The big data bubble began to explode, and reasonable developments in the applications of the big data world are anticipated in the upcoming year. Many of us now know more than Hadoop, Spark, NO-SQL, Hive, Cloud, etc. We know that every month there are at least 20 NO-SQL databases and several other Big Data technology. What are the upcoming prospects for these Big Data technologies? Which big data tools will bring immense advantages for you?
Big Data Technology
Big data is a unique indicator of large amounts of data, and it is rapidly growing in terms of size and time. Big data technology can be defined as tools used to analyze, process, and extract data from various complex data that has never been managed traditionally.
Let’s take a look at the top five big data technologies in the IT industry:
Hadoop EcoSystem
Hadoop Framework was evolved to store and process data using a simple programming model in the distributed data processing environment. Data can be stored and analyzed on various high-speed and low-cost machines. Because of their data storage needs last year, companies have adopted Hadoop extensively as Big Data Technologies. In the coming year, too, the trend appears to continue and to grow. It is most likely that companies that have not explored Hadoop to date will see its benefits and applications.
Artificial Intelligence
Artificial Intelligence is the breadth of computer technology dedicated to the development of intelligent machines that perform various tasks that usually require human understanding. Artificial intelligence is rapidly evolving from the Apple Siri autonomous machine. The interdisciplinary science field is considering a category of methods, including the development of machine learning, and fundamentally change many technology industries by deep learning. Artificial intelligence is revolutionizing big data technology.
NoSQL Database
NoSQL contains a wide range of Big Data technologies developed to design modern applications in its database. It displays a non-SQL or non-relation database that use to gain and recover data. They use real-time in web and big data analysis. It stores unstructured data and provides performance and flexibility while addressing different data kinds, such as MongoDB, Redis, and Cassandra. It offers design integrity, facilitates horizontal scaling and control over a range of devices. It uses different database structures than those used to perform NoSQL calculations by default.
R programming
R is one of open source programming and big data languages. Free software for statistical computing, visualization, and unified development environments has been widely used, such as Eclipse and Visual Studio. According to experts, it is the world’s leading language. It is also extensively used in statistical software development, especially data analysis.
Data Lakes
Data Lakes represents aggregated structured and unstructured data storage of all data formats at all levels. Data can be stored as-is and converts to structured data during data accumulation. Supports analysis in the form of several data types. It’s time to reduce the business impact of dashboards on data visualization and big data transformation.
This big data technology promotes business growth by understanding and attracting customers, maintaining productivity, maintaining equipment health, and making family decisions to help companies deal with better business growth opportunities.
