Typically, Machine Learning is used to solve business problems in various sectors and areas where different algorithms are applied.
Read More »We often wonder where Big Data is applied and we can assume a great relevance of Big Data for business. This explains the current great interest of Big Data by companies, which is actually becoming the main driving force in this technological domain.
► You may be interested in: Big Data applied to business
We note that the 'revolution' from Big Data is occurring in different domains of human activity enhanced by significant growth in computer power, ubiquitous availability of computing and storage resources, and increased production of digital content. This creates a variety of source sources and the use of Big Data.
Science has traditionally faced challenges in handling a large volume of data in complex scientific research experiments, which also involves extensive cooperation between distributed groups of individual scientists and research organizations.
Scientific research typically involves the collection of data in passive observation or active experiments aimed at verifying one or another scientific hypothesis. Scientific research and discovery methods are typically based on the initial hypothesis and a model that can be refined based on the data collected.
The refined model may lead to a new, more advanced and accurate experiment and/or re-evaluation of previous data. The future Big Data and data science infrastructure needs to support all data management operations and processes by also providing access to data and facilities to collaborating researchers.
In addition to the traditional issues of access control and data security, security services must ensure a secure and reliable environment for the investigator to conduct his or her investigation.
One sector where Big Data is applied is in business. Private companies typically do not share data or expertise. When dealing with data, companies will always try to maintain control over their information sources.
They can use third-party shared facilities, such as clouds or specialized applications, but special measures must be taken to ensure workspace security and data protection, including encryption of inbound/outbound data.
The Big Data in the industry is related to the control of processes and complex technological objects or installations. Computer-aided manufacturing produces a large amount of data that, in general, must be stored or retained to enable quality control or effective diagnosis in case of failure or blockage.
In many industrial applications there is a need for collaboration or interaction of many workers.
And the last sector where Big Data is applied is in society. The rise of Big Data is closely related to the social data revolution that provided the initial motivation to develop large-scale services, global infrastructure and high-performance analytical tools, producing a large amount of data themselves.
A clear example is social networks, which are widely used to collect personal information and provide better profiled personal services, from personal search advice to precisely targeted advertisements and campaigns.
► You may be interested in: The 5 Challenges of Big Data in Machine Learning
Typically, Machine Learning is used to solve business problems in various sectors and areas where different algorithms are applied.
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