Big Data Trends: As big data evolution from a departmental focus to become more customer-fed and business-led, then the focus on increasing the complexity of analytics continues. Using emerging big data trends to stay ahead of the competition hugely based on business ability. From Internet of Things to Predictive Analysis, let’s know some emerging trends in Big Data Projects.

Emerging Trends in Big Data Projects

Edge Computing: It is one of the latest trends in big data that increases the efficiency and speed of the big data processing. In that case, the entire processing of data occurs at the data source in the fog layer or data center. Mostly, this can hugely attribute to the speed of the streaming network media.

Open Source Technology: In this recent days, only seeing more widespread adoption of open source technologies with startups and organizations getting the wins. As well as, free data and software tools are expanding in the open source world, and the GNU’s analytical language R has been seeing the lot of new adoptions.

Quantum Computing: Technology companies such as Google, Intel, Microsoft and IBM are in a race to beat against each other to develop the first quantum computer. This trend can sure to take off. As soon as one of these companies accomplishes the goal. As well as, it allows seemless encryption, data prediction, problem solving with complicated issues, increased financial modeling and real conversations.

Predictive Analysis: According to Gartner, data analytics is in the third wave of development and it is a great trend. Most organizations are continue to shift growing masses of data via automated analytic algorithmic systems. More than 50 percent of data analyst jobs are expected to be automated by artificial intelligence.

Dark Data: It is the data which is gathered but not used in any analytical system. Many businesses may not have an aware of their dark data. But it is becoming increasingly aware that this data can become most valuable in future. Therefore, more companies are beginning to gather data and keep dark data, as opposed to disposing of it.

Final Thoughts

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