Big Data is aimed to handle a huge amount of data. Usually, the main purpose is identifying the main questions to make a difference. These questions serve for further reporting and exploration. Moreover, big data helps to involve analytics into the business processes.
These are Big Data functions:
- Gather and store big amounts of data efficiently.
- Dissect the data so that the company may capture a great understanding of customer expectations and what needs to be improved.
- Collect the data and maintain the analysis directly. This is especially important in a secure fashion that deals with privacy regulations.
- Decrease the delays and latency.
Big data became a buzzword now: many people talk about it but not all of them know exactly what it is. However, it has changed our everyday life. Big data made us smarter and helped to speed up processes by structuring the data. So, now its easier to make use of it. Big data offers new valuable insights for the better decisions.
Business Intelligence is the collecting of software, systems and products which may import big data streams and apply them to create meaningful data for business use. BI involves deep analysis of raw data and then companies’ present information in an easy-to-consume way based on authentic real-time facts. Data mining for business intelligence works this way: it captures data, analyzes it from various perspectives or dimensions, and creates a summary. Technically, data mining requires searching correlations in big relational databases.
These are key features of it:
- Capture, transform and upload data as a part of centralized data management.
- Keep and handle the data in a database system.
- Visualize the data by the graphs or tables.
- Dissect the data by application software.
- But most importantly, deliver data access to the companies.
- Actually, this is a meeting point between scientists and businessmen. It helps to save money and achieve greater goals. Nowadays, data-mining tools are the essential part of risk management and making decisions.