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5 Important Trends in Big Data Technologies for 2018

As we all know, it’s just a start of another year, but technology is something that evolving continuously with amazing innovations. It’s the first month of 2018, so, this is a good time to make some predictions on how the new technologies will shape up big data industry.
We saw the upswing of big data in 2017 and the trend will continue to gain traction. Today, the term ‘Big Data’ is associated with a number of big data technologies which have developed through the years. Looking forward to 2018 will be the year of growth of convergence between big data with other technologies. The fastest growth in spending on big data technologies is occurring within banking, healthcare, insurance, securities and investment services, and telecommunications.

A Brief Look at Expected Development in Big Data Technology and Services

Well, most of us are now more than familiar with terms like Hadoop, Spark, NO-SQL, Hive, Cloud etc. We know there are at least 20 NO-SQL databases and a number of other Big Data solutions emerging every month. Here's a rundown of 5 important big data trends we believe is going to make a big splash in the coming months, such as-

·         App-Development: In 2018, we'll see the data-science/app-development community converge on an open AI development framework that wraps a common abstraction layer around modeling tools such as TensorFlow, MXNet, Caffe2, Spark, etc.

·         No Data Silos: It is one of the most important assets that data is not in silos anymore. The surplus of systems of records now feeds into big data lakes which then make it available to anyone within the organization with right credentials.

·         AI Driven Self-Service: More organizations are using artificial intelligence to help a customer find answers to their product, billing or technical question. Deeper integration with Apple Siri, Amazon Echo and Google Home will accelerate this trend soon.

·         Utilization of Legacy: Most organizations are not in a rush to replace legacy systems but they are building new parallel systems which are future ready and can utilize data from legacy systems. The new systems will also add intelligence to the data by mining and deep learning with tools such as Google TensorFlow, R, and Python etc.

·         Cloud solutions will Empower Big Data Solution: Advantages of Hadoop on cloud has already been realized by many organizations and technologies pertaining to the coupling of Big Data technologies like Hadoop, Spark, IOT and cloud is expected to be well in 2018 as well.
Presently, with an increase in adoption of smart services big data analytics is expected to allow smart technological capabilities to be incorporated in enterprise solutions.

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