We found 45 results that contain "data communications"

Data communications refers to the transmission of this digital data between two or more computers and a computer network or data network is a telecommunications network that allows computers to exchange data. The physical connection between networked computing devices is established using either cable media or wireless media. The best-known computer network is the Internet.

Big data is a collection of large datasets that cannot be processed using traditional computing techniques. Testing of these datasets involves various tools, techniques and frameworks to process. Big data relates to data creation, storage, retrieval and analysis that is remarkable in terms of volume, variety, and velocity. You can learn more about Big Data, Hadoop and Mapreduce here In this tutorial we will learn, Testing Big Data application is more a verification of its data processing rather than testing the individual features of the software product. When it comes to Big data testing, performance and functional testing are the key. In Big data testing QA engineers verify the successful processing of terabytes of data using commodity cluster and other supportive components. It demands a high level of testing skills as the processing is very fast. Processing may be of three types Along with this, data quality is also an important factor in big data testing. Before testing the application, it is necessary to check the quality of data and should be considered as a part of database testing. It involves checking various characteristics like conformity, accuracy, duplication, consistency, validity, data completeness, etc.

Data Science::
Data Science is a comprehensive process that involves preprocessing, analysis, visualization, and prediction. On the other hand, AI is the implementation of a predictive model to forecast future events.
A Data Scientist, on the other hand, helps the company and businesses to make careful data-driven decisions. A Data Scientist is responsible for extracting data using SQL and NoSQL queries, cleaning various anomalies in the data, analyzing the patterns in data, and applying predictive models.

Big data is more than high-volume, high-velocity data. Learn what big data is, why it matters and how it can help you make better decisions every day.

Data Science is a process of extracting, manipulating, visualizing, maintaining data as well as generating predictions.
A Data Scientist is supposed to have knowledge of various data operations as well as machine learning algorithms. Using Data Science, industries are able to extract insights and forecast their performance.

What is communication (and what isn’t it)?
The P21 framework emphasizes effective use of oral, written, and nonverbal communication skills for multiple purposes (e.g., to inform, instruct, motivate, persuade, and share ideas). It also focuses on effective listening, using technology to communicate, and being able to evaluate the effectiveness of communication efforts—all within diverse contexts (adapted from P21). Note that working in partners is a great way to collaborate or build shared understanding but a critical part of communication is sharing with an authentic audience.
REF:What is communication (and what isn’t it)?
The P21 framework emphasizes effective use of oral, written, and nonverbal communication skills for multiple purposes (e.g., to inform, instruct, motivate, persuade, and share ideas). It also focuses on effective listening, using technology to communicate, and being able to evaluate the effectiveness of communication efforts—all within diverse contexts (adapted from P21). Note that working in partners is a great way to collaborate or build shared understanding but a critical part of communication is sharing with an authentic audience.

Machine-generated data is information automatically generated by a computer process, application, or other mechanism without the active intervention of a human. While the term dates back over fifty years,[1] there is some current indecision as to the scope of the term. Monash Research's Curt Monash defines it as "data that was produced entirely by machines OR data that is more about observing humans than recording their choices."[2] Meanwhile, Daniel Abadi, CS Professor at Yale, proposes a narrower definition, "Machine-generated data is data that is generated as a result of a decision of an independent computational agent or a measurement of an event that is not caused by a human action."[3] Regardless of definition differences, both exclude data manually entered by a person.[4] Machine-generated data crosses all industry sectors. Often and increasingly, humans are unaware their actions are generating the data.[

Big data is more than high-volume, high-velocity data. Learn what big data is, why it matters and how it can help you make better decisions every day