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Hadoop in 2017: Bigger, Better, Faster?
Hadoop will stand strong in 2017.Hadoop not only lives in the big data cloud, it embodies the big data cloud. Owned by Apache, Hadoop turns 11 years old in 2017. This open source software provides distributed cloud storage and the ability to process large disparate datasets into actionable insight.
Hadoop not only lives in the big data cloud, it embodies the big data cloud. Owned by Apache, Hadoop turns 11 years old in 2017. This open source software provides distributed cloud storage and the ability to process large disparate datasets into actionable insight.
Hadoop hit a rough patch over the past couple years, and data managers openly questioned the platform’s value as measured against the complexity of implementation. IT pundits are now saying that Hadoop adoption will increase this year, as enterprise organizations begin integrating it with their own software applications in a big push to migrate data to the cloud.
The poll numbers are in, and despite the widely publicized rumors of Hadoop’s demise, tech experts are saying these were actually “alternative facts.” Technology experts are predicting the following Hadoop trends this year:
• Hadoop adoption expanding
According to Market Analysis, Hadoop usage is expected to expand to $16 billion by 2020. Hadoop will hold its place as the default big data platform in 2017.
• Hadoop in the fast lane
CIO predicts Hadoop will gain data warehouse-like speed in 2017. The platform is already scalable, just by virtue of being in the cloud. The Spark overlay will likely be one way that streaming analytics will be applied to Hadoop’s traditional batch mode processing.
• Data Lakes
One important 2017 trend is the realization of how much data we’re capturing. This IoT spawned phenomenon will increase as data managers pool nodes of raw data in “lakes.”
• Machine Learning
The exponential capture of raw data has spawned a push for machine learning automation to streamline and improve actionable analytics. Most pundits suggest ML will increase the efficiency of human data scientists - something that is intriguing when you consider the programmer drought felt in most American industry sectors.
Machine learning is artificial intelligence, and most IT experts suggest that all the hype has come down to three big players this year: IBM Watson, Salesforce Einstein, and Oracle Adaptive Intelligent Applications. Yet as these platforms evolve, it is widely understood that they must have a reliable lake of data to draw from - which is why Hadoop will remain relevant.
• BI from BD
AtScale’s BigData Maturity and Results survey polled 2,550 data professionals in 1,400 companies and 77 countries. The respondents suggested 75% were using or planning to use business intelligence on big data and 97% said they were increasing big data efforts in the first quarter of 2017. The survey also showed Hadoop usage increasing from 64% in 2015 to 73% in 2016.
• Data is going to Hadoop-as-a-Service
CIO confirmed Hadoop utilization rates will increase this year, as enterprise organizations shift their data to the cloud. Citing Yahoo!, Spotify and TrueCar as Hadoop users, CIO suggests even the most traditional businesses will finally leverage cloud platforms. Hadoop responded to this trend last year by implementing Apache Sentry, which integrates role-based authorization to data, needed security, that enterprise-level businesses demand.
What are some of the other trends affecting big data in 2017? How can your enterprise capitalize on these trends? Start the conversation.