Search results
Results from the WOW.Com Content Network
Big data can include structured, unstructured, or combinations of structured and unstructured data. Big data analysis may integrate raw data from multiple sources. The processing of raw data may also involve transformations of unstructured data to structured data. Other possible characteristics of big data are: [41] Exhaustive
Data ecosystems possess three major characteristics: network, platform, and co-evolution. [1] Network loosely refers to the groups of data and technology developers, providers, and resellers. [ 1 ] The platform, then, is the service, tool or platform that is collaboratively used by the network of actors. [ 1 ]
Industrial big data refers to a large amount of diversified time series generated at a high speed by industrial equipment, [1] known as the Internet of things. [2] The term emerged in 2012 along with the concept of "Industry 4.0”, and refers to big data”, popular in information technology marketing, in that data created by industrial equipment might hold more potential business value. [3]
[4] [5] Data, as a general concept, refers to the fact that some existing information or knowledge is represented or coded in some form suitable for better usage or processing. Advances in computing technologies have led to the advent of big data, which usually refers to very large quantities of data, usually at the petabyte scale. Using ...
Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11] Statistician John Tukey, defined data analysis in 1961, as:
A data lake refers to the storage of a large amount of unstructured and semi data, and is useful due to the increase of big data as it can be stored in such a way that firms can dive into the data lake and pull out what they need at the moment they need it, [3] whereas a data stream can perform real-time analysis on streaming data, and it ...
Given the fairly static yet voluminous nature of machine-generated data, data owners rely on highly scalable tools to process and analyze the resulting dataset. Almost all machine-generated data is unstructured but then derived into a common structure. [4] Typically, these derived structures contain many data points/columns. With these data ...
Defining data quality is difficult due to the many contexts data are used in, as well as the varying perspectives among end users, producers, and custodians of data. [5] From a consumer perspective, data quality is: [5] "data that are fit for use by data consumers" data "meeting or exceeding consumer expectations"