Upcoming Trends in Big Data Analytics for Effective Data Management in the Future

Discover upcoming trends in big data analytics to generate meaningful insights

Big data analysis involves using advanced analytical techniques against very large and diverse sets of big data that include structured, semi-structured and unstructured data, from different sources and in different sizes ranging from terabyte to zettabyte.

Big Data is a term applied to datasets that are larger or larger than the ability of traditional relational databases to capture, manage, and process data with low latency. Big data has one or more of the following characteristics: high volume, high speed, or wide variety. Artificial intelligence (AI), mobile, social networking and the Internet of Things (IoT) are driving data complexity through new forms and sources of data. For example, big data comes from sensors, devices, video / audio, networks, log files, transactional applications, the web and social media – much of it is generated in real time and at massive scale. .

Big data analytics enables analysts, researchers and business users to make better and faster decisions using data that was previously inaccessible or unusable. Businesses can use advanced analytics techniques such as text analytics, machine learning, predictive analytics, data mining, statistics, and natural language processing to gain new insights from previously untapped data sources, independently or with existing business data.

Latest trends in big data analytics

Big Data Analysis Natural Language Processing (NLP) enables users to perform natural human language queries, with written or voice input

Using artificial intelligence and machine learning, augmented analytics offers users a programmed way to find the most important information

Blockchain can improve predictive analytics of big data as it verifies the validity of data, preventing the inclusion of false information in the analysis

Edge computing brings compute to the edge of a network and reduces the number of long distance connections that must occur between a client and a server, making it the latest trend in big data analysis.

Hybrid cloud provides excellent flexibility and more data deployment options by moving processes between private and public clouds

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