone to the training will be able to master the concepts of Hadoop framework and learn its deployment in any environment.

Similarly, an enrollment in big data Hadoop training will help IT professionals learn different major components of Hadoop ecosystems such as Pig, Hive, Impala, Flume, Sqoop, Apache Spark and Yarn and implement them on projects. They will also learn about the ways to work with HDFS and YARN architecture for storage and resource management. The course is designed to also enrich trainees with the knowledge of MapReduce, its characteristics and its assimilation. The participants can also get to know how to ingest data with the help of Flume and Sqoop and how to create tables and database in Hive and Impala.

What's more, the training teaches about Impala and Hive for portioning purposes and also imparts knowledge about different types of file formats to work with. The trainees can expect to understand all about Flume, including its configurations and then become familiar with HBase and its architecture and data storage. Some of other major aspects to learn in the training include Pig components, Spark applications and RDD in detail. The training is also good for understanding Spark SQL and knowing about various interactive algorithms. All this information will be particularly helpful to those IT professionals planning to move into the big data domain

DevOps Automation for Faster and Continuous Product Release

DevOps

Although the above example is somewhat crude it is a fair assessment of what application development can be like end-to-end. Everyone in the industry knows that this is the 'normal' state of affairs and accept that it is less than perfect. DevOps has begun to appear on the scene as the answer to the traditional silo approach. DevOps attempts to remove the silos and replace them with a collaborative and inclusive activity that is the Project. Application Development and Solution Design benefit from DevOps principles.

What needs to be done to remove silos:

    Change the working culture
    Remove the walls between teams (and you remove the silos)

Keys:

    Communication, Collaboration, Integration and Information Sharing

Easy to say and hard to do.

Most SMEs like to keep their information to themselves. Not true of all but, of many. It's part of the traditional culture that has developed over many years. Working practices have made change difficult. Management of change is one of the most challenging tasks any company can embark on. Resistance will be resilient as it is important that people give up something to gain something. Making it clear what the gains are is imperative. People will change their attitudes and behaviours but, you have to give them really good reasons to do so. I've found that running multi-discipline workshops for the SMEs has proven an effective method of encouraging information-sharing and the breaking down of those 'pit-walls'.

Explaining to the teams what DevOps is and what it is supposed to achieve is the first part of the educational process. The second is what needs to be done.

State specific, measurable objectives:

    Implement an organization structure that is 'flat'. If we espouse horizontal scaling, why not horizontal organizations?
    Each App-Dev or Solution-Dev is a project and the team is end-to-end across the disciplines
    Implement ongoing informational exchange and reviews
    Make sure that everyone signs up to DevOps and understands the paradigm

What is DevOps

Just like the Cloud paradigm it is simply another way of doing something. Like Cloud it has different definitions depending on to whom you are speaking at the time.

Wikipedia states: Because DevOps is a cultural shift and collaboration between development and operations, there is no single DevOps tool, rather a set or "toolchain" consisting of multiple tools. Generally, DevOps tools fit into one or more categories, which is reflective of the software development and delivery process.

I don't think that this is all DevOps is. The inference is that DevOps is concerned only with application development and operations. I do not believe that. I believe that DevOps is a paradigm and that like other IT 'standards' and paradigms it is relevant to all IT and not just applications. By removing the partitions between each practice in the chain and having all the key players involved from day one, as part of an inclusive and collaborative team, the cycle of application development and solution design becomes a continuous process that doesn't have to divert to consult each required expert. No-one needs to throw a document over the wall to the next crew. Each document is written within the collaboration process and this has to make the document more relevant and powerful. Imagine that the project team is always in the same room from concept to deployment and each expert is always available to comment on and add to each step of that project. How much better than the traditional method where it can take days to get an answer to a simple question, or to even find the right person to ask.

The mantra is: Develop, Test, Deploy, Monitor, Feedback and so on. This sounds application-orientated. In fact, it can apply to the development of any IT solution. Like ITIL, TOGAF and the Seven Layer Reference Model it can be applied to any and all IT activities from development right through to support services. DevOps puts us all on the same page from the start to the finish.