In the previous articles, we have discussed how big data can help SMEs and some of its use cases. This article is the top main technologies that enable big data analytics for SMEs.
Rather than depending on trial and error, companies have begun to use an optimized technique for the optimal distribution of resources to sculpt the path of a company’s growth. Incorporating big data analysis techniques has proven to be the most effective approach to implementation. Large organizations’ business data is just too complicated to be processed by traditional data processing systems over long periods of time. There are better techniques to extract relevant information that can aid in appropriate decision-making and reveal patterns in data that appears to be random. These methods are at the heart of big data analytics.
Big data analytics technology is made up of a variety of methodologies and processing methods. What makes them useful is how businesses employ them collectively to achieve relevant results for strategy management and implementation. Here’s a quick rundown of the big data technologies adopted by small and medium business as well as big companies.
Predictive analytics is one of the most important tools for businesses to prevent risks in decision-makeing. By processing large dataset, predictive analytics hardware and software solutions can be used to uncover, evaluate and apply predicted scenarios.
These NoSQL Databases are used to manage data across a large number of storage nodes in a reliable and efficient manner. Data is stored in NoSQL databases as relational database tables, JSON docs, or key-value pairs.
Data that an organization must process may be kept in a variety of formats and on numerous platforms. Filtering, compilation, and analysis of such vast data are all made easier by stream analytics software. External data sources can also be connected to and integrated into the application flow using stream analytics.
It enables applications to get data without enforcing technical constraints such as data formats, data location, and so on. Data virtualization is a big data technology that is utilized by Apache Hadoop and other distributed data stores allowing real-time or near real-time access to data stored on diverse platforms.