Companies have started adopting an optimised method for the optimal distribution of resources to carve the path of a company’s growth rather than relying on a trial and error method. The best method of implementation has been incorporating techniques of big data analysis. The business data acquired by large corporations over large periods of time is too complex to be processed by conventional data processing applications. There are better ways to extract useful information which can support proper decision making and help uncover patterns in an otherwise random looking data. These techniques form the core of big data analytics. There are many ways in which small and medium businesses are leveraging big data to obtain the best possible outcomes for their firms.
The big data analytics technology is a combination of several techniques and processing methods. What makes them effective is their collective use by enterprises to obtain relevant results for strategic management and implementation. Here is a brief on the big data technologies used by both small enterprises and large-scale corporations.
1) Predictive Analytics
One of the prime tools for businesses to avoid risks in decision making, predictive analytics can help businesses. Predictive analytics hardware and software solutions can be utilized for discovery, evaluation, and deployment of predictive scenarios by processing big data.
2) NoSQL Databases
These databases are utilized for reliable and efficient data management across a scalable number of storage nodes. NoSQL databases store data as relational database tables, JSON docs or key-value pairings.
3) Knowledge Discovery Tools
These are tools that allow businesses to mine big data (structured and unstructured) which is stored in multiple sources. These sources can be different file systems, APIs, DBMS or similar platforms. With search and knowledge discovery tools, businesses can isolate and utilize the information to their benefit.