What are big data and knowledge management? Large-scale data analysis is gaining importance in every business function. Large data has many advantages. It makes businesses more efficient by providing information that enables quick decision making. It helps in improving product quality by collecting, collating and analyzing large sets of data. Knowledge management deals with the process of collecting, managing and delivering knowledge to users.
Knowledge is the product of human effort and it can be measured, aggregated and shared very efficiently. Knowledge can be used to make decisions about product design, services and business strategy. In a nutshell, big data and knowledge management refer to the combined concept of large-scale data analysis, automated data management and knowledge delivery. Data is one of the important ingredients of knowledge.
Knowledge must be accessed, used and acted upon quickly to get the most advantage from it. This requires a highly interactive process between analysts and users. Knowledge can be made available through online databases that allow users to access it from any place at any time. It helps in improving knowledge and at the same time, this also allows the employees to gain more skills and make use of the new knowledge for their work. Managed services and products that are developed using information technology can make use of such knowledge to make better marketing decisions.
Knowledge management systems help in the sharing of information. They help users gain access to large amounts of structured data in a manner similar to a catalogue or a book. The information can be downloaded to the desktop of the user for future reference. Knowledge can also be captured using digital devices such as computers, tablet computers and smartphone. These devices can capture and store information in the form of digital information that can then be retrieved by the users later on.
Information science is one of the fields that have gained a lot from the big data. It uses this information to develop new and improved methods for gathering and organizing data. Experts in this field study the relationships among various types of data, how they are collected and used and what they reveal about people and their behaviors. They also study the social patterns and networks that are formed around specific information and how these networks can be leveraged for good purposes.
Knowledge is also used for business purposes. It is used to solve problems that require quick response. This helps in reducing costs and the risk involved in activities. Some examples of things that fall under this category include product analysis, market research, advertising research and survey methods.
Knowledge is also used in different forms of technologies. Examples include computer vision, which aims at improving the quality of images captured by cameras. It also aims at minimizing the loss of data in case of camera crashes. The main purpose of big data is to gain access to vastly increasing amounts of data. Experts use this information to build better and advanced systems. One example of this is the Google Brain which is an artificial intelligence project that uses large sets of information to analyze them and make intelligent guesses about real-time data.
Experts are constantly trying to come up with machines that can process information even better than humans. With the arrival of greater amounts of data, it has become increasingly difficult to analyze and to collect such data without running the risk of losing it. This is where machine-learning comes in. Machine learning involves the use of computers to automatically and effectively process large amounts of information without any human supervision. Experts who are involved in this field are now working on self-driving cars and self-driving trucks.