3 Latest Trends In Big Data You Should Know About

Over the last few years, big data has become an astute idea in almost all important technical terms. Because of how technology has evolved throughout the years, analyzing big data sets is now possible, allowing big data to flourish when it comes to applications. Organizations and huge companies are leveraging on this technology, continually improving their data analytics and platforms. 

Big data allows concepts like consumer behavior to be comprehensive and measurable. It has assisted the progress of inductive reasoning by creating a controversial data-first inversion of the scientific method. The creation of big data also allowed many companies to take advantage of analytics, allowing even non-tech employees to have access and take advantage of data-driven insights. 

According to Statista, in 2018, the global big data and business analytics market was valued at US$ 169 billion and is expected to grow at US$274 in 2022. With this in mind, it is ideal to look at current trends that help the big data market flourish. Below are some of them. 

Data as a service

Data is traditionally stored in data stores, developed to be used by various applications. If SaaS (software as a service) is increasingly gaining popularity, DaaS is just starting. DaaS works the same way as SaaS applications. It uses cloud technology, allowing users and applications with on-demand access to data without depending on where the applications or users may be. Data as a service is one of the booming trends in big data analytics and aims to deliver accessible data, making it easier for analysts to obtain and review data to help businesses. 

Predictive analytics

One of the most used big data applications is predictive analytics, which has been a fundamental approach for companies to become competitive in their industry. Not only that companies use it to their advantage, but it has also been offered at a consumer level so more and more people can take advantage of this innovative technology. For example, predictive analytics has been used in the financial industry, particularly with trading investments. 

One company that leverages big data analytics is Globalytics Tech Research and has created proprietary software for Tracking, Analysis, and Risk Assessment called the STAR System. This system was founded on ideology to capitalize on various innovative technologies such as artificial intelligence (AI), data analytics, and business intelligence (BI) to precisely predict future outcomes in the fields of stocks, commodities, forex, blockchain, and cryptocurrency, with a near perfect accuracy rate.  

In general, predictive analytics is a trend in big data that can predict events that may occur in the future. This strategy is extremely efficient in correcting analyzed assembled data to predict market outcomes and customer response. This enables consumers and organizations to define any steps they need to take in the future. 

Natural Language Processing

Natural Language Processing (NLP) exists through artificial intelligence and works to develop communication and understanding between computers and humans. The objective of this innovative technology is to read and decode the meaning of human language. NLP is mostly based on machine learning, and it is used to develop word processor applications or translating software. 

Natural Language Processing Techniques require algorithms to recognize and obtain the necessary data from each sentence by applying grammar rules. Two techniques are most commonly used in natural language processing: syntactic and semantic analysis. The syntactic analysis takes care of sentence structure and grammatical issues, while semantic analysis handles the meaning of the data or text. 


Technology is continually evolving, and new technologies in big data analytics are changing. This is why businesses and even consumers should be aware of these trends and how they can stay ahead of their competitors. By leveraging these trends, organizations can fully realize the potential of big data and what it has to offer. 

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