Is Hadoop Racing Fast towards Future?

Let us find out about Hadoop and Its Future and explore the possibilities..

Huge Investment in Hadoop and Bigdata Technology

“More than half a billion dollars in venture capital has been invested in new bigdata technology” – Dan Vessett, IDC

It is beyond any doubt that Big Business houses have invested millions of bucks in Hadoop and bigdata technology. The reason is obvious! Hadoop caters to the Digital world by storing, processing, and by digging out meaningful data from petabytes and terabytes of data. It is the age characterised by production of huge data at an uncontrollable speed, which needs to be processed at an equivalent thrilling velocity to counter the inertia that can otherwise slacken to almost dead speed all the systems across the globe.

According to Times of India, Hadoop is a saviour from data congestion. In an article on Hadoop,Times of India reports:  

“As the world moves to a digital age, there is literally an explosion of data and Hadoop makes it possible to stay on top of it. If a few years ago, megabytes and gigabytes used to be the extent of data, experts are now talking of several petabytes.”

Bigdata Hadoop Market – On the Rise!

Bigdata Hadoop Market is certainly on the rise! Digitalization and other factors have made things accessible while simultaneously making it difficult to keep data structured and well-managed. How to manage data is the key concern for all the commercial houses for which these rely on Bigdata solutions, therefore increasing its scope manifold. However, with more and more business houses depending on Bigdata Solutions for enterprise success, there is an ever-rising demand for efficient Bigdata professionals, who have an expertise in the areas of Hadoop and related technologies such as Pig, Hive, Sqoop, Kafka, and Oozie. Though the demand for bigdata professionals is on the high, and “Hadoop-as-a-Service” is emerging as a leader, there is a severe shortage of bigdata professionals, with many leading magazines pointing it around 140,000-190,000 by the end of 2018.

Which Companies hire Bigdata Hadoop Professionals?

Myriad companies employ Bigdata Hadoop Professionals to mine significant information from the volumes of unstructured data, infinite clickstream logs, and from numerous algorithms. Hadoop Developers are in great demand in various sectors such as Banking, Healthcare, E-commerce, Telecom, and Automobile. On a global scale, big names like Facebook, Twitter, Walmart, Royal Bank of Scotland, and Deutsche Bank are associated with Bigdata Technologies. In India, Banks such as Axis, Kotak Mahindra, HDFC, YES Bank, ICICI use Bigdata Hadoop. In the e-commerce and telecom industry, companies such as Flipkart, Jabong, Shoppers Stop, Snapdeal, and Bharti Airtel, Idea Cellular respectively, hire bigdata Hadoop professionals.

Other companies that hire Bigdata Professionals are:

“Big Data is the new definitive source of competitive advantage across all industries” – Jeff Kelly, Wikibon”

It is for sure that data will not cease to bombard the systems for it has already set on its unending fierce journey. With petabytes and zettabytes of data coming our way, there is a never ending hope for Hadoop Professionals to excel in their careers. With a rapidly growing e-commerce industry and social media, and with majority of the population spending maximum time on the internet and other allied services, Bigdata Hadoop certainly has a long way to go!

Having foreseen the ever-rising demand of bigdata Hadoop Professionals, ETLhive has specifically designed its Hadoop Training Course in such a way that it makes their customers industry-ready. It is undoubtedly evident that bigdata solutions have worked wonders in diverse sectors. This remains the primary reason why everyone is keen on undergoing Hadoop training. To have hands-on experience in Hadoop Development and Hadoop Administration, and to undergo extensive training with some real-time industry projects in hadoop, join ETLhive, deemed as the best hadoop training institute in Pune. At ETLhive, industry-experienced training professionals impart a specifically targeted career-oriented training in hadoop. The hadoop training course at ETLhive is comprehensive and covers all the significant aspects such as Pig, Hive, Sqoop, MapReduce, Flume, Kafka, Oozie, MongoDB, Elastic Search, and Spark and Scala. Come, join, learn, and excel with ETLhive because We Deliver What We Promise!

Roles and Responsibilities of Hadoop Professionals

Let’s have a look at the Roles and Responsibilities of Hadoop Professionals.

Meet the Happy Hadoopers…

I take care of the needs of the organization and execute my responsibilities by bridging the gap among Big data Scientists, Big data Developers, and Big data Testers. I ensure that the proposed Hadoop Solution gets materialized the way it is designed to be.

Check out what my profile is:

• I plan and design bigdata system architectures
• I create requirement analysis
• I am responsible for platform selection
• I design Hadoop applications and plan their development
• I ensure successful progression of development life cycle

I am skilled in:

• Hadoop Architecture
• Hadoop Distributed File System (HDFS)
• Hadoop Distribution Platforms: Cloudera, HortonWorks, MapR
• Java MapReduce
• HBase, Hive, Pig

I am Happy because I earn a lot!

I am Happy because there are number of opportunities in this field!

Look at the facts:

I love programming and that is what my profile demands out of me. I am a programmer akin to other software programmers but I specialize in BigData Technologies. I have a strong technical knowledge of computer procedural languages and of all the concepts that are central to create and deploy Hadoop applications.

Have a look at my roles and responsibilities:

• I develop Hadoop Applications
• I manage and monitor Hadoop Log Files
• I manage Hadoop jobs using scheduler
• I design, build, install, and configure Hadoop
• I maintain security and data privacy
• I am responsible for Cluster Coordination Services through Zookeeper
• I develop MapReduce coding running on Hadoop cluster
• I design scalable web services for data tracking
• I test software prototypes and supervise its’ transfer to operations

My Skill-set includes:

• Hadoop Distributed File System (HDFS)
• Hadoop Distribution Platforms: Cloudera, HortonWorks, MapR
• Java MapReduce
• HBase and HiveQL
• Pig Latin Scripts
• Multi-threading and concurrency concepts
• Data Loading Tools: Flume and Scoop
• Workflow and Schedulers: Oozie

I am Happy because I am quite confident about my future. 
I am happy because I am earning well and Job trends indicate fortunate years for me ahead.

See what Indeed.com points out:

I test the Hadoop application under consideration. My responsibility includes finding bugs and carrying out the process of troubleshooting. I make sure that the MapReduce jobs, HiveQL scripts, and Pig Latin scripts are tested properly so that they work under all scenarios without any trouble.

I am also responsible for:

• Constructing test cases to find bugs
• Creating reports about defects
• Finding and reporting defects to the managers and the development team

I have an in-depth knowledge of:

• Java
• MapReduce
• JUnit
• MRUnit
• Hive and Pig

I am a Happy Hadooper because this profile is interesting and promises professional growth.

I am a system administrator, specializing in Hadoop, therefore known as Hadoop Administrator. My roles and responsibilities include administration of Hadoop infrastructure. I team up with Hadoop developers and testers in order to deploy hardware and software environments.

Let me compile the roles and responsibilities of a Hadoop Administrator:

• Managing cluster connectivity and security
• Removing nodes with the help of tools such as Cloudera Manager Enterprise and Dell Open Manage
• Managing HDFS maintenance and support
• Working closely with data scientists and business application teams to provide data
• Setting up Linux Users and ensuring Hive, Pig, HDFS, and MapReduce access to users.
• Reviewing Hadoop log files and monitoring file system
• Escalating the final product to the vendors

I am skilled in:

• Linux
• Oozie, HCatalog, Hive
• HBase, Pig, Mahout
• Deployment tools: Puppet, Chef, Linux Scripting
• Deploying Hadoop Cluster and adding and removing nodes
• I have knowledge of troubleshooting, bottlenecks, storage, and networks

I am Happy with my profile. 
I am happy because I have a steady career with a handsome salary.

I analyze, manage, and streamline complicated data sets. I am responsible for devising tools to enhance the information flow to the organizations for business benefits. I analyse data coming from varied sources to help business houses derive business intelligence so that they can take intelligent decisions and make good business policies.

Have a look at my roles and responsibilities:

• Extract relevant data for analysis
• Work on data modeling standards
• Create predictive models for deriving business intelligence
• Work on data mining architectures and data analysis methodologies
• Analyzing business requirements and developing big data analytics projects accordingly

My skill set is as follows:

• Mathematics, Statistics, and Programming
• Data extraction and manipulation, and data analytics
• Pig, Hive, SQL
• SAS and R

I am Happy because I have the “sexiest job of the 21st century!”

Why Hadoop still make sense

 

Reasons Hadoop still make sense

Hadoop has moved to the cloud now. As the widespread benefits are for everyone to see, we will see how it enhances the power of Hadoop.

• Lowering the cost of innovation

Running Hadoop on the cloud makes sense for relevant reasons as performing any other software contributing on the cloud. 

Companies are still testing the waters with Hadoop, the less capacity investment in the cloud is a no-brainer. 

The cloud plays an important role in making sense for a quick, one-time help case including big data computing.

• Procuring large-scale resources quickly

The point above of quick resource procurement needs some elaboration. 

Hadoop platform was inspired by the vision of linear storage and compute using commodity hardware a reality. 

On internet google, who always managed at web-scale, they know that there will be a demand for running on more hardware resources. 

Hardware had to be acquired on their own.

• Handling Batch Workloads Efficiently

Hadoop is a batch-oriented system, where you can schedule jobs and have an incoming data feed. 

Enterprises are collecting activity data from web server logs and consume this collected data into an analytic function on the Hadoop.

The capacity to compute resources of a Hadoop cluster varies based on the timings of these scheduled runs or rate of incoming data.  

A fixed capacity Hadoop cluster built on physical machines is always on whether it is used or not – consuming power, leased space, etc. and incurring a cost.

• Handling Variable Resource Requirements

Not all Hadoop jobs are created equal. 

Some Hadoop jobs require more computer resources, some of them needs more memory, and some others demand a lot of I/O bandwidth. 

Normally, a physical Hadoop cluster is built of homogeneous machines, usually, they are large enough to handle the biggest work.

• Running Closer to the Data

Today businesses are moving their services to the cloud, it follows that data starts living on the cloud. 

• Simplifying Hadoop Operations

As the cluster merger happens in the business, there is one thing which gets lost is the segregation of resources for different sets of customers. 

As all of the client's jobs get grouped up in a shared cluster, the authority of the cluster gets started to deal with multi-tenancy problems such as clients jobs interfering with each other, varied security constraints etc.

Conclusion:

It is said that the next decade will be going to be dominated by Big-data wherein all the companies will be using the data available to them to learn about their company’s ecosystem and improving fallback.

Learn Big Data with ETLHive.

How Netflix Uses Big Data to Drive Success

Netflix has over 100 million subscribers in the past nine years since its founding; the online streaming platform Netflix has turned the film and television industry on its head. With that comes a huge amount of data they can analyze to improve the user experience. Big Data has helped Netflix to become the king in online streams.

If you have a Netflix subscription understands the process of finding a movie or TV show to watch. For Netflix user it has unique sets of options with Netflix, putting a lot of effort into ensuring you find something to watch quickly. This differentiates Netflix from other online streams.

Let’s see how Big Data helps Netflix

Big data helps Netflix to decide which programs will be of interest to the user and the endorsement of the system actually influences 80% of the content that user watches on Netflix.

The Netflix even gave away a $1 million prize since it has been founded to the group who came up with the best algorithm for anticipating how customers would like a movie based on previous ratings.

Algorithms help Netflix to save $1 billion a year in value from customer retention it is an eye-opening figure in the entertainment industry.

Finding the next smash-hit series with Big Data

Netflix has arranged itself as a content designer, not just a distributor for movie studios and other networks.

Big Data enabled Netflix to spend $100 million on 26 episodes of the House of Cards, as they were confident the show could be marketed successfully to their audience.

They know it would appeal to the fans of the originals British “House of cards” and the built-in fan bases for director David Fincher and actor Kevin Spacey.

The ultimate strategy which Netflix hopes to improve in the number of hours those customers spends using its service.

Big Data in Personalized video ranker

Netflix collects information for each member profile in a personalized way.

The same genre now for each member has an entirely different selection of videos.

These rows are based on genre, with headers like “Suspenseful Movies”.

Big Data algorithm orders Netflix’s catalog according to the user tastes and the resulting order is used to select the order of videos in a particular genre and in the other rows as well.

Big Data algorithm in Top-N video ranker

This algorithm of Big Data analyzes the best few personalized recommendations in the entire catalog for each member.

It focuses on the top of the rankings, unlike PVR which looks at the ranking for the entire catalog.

Big data in Trending Now

In “Trending Now” Big Data hones in on short-term trends, spanning anywhere from a few minutes to a few days.

It takes into account unique personalized metrics and teases out two types of trends – those that repeat at regular intervals, such as an uptick of romantic films around Valentine’s Day, and one-off events, like a hurricane, that drive sudden interest in documentaries about natural disasters.

Big Data in Continue Watching

“Continue Watching” is the list of shows the user has not completed watching.

Big Data sorts the recently viewed titles based on Netflix’s best estimate of whether you intend to resume watching, or if you’re just going to abandon the title.

Big Data considers factors such as time elapsed since viewing, whether you stopped watching in the middle, beginning, or end, or whether different titles have been viewed since.

Big Data algorithm in Video-video similarity

Finally, the “Because You Watched” row anchors its recommendations to a single video. This video-video similarity Big Data algorithm, as it is called, helps drive this list.

Big Data algorithm that generates a ranked list of videos for every video in Netflix’s entire catalog.

But even though the ranking itself is not personalized, the anchor video which makes it to the homepage is, as is the subset of BYW videos recommended.

Conclusion

Netflix is just one example of how Big Data helps us make simple viewing choices and how Big Data has influenced the entertainment industry in a big way. The applications of Big Data are many fold.

Want to know how you can reap the benefits of Big Data and Data Analytics?

Contact us at ETLHive today to know how it can drive your business!

Big Data & healthcare

Do you know Big Data helps in healthcare

The healthcare industry may be going through a seemingly endless period of flux, but there are a few unchanging truths about big data analytics that can help guide executive leaders through troubled times.

What is big data in Healthcare?

Big data analytics is not new in healthcare industry and it has lots of positive and life saving results.
Big data analytics prefers to the wide quantity of data created by the digitization of everything, that gets merged and analyzed by some specific technologies.
useful to healthcare, it will use precise health information of  people (or of a specific individual) and can sure that it helps to prevent epidemics, cure disease, cut down costs, etc.

Why there is a Need of Big Data Analytics in Healthcare?

There are big opportunities for big data in healthcare industry, because of increasing costs of hospitality in nations like United States. According to the report, healthcare costs currently are 17.6 percent of  Gross Domestic Product(GDP) —almost $600 billion  much ahead than the expected measure for a nation of the United States’s size and wealth.
In the earlier strategy, healthcare contributors was not having any source or motive to communicate patient information with expert and consult them, which made it tougher to apply the power of analytics.
Now many of them are getting paid based on patient end results, they have a proper financial motive to communicate information which will help to improve the lives of patients whereas the cutting costs for insurance companies.

1) Patients predictions for an improved Staffing

 In one hospital manager faces so many things like: If you put on too many workers, you run the risk of having unnecessary labor costs add up. If suppose you put very less workers, you will experience poor customer service result – which leads to a problem for patients in that industry.
Big data helps to resolve this problem, some hospitals using data from a variety of sources to come up with daily and hourly predications of how many patients are excepted to be a each hospital.

2) Electronic Health Records (EHRs)

It’s the broadest application of big data in hospital and medicine. Every patient that comes to hospital has its own digital report which includes populations, medical record, allergies, laboratory test results etc.
Through secured data systems records are shared to each other and are opened for providers from both private and public sector.
 Every report is collectively of one updatable file, which means changes can be implemented over time whenever doctor wants to make changes and can reduce paperwork and no danger of data replication.

3. Big Data helps patients come up with a treatment plan
 

Big data in healthcare will help you for strategic planning and to superior insights into public motivations.
Healthcare managers can inspect body check-up outcomes among people in various demographic groups and can identify that what are the things that discourage people from taking up treatment.

4. Big Data can Cure Cancer

Large amounts of data can be used by medical researchers on therapy plans and improvement rates of cancer patients. This will help to discover trends and treatments which have the maximum rates of success in the real world.
For e.g, researchers can study tumor samples in biobanks that are merged up with patient treatment records.
 Using this data, researchers can see things like how certain mutations and cancer proteins interact with different treatments and find trends that will lead to better patient outcomes.

Conclusion:

Bigdata Analytics in healthcare is coming with great results and promising this field for providing insight from very large data sets and doing best practices with positive results while reducing costs.
In the current day and age, we cannot ignore the potential of Big Data and there are many companies and industries that need Big Data professionals.
Contact us at https://www.etlhive.com and learn Big Data today.
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Why is Big Data analytics is important?

Why is Big Data analytics is important?

• Data, in today’s business and technology world, is basic. The Big Data technologies are driving to analyze this data for gaining vision that can help in making strategic decisions. 
• The big data technology evolved at the beginning of the 21^st century, and every technology giant is now making use of it.
•  Big Data refers to massive and numerous data sets that may be structured or unstructured. This massive amount of data is produced every day by businesses and users. 
• Big Data analytics is the process of investigating the large data sets to underline insights and patterns. The Data analytics field in itself is massive.

• The reason why Big data analytics important

• Cost reduction. Big data analytics bring serious cost advantages when it comes to storing large amounts of data and they can identify more efficient ways of doing business.
• Faster, better decision making. The speed of big data analytics, mixed with the capability to analyze new sources of data, businesses are able to analyze information immediately and make decisions based on what they’ve learned.
• New products and services. With the capability to meter customer needs and satisfaction through analytics comes the power to give customers what they want. Big data analytics helps more companies to create new products to meet customers’ needs.

• Who uses big data analytics?

Think of a business that depends on quick decisions to stay ambitious, and most likely big data analytics is involved in making that business grow. Here’s how different types of organizations might use big data analytics:

• Healthcare

• Big data analytics maintain Patient records, health plans; insurance information and other types of information can be difficult to manage but are full of key insights once big data analytics are applied.
• With the help of big data analytics, it analyzes large amounts of information both structured and unstructured. So that health care providers can provide lifesaving diagnoses or treatment options almost immediately.

• Government

• Many agencies use big data analytics this technology plan operations while giving the agency a more comprehensive view of criminal activity.
• Data analytics help them with some trouble in law enforcement agencies, which are struggling to keep crime rates down with relative resources. 

• Conclusion

The importance of big data analytics leads to deep struggle and increased demand for big data professionals. Data analytics help in analyzing the value chain of business and gain vision. To know more or to increase your business give a visit to https://www.etlhive.com/best-bigdata-hadoop-training-institute-in-pune.