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Best of 2016: Top 5 Big Data Blogs – It’s All About Hadoop

As we countdown the final days of 2016, we’re taking a look back at our best content this year. So without further ado, here’s a list of the best of Big Data we’ve offered you this year:

#1:  Debunking the Top 5 Myths About Big Data & Hadoop

There are a lot of myths surrounding Hadoop and Big Data. Many of these myths keep good organizations from seeing strong ROI on their analytics. Has your organization fallen into one of these common misconceptions? Read on >

#2:  4 Benefits of Using Apache Kafka in Lieu of AMQP or JMS

Kafka is relatively easy to describe at the highest level, but you have to delve into individual use cases to begin to realize its true benefits. See how you can benefit from using Apache Kafka. Read on >

Download our Hadoop Perspectives for 2017 eBook

#3:  3 Alternatives to MapReduce Programming

While the Java-based MapReduce is both powerful enough to take on Big Data and flexible enough to allow for good progress, the coding is anything other than easy. Fortunately, some of the big names in Big Data have also taken on Hadoop and backed their initiatives with other platforms that accomplish programming without massive teams of expensive, hard-to-find Java programmers. Read on >

#4:  Syncsort Big Data Integration – Streaming and Kafka and Spark, Oh My!

In navigating Big Data integration technology, companies might start to feel like Dorothy in Oz – simply overwhelmed with the complexities of this new world and bewildered by the constantly changing landscape. Get a look into how Syncsort went about making Big Data integration easier for customers as they set out to build DMX/DMX-h 9.0. Read on >

#5:  10 Completely Free Resources for Sharpening Your Skills in Hadoop

Taking on a Big Data initiative isn’t cheap. If you have to add in training costs, the price tag can quickly skyrocket. Or, you can just take advantage of one of the numerous free resources available – because who doesn’t love free stuff? Read on >

BONUS Top eBook of 2016: Best Practices for Hadoop in the Enterprise

After surveying over 250 IT decision-makers, we’ve discovered the hottest compute frameworks and top uses for Hadoop, as well as the biggest benefits and toughest challenges seen during Hadoop implementation. Find out what every business needs to know about Big Data. Read on >

Already tired of 2016? Check out: Hadoop Perspectives for 2017: New Insights as the Market Matures. This eBook summarizes the results of Syncsort’s third annual Hadoop survey, uncovering the trends in data integration to watch for in 2017!

33 comments
  • Big Data hadoop Online Training — February 16, 2017 at 4:28 am

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  • chris — February 21, 2017 at 3:24 am

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  • Hadoop Training In Hyderabad — March 20, 2017 at 8:02 am

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    We at acadgild also write some great articles on big data, hadoop, scala, spark .

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    • Michael Kornspan
      Michael Kornspan — May 1, 2017 at 9:20 am
      In reply to: emergers

      We are glad you found this blog valuable! That’s our goal!

  • kuldeep sharma — July 18, 2017 at 4:43 am

    5th was awesome , as its really help me a lot when i was working on hadoop, thanks a ton.

  • Jasmini — August 8, 2017 at 2:19 am

    Thanks for your contribution, big data is now emerging field.
    Keep sharing such valuable information.

    Thanks a Ton!!!

  • Jasmini — August 8, 2017 at 2:21 am

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    Keep sharing such valuable pieces of information

    Thanks a Ton!!!

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  • Cinth Maria — October 25, 2017 at 7:11 am

    Hey, awesome resources! Thanks.

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    They have excellent curation of the latest tech news on big data analytics, AI, BI and more.

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  • Sundaresh K A — April 9, 2018 at 7:10 am

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  • Heena Malik — April 15, 2018 at 5:11 am

    Privileged to read this informative blog on Hadoop. Commendable efforts to put on research the Hadoop. Please enlighten us with regular updates.

  • owenmorris — April 16, 2018 at 1:35 am

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  • Prince Arora — April 17, 2018 at 3:02 am

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  • Technogeeks — April 25, 2018 at 8:31 am

    Thank you for providing such a great information. Its really a important list for Big Data Hadoop.

    Big Data Analyst

  • Aanchal Iyer — May 15, 2018 at 6:16 am

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