1-844-696-6465 (US)        +91 77600 44484        help@dezyre.com

10 Best Hadoop articles from 2015 that you should read

We know that big data professionals are far too busy to searching the net for articles on Hadoop and Big Data which are informative and factually accurate. We have taken the time and listed 10 best Hadoop articles for you. We have created this list of “10 Hadoop articles from 2015 Everyone Must Read” - by choosing articles that contain up-to-date information and are in line with big data trends. After searching thoroughly on the web, we have identified the best 10 Hadoop and big data articles from 2015, that can help the big data learning community gain insights on Apache Hadoop from different perspectives.

Best Hadoop Articles of 2015

Disclaimer: The 10 hadoop-related articles from 2015 listed below are not ranked in order of importance or quality. These blogs represent 10 of the most appreciated hadoop articles on the web according to DeZyre industry experts, that are a must-read for all big data professionals.

Work on Hands on Projects in Big Data and Hadoop

1) Spark vs. Hadoop: Not Enemies, but Sidekicks

All conversations about big data are incomplete without the mention of Spark and Hadoop. Though Spark and Hadoop are considered as competitors in the big data space, the collective agreement is that both technologies complement each other and are better when used together. However, the big “Big Data” question that many companies have is - “Is Spark going to replace Hadoop?”. Most of the professionals who want to pursue a career in big data are now in a dilemma on whether they should learn Hadoop or Spark. This article by Bernard Marr very well compares the two technologies Spark and Hadoop to -

  • Ease the decision making process for companies to choose between Hadoop or Spark for their next big data deployment.
  • It also clears the confusion amongst professionals on whether they should learn only Hadoop or learn both Hadoop and Spark.

To read the complete article, click here

2) How much Java is required to learn Hadoop?

Students/Professionals who are keen on learning Hadoop are often confused with the question - ‘Is Java is a pre-requisite to learn Hadoop?’. The answer to this question is both a YES and NO because it depends on the individuals skills and interest on what they would like to do with Hadoop. If they want to use hadoop tools like Pig and Hive-knowledge of Java Skills is not necessary. On the other hand if they want to use MapReduce they need to have basic Java Knowledge. This article on DeZyre blog very well explains on how much Java knowledge is required to learn Hadoop and when it is not necessity to know Java for Hadoop.

To read the complete article, click here

Activate free course on Java for learning Hadoop!

3)How Big Data Analysis helped increase Walmart’s Sales turnover?

Walmart is a name to reckon with for business success as it is one of the world’s largest retailers when it comes to revenue - operating in multiple countries across the globe. There are several retailers who want to come close to Walmart’s success. The big box retailer Walmart has many interesting lessons powered by big data and hadoop technology that retailers can explore. Walmart tells its customers what to buy and its using its huge collection of data to make it a reality prediction. This case study is a must read to understand how Walmart is investing in big data and hadoop technology, to increase revenue and customer satisfaction.

To read the complete article, click here

4) Hadoop- Whose to Choose

Apache Hadoop ecosystem has several tools and components that exists as individual Apache projects. With rapid growth of Hadoop community, different versions of these components are not completely compatible with other hadoop components. This makes it difficult for organizations to start with open source Hadoop. To simplify working with Hadoop, there are several companies that have bundled hadoop components into their own hadoop distribution which organizations can deploy. Cloudera, MapR and Hortonworks compete in the Hadoop distribution world making it a hard-hitting decision for organizations on which one to choose. This article on Hadoop360 clearly elucidates the differences and compares the 3 popular Hadoop distributions - so that companies can choose the best one based on their business requirements.

To read the complete article, click here

5) Making its Way into the Mainstream, the Hadoop Market is Accelerating

We all know that Hadoop market is not just healthy but is growing at a rapid pace. With positive indicator for enterprise adoption, Hadoop is becoming the de facto standard for enterprise IT landscape. With its impressive growth, most of us are excited to know- What’s next for Hadoop? This article on InsideBIGDATA is an enlightening read - to understand how organizations should move beyond the storage capabilities of Hadoop, by making use of multiple computing nodes to increase the processing power.

For the complete list of big data companies and their salaries- CLICK HERE

To read the complete article, click here

6)Must Read Books for Beginners on Big Data, Hadoop and Apache Spark

If you are looking for suggestions on what books will help you with Hadoop, then this article is a must read for you. Any beginner who is in pursuit of building a lucrative career in big data, will find this article very useful. This article lists the best Hadoop books for beginners and is focussed on those books, that contain basics of big data analytics and MapReduce programming in Hadoop. Big data ecosystem is an ocean of various tools and technologies and takes long time to get trained in Hadoop. Professionals who are beginning their career in big data and hadoop should start with these books to enhance their knowledge on hadoop ecosystem. If you haven’t already read these books, add these Hadoop books to your reading list for 2016.

To read the complete article, click here

7)Hadoop Can't Do That

Organizations always are looking to hire Hadoop developers who can deploy Hadoop and augment the capabilities of Big Data, without replacing their existing data infrastructure. With steep learning curve for Hadoop, developers need to understand, when it makes sense to use Hadoop and when not; what you can expect to achieve using Hadoop and what capabilities hadoop provides for your project requirements. This article is a must read for everyone as it helps understand what Hadoop can and cannot do so that hadoop developers can plan the implementation of the technology accordingly, to make the most of Hadoop capabilities. Having read this article, developers should be able to unlock the complete potential and value of the hadoop framework.

To read the complete article, click here

8) 22 Data Experts Share Their Predictions for 2016

With several emerging big data trends for 2015, the big data industry generated many headlines in 2015.But now since 2015 is over, many people are interested to read about where the accelerating big data industry is heading this new year. The possibilities for the future in the big data industry might have already been written in different tech stories, magazines, news headlines and other renowned publications. It is always exciting to know what lies ahead for Big Data technologies, in 2016, from industry experts, particularly when it is about one of the hottest technology trends. This article on Datafloq is for all the big data enthusiasts who want to know the big data trends for 2016 from experts, along with insights from industry leaders in the big data space.

To read the complete article, click here

9) What are the biggest Hadoop challenges?

The learning curve to gain practical knowledge in successfully deploying Hadoop in production is very steep. No doubt, Hadoop provides enhanced performance to any data oriented business but there are several challenges like choosing Hadoop vendors, hiring the right set of big data talent, handling multiple workloads, etc. This article on Dzone highlights the most common challenges encountered while putting hadoop to work. You definitely will be able to use Hadoop the right way after reading this article.

To read the complete article, click here

10) The Seven Most Common Hadoop and Spark Projects

Big data professionals are often interested to know how technologies like Hadoop, Spark, and Storm are implemented in production, to make the most of an organization’s big data. Most of the big data professionals are of the thought that they are working on some extraordinary Hadoop or Spark project that nobody else is working on - this is just a myth. The implementation of a Hadoop or a Spark project varies from one organization to other; however the main objective is the same. So, next time when you are think you are breaking new ground into Hadoop or Spark–do refer to the article and see if you project falls into one of these categories mentioned in the article “Seven Most Common Hadoop and Spark Projects”. This article on InfoWorld highlights the most common Hadoop and Spark projects that big data professionals are required to implement while working with big data technologies in any organization.

To read the complete article, click here

Feel Free to add your favourite Hadoop-related articles from 2015 in the comments below!

Learn Hadoop Online Now to develop interesting big data applications

 

PREVIOUS

NEXT

Work on hands on projects on Big Data and Hadoop with Industry Professionals