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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.[

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.

A career in Artificial Intelligence requires a strong background in programming, systems analysis, and/or fluency in several computer languages. A bachelor's degree in mathematics, data science, statistics, and computer science can qualify you for entry-level positions in the Artificial Intelligence field.

Artificial Intelligence, also known as AI, and Data Science, has become the two most important sought after technologies in today's time. Many a time, people think of it as the same thing, but they are not the same thing in reality. Artificial Intelligence is used in the field of Data Science for its operations

It is recommended that rising educators visit the same learning environment (and not their own classrooms where they are students) as observers at least two times for at least 40 minutes per visit. These observations will form the source material for demonstrating what the rising educator learned about classroom culture in the micro-credential submission.

This micro-credential is aligned to the following Educators Rising Standards:

I. Understanding the Profession
II. Learning About Students
VII. Engaging in Reflective Practice

Educators Rising Standards Alignment
This micro-credential is aligned to the following Educators Rising Standards:

I. Understanding the Profession
II. Learning About Students
VII. Engaging in Reflective Practice

Management Information Systems is of paramount importance to reach effective decisions in an organization. The literature presented in this study explained the significant role of MIS in the decision-making process enhancement in an organization. MIS is deemed to be an integrated user-machine system that provides information to support operations, management, and decision-making functions at various levels of an organization. Organizations are aware that MIS is a special-purpose system useful for management objectives. The study has highlighted that MIS should be accessible in supplying appropriate and high-quality information from its generation to its users. To MIS, to be vital and effective, a carefully conceived, designed, and executed database should exist to communicate the adaptive decisions.