Global computing depends on sensors to ensure that information systems have input data that can be tied to algorithms or functions to allow specific actions to get instigated. For instance, in an e-commerce warehouse, a sensor would be used to direct an ordered item from storage to the packaging section. It means that when an order for a particular product gets made, it can be automatically shifted out of storage to the packaging section to be packaged and sent out to the buyer.
What We’ll Discuss On This Article:
- Computer Networks
- Data Storage
- Cluster Computer Systems
- Cloud Computing Facilities
- Data Analysis Algorithms
Computer networks are the backbone of interconnectivity for global computing and big data. They allow computers to be connected regardless of their geographical locations allowing for access to services and data. This data can get fed into big-data systems for analysis enabling organizations to find meaningful patterns in data. This information can then get used to complement the organization’s operations and to bolster its product and service offerings.
Data storage technologies allow global computing and big data systems access to and facilitation for adequate and reliable data storage mechanisms. It means that these systems can store vast amounts of operational or historical data that can get utilized for forecasting and business intelligence. Big data can get employed as a tool to draw business intelligence from meaningless and jumbled data.
Cluster computer systems are interconnected computers that work as a single entity. These are crucial in that they standardize operations and reduce the costs of performing business-related activities. For instance, they allow for software installation in the entire system while necessitating only a single copy of the software’s enterprise version. It makes it easier and inexpensive to install needed software as compared to doing individual installations in all computers in the organization.
Cloud computing is revolutionary when it comes to global computing and big data. Through such technologies, organizations can outsource infrastructure, software, storage, and platforms from cloud computing providers. It means that an organization can create entire systems without needing to have in-house platforms, infrastructure, storage, or software. Additionally, it makes it cheaper to conduct business activities and alleviates security risks as the provider deals with cloud security.
Data analysis algorithms are crucial to how well organizations can draw meaningful data from massive data sets as part of big data. They allow for the automation of processes and procedures and can get configured to instigate actions based on inputs. For instance, for a retailer, the use of algorithms could mean that when inventory is low, the system can alert the procurement department to restock items as part of just-in-time inventory facilitation.
Watch the video below for more on Big Data.