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The decoding of a message is how an audience member is able to understand, and interpret the message. It is a process of interpretation and translation of coded information into a comprehensible form. The audience is trying to reconstruct the idea by giving meanings to symbols and by interpreting messages as a whole.
Used to spot trends and make sense of data. This type of visual is more common with large and complex data where the dataset is somewhat unknown and the task is open-ended. everyday data-visualisation (data-driven & declarative). [61] The most common and simple type of visualisation used for affirming and setting context.
Analytics is the systematic computational analysis of data or statistics. [1] It is used for the discovery, interpretation, and communication of meaningful patterns in data, which also falls under and directly relates to the umbrella term, data science. [2] Analytics also entails applying data patterns toward effective decision-making.
Sensemaking is an active two-way process of fitting data into a frame (mental model) and fitting a frame around the data. Neither data nor frame comes first; data evoke frames and frames select and connect data. When there is no adequate fit, the data may be reconsidered or an existing frame may be revised.
Machine perception is the capability of a computer system to interpret data in a manner that is similar to the way humans use their senses to relate to the world around them. [1] [2] [3] The basic method that the computers take in and respond to their environment is through the attached hardware.
Data literacy is the ability to read, understand, create, and communicate data as information. Much like literacy as a general concept, data literacy focuses on the competencies involved in working with data. [1] It is, however, not similar to the ability to read text since it requires certain skills involving reading and understanding data. [2]
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Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. [2] In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. [3]