Computer science Questions

 

Definition

Data analytics is a system that analyzes raw data to conclude that information. The system is computerized into automated methods and processes that work over raw data for human use (Franklin, 2013). Data analytics helps the organization optimize its performance.

Components of data analytics

Data acquisition is the process of measuring the physical or electrical variations like temperature, pressure, currents, voltage, and sound fluctuation in a computer system.

Data security is a component concerned with monitoring and detecting malicious activities within the organization's networks, essential for rising security threats (Franklin, 2013). Data security analyzes a collection of new generation security techniques that uses various correlation algorithms to detect anomalies.

Data storage is the retention of data using machines and other devices. Data retention and analysis are performed using specific technology, which makes it accessible for future use.

Data visualization is a component that graphically represents info gained through data analysis. It assists in the presentation of data effectively, making output interactive and easier to understand (Franklin, 2013). The techniques used are tables, graphs, maps, dashboards, and info graphics.

Data optimization policies function to reduce the database system response time to increase the efficiency speed on how data is retrieved. The analysts use the optimizations method to improve the server's data access means.

Categories of data analytics

There are four sorts of data analytics, including the following:

Descriptive analytics answers the question of what occurred. For instance, a company analyzes monthly revenue and income per product and the total quantity of products made per month; it makes it easier for a manufacturer to answer a series of what occurred (Russom, 2011). This analytics manipulates raw data from many data sources to give a valuable understanding of the past.

Diagnostic analytics uses past data to give a depth understanding of a specific issue. At the same time, an organization has detailed information at its disposal (Russom, 2011). It is where the historical data is compared with other data to answer why something happened.

Predictive analytics tells what is likely to take place in the future (Russom, 2011). It uses the finding of descriptive and diagnostic to detect expectations and predict future technologies that make it a valuable technique for forecasting.

Prescriptive analytics is the data analytics used to prescribe what to be done to eliminate any future issue or take advantage of promising technologies.

Data management

Data management is the process of gathering, storing, and using data safely, competently, and cost-effectively. Data management targets to assist the users link things to enhance the use of data within the constraints of policies and rules set. In a data analytics system, managing digital data consists of many tasks, policies, and practices (Slade & Prinsloo, 2013). Data is stored in multiple clouds and premises; there is use data privacy and security, and also information is created and accessible to various speculations. The data is maintained by organizing and storing categorically to ensure the users quickly access it. The analysts ensure the data kept are up to date and placed in a central database to enhance easy access for use.

 Ethical considerations

In data analytics, the ethical issue considered on data is confidentiality. That means that any identifying information isn't available to or accessed by any person but the authorized personnel. Confidentiality also ensures that identified info is excluded from any reports or published files. The participants' names and identities are always made private when data is displayed after analytics (Slade & Prinsloo, 2013). The other ethical consideration is informed consent, where the participants are made aware of the project's purpose. It is an issue that participants need to know to enable them to decide whether they will take part in the evaluation.

Outline

Topic: Computer science Questions

The paper covers the following

Definition

• Data analytics is a system that analyzes raw data to conclude that info. The system is computerized into automated methods and processes that work over raw data for human use (Franklin, 2013). Data analytics helps the organization optimize its performance.

Components of data analytics

• Data acquisition is the process of measuring the physical or electrical variations like temperature, pressure, currents, voltage, and sound fluctuation in a computer system.
• Data security is a component concerned with monitoring and detecting malicious activities within the organization's networks, essential for rising security threats (Franklin, 2013). Data security analyzes a collection of new generation security techniques that uses various correlation algorithms to detect anomalies.

Categories of data analytics

• There are four sorts of data analytics, including the following:

Descriptive analytics answers the question of what occurred. For instance, a company analyzes monthly revenue and income per product and the total quantity of products made per month; it makes it easier for a manufacturer to answer a series of what occurred (Russom, 2011). This analytics manipulates raw data from many data sources to give a valuable understanding of the past.

• Diagnostic analytics uses past data to give a depth understanding of a specific issue. At the same time, an organization has detailed information at its disposal (Russom, 2011). It is where the historical data is compared with other data to answer why something happened.

Data management

• Data management is the process of gathering, storing, and using data safely, competently, and cost-effectively. Data management targets to assist the users link things to enhance the use of data within the constraints of policies and rules set. In a data analytics system, managing digital data consists of many tasks, policies, and practices (Slade & Prinsloo, 2013).
• Data is stored in multiple clouds and premises; there is use data privacy and security, and also information is created and accessible to various speculations. The data is maintained by organizing and storing categorically to ensure the users quickly access it. The analysts ensure the data kept are up to date and placed in a central database to enhance easy access for use.

 Ethical considerations

• In data analytics, the ethical issue considered on data is confidentiality. That means that any identifying information isn't available to or accessed by any person but the authorized personnel. Confidentiality also ensures that identified info is excluded from any reports or published files. The participants' names and identities are always made private when data is displayed after analytics (Slade & Prinsloo, 2013).
•  The other ethical consideration is informed consent, where the participants are made aware of the project's purpose. It is an issue that participants need to know to enable them to decide whether they will take part in the evaluation.