IT Exam Answers

What is a benefit of analyzing data in motion rather than a static data set?

• Critical decisions can be made more quickly.
• The data is more accurate.
• All historical data is used to arrive at a decision.
• The data is more structured.

• Answers Explanation & Hints: A benefit of analyzing data in motion rather than a static data set is that critical decisions can be made more quickly. Analyzing data in motion refers to analyzing data as it is generated or received, rather than analyzing a static data set that has already been collected. Analyzing data in motion allows for real-time insights and decision-making, which is important in many industries where time is of the essence, such as finance, healthcare, and manufacturing. In contrast, analyzing a static data set requires the data to be collected, processed, and then analyzed, which can take time and delay decision-making. Analyzing data in motion allows for quicker response times and more immediate action, which can be critical in situations where decisions need to be made quickly. While analyzing data in motion can provide real-time insights, it is important to note that it may not always be more accurate than analyzing a static data set. In fact, analyzing data in motion can sometimes be less accurate due to issues such as data quality, data integrity, and data latency. The accuracy of the data depends on the quality and reliability of the data sources, as well as the algorithms used to analyze the data.

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1.4.2 Module 1 Quiz – Data Analytic Projects Exam Answers Full 100% | Data Analytics Essentials 2023

What is an example of descriptive data analysis?

• predicted oil price increases
• control of highway traffic signals
• an hourly traffic report for a highway
• a weather forecast description

• Answers Explanation & Hints: An example of descriptive data analysis is an hourly traffic report for a highway. Descriptive analytics refers to the analysis of historical data to gain insights and understand what has happened in the past. In this case, an hourly traffic report for a highway is an example of descriptive data analysis because it provides information about the current state of the system (i.e. the traffic on the highway) based on historical data. The report describes the traffic conditions and provides information about what has happened in the past hour. Predicted oil price increases is an example of predictive analytics, which involves using historical data and statistical models to make predictions about the future. Control of highway traffic signals and weather forecast description are examples of prescriptive analytics, which provides recommendations or actions to take based on the analysis of historical data.

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1.4.2 Module 1 Quiz – Data Analytic Projects Exam Answers Full 100% | Data Analytics Essentials 2023

A large online ordering company collects the sales history of its customers. Using this historical data, the online company sends customized sales advertisements to a specific group of customers. Which data analytics method is being used?

• indicative
• predictive
• descriptive
• prescriptive

• Answers Explanation & Hints: Prescriptive analytics involves the use of advanced analytical techniques and algorithms to make recommendations and predictions about what actions should be taken in the future to optimize business outcomes. It relies on a combination of historical data, current data, and external data sources to provide guidance on what actions to take, and it aims to provide the best possible outcome by considering multiple scenarios and potential decision pathways. In the case of the online ordering company, the use of historical sales data to send customized sales advertisements to a specific group of customers is an example of prescriptive analytics. The company is using this data to prescribe a course of action (sending targeted sales ads) based on an analysis of historical data to improve the outcome (sales revenue) of its business. By analyzing the data and identifying patterns and trends, the company can make recommendations on what actions to take to optimize the outcome.

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1.4.2 Module 1 Quiz – Data Analytic Projects Exam Answers Full 100% | Data Analytics Essentials 2023

A college uses a learning management system (LMS) to host lecture materials and provide access to assignments and assessments. A teacher uses the LMS to check activities completed by students in a particular course. Which data analytics method is being used?

• indicative
• predictive
• descriptive
• prescriptive
• proactive

• Answers Explanation & Hints: The data analytics method being used in this scenario is descriptive. Descriptive analytics refers to the analysis of historical data to gain insights and understand what has happened in the past. In this case, the teacher is using the LMS to check the activities completed by students in a particular course, which is an example of looking at historical data. The teacher is not trying to make predictions or take any action based on this data, but rather simply trying to understand what has happened in the past. Indicative analytics is a type of analytics that provides information about the current state of a system, while predictive analytics uses historical data to make predictions about the future. Prescriptive analytics provides recommendations or actions to take based on the analysis of historical data. Proactive analytics is a term that is not commonly used in data analytics, but it can refer to taking preemptive actions to prevent future problems based on analysis of historical data.

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1.4.2 Module 1 Quiz – Data Analytic Projects Exam Answers Full 100% | Data Analytics Essentials 2023

A college has deployed next-generation analytics. Which question would most likely be answered by next generation analytics that could not be answered by traditional analysis tools?

• Which class has the most sections available?
• What are the 10 most expensive textbooks required in any class?
• Which 100 classes fill the fastest once open enrollment is available for the general population?
• Which teacher had the highest number of students enrolled in classes during the last year?
• Which class sections do students consider the most in the online environment without actually enrolling?
  

  Answers Explanation & Hints: The question that would most likely be answered by next generation analytics that could not be answered by traditional analysis tools is “Which class sections do students consider the most in the online environment without actually enrolling?” Next-generation analytics refers to advanced techniques for data analysis that go beyond traditional methods. In this case, it implies the use of sophisticated algorithms and machine learning models to extract insights from complex data sets. The question about which class sections students consider the most in the online environment without actually enrolling is difficult to answer using traditional analysis tools because it requires analyzing unstructured data such as student reviews, comments, and feedback on social media or other online platforms. Next-generation analytics can process this unstructured data and identify patterns and trends that traditional analysis tools cannot. This type of analysis can help colleges improve their online course offerings, identify areas for improvement, and ultimately enhance the learning experience for their students. The other questions listed can be answered using traditional analysis tools such as data querying, statistical analysis, and data visualization.

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1.4.2 Module 1 Quiz – Data Analytic Projects Exam Answers Full 100% | Data Analytics Essentials 2023

What is the correct order of the stages in the data pipeline?

• Ingestion, Transformation, Analysis, Storage
• Ingestion, Analysis, Transformation, Storage
• Ingestion, Storage, Transformation, Analysis
• Ingestion, Transformation, Storage, Analysis
  

  Answers Explanation & Hints: The correct order of the stages in the data pipeline is: Ingestion, Transformation, Storage, Analysis. Ingestion: This is the stage where data is collected from various sources and brought into the data pipeline. This can involve data streaming or batch processing techniques. Transformation: Once data has been collected, it needs to be transformed into a format that can be processed and analyzed. This can include cleaning, normalization, and structuring the data. Storage: After transformation, data needs to be stored in a way that makes it accessible for analysis. This can involve a variety of storage options such as data warehouses, data lakes, or cloud storage. Analysis: The final stage of the data pipeline involves the use of tools and techniques to analyze the data and extract insights from it. This can include visualization tools, machine learning algorithms, or statistical analysis.

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2.3.3 Module 2 Quiz – Data Collection and Gathering Exam Answers 100% 2023

What big data term includes reducing the amount of data cleaning that is required?

• Volume
• Variety
• Velocity
• Veracity
  

  Answers Explanation & Hints: The big data term that includes reducing the amount of data cleaning that is required is veracity. Veracity refers to the quality or trustworthiness of the data, and it encompasses data accuracy, consistency, completeness, and reliability. By ensuring data veracity, it is possible to reduce the amount of data cleaning and preparation required before it can be used for analysis. This includes identifying and addressing issues with data quality, such as missing values, inconsistencies, errors, and duplication. By improving the veracity of data, it becomes more reliable and valuable for decision-making purposes.

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2.3.3 Module 2 Quiz – Data Collection and Gathering Exam Answers 100% 2023

The four V’s of Big Data are volume, velocity, variety, and veracity. What is meant by variety?

• The volume of data in motion.
• The amount of data cleaning that is required.
• The rate at which data is generated.
• The data type that is not ready for processing and analysis.
  

  Answers Explanation & Hints: The variety in the four V’s of Big Data refers to the different types and sources of data that are available. This includes both structured and unstructured data from a variety of sources such as social media, sensors, web logs, and more. With the increasing availability of new data sources and formats, managing and analyzing such a variety of data can be challenging. The variety of data can affect the way it is stored, processed, and analyzed. This requires specialized tools and techniques to handle different types of data in order to extract meaningful insights and value from it.

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2.3.3 Module 2 Quiz – Data Collection and Gathering Exam Answers 100% 2023

Match the network security testing tool with the correct function. (Not all options are used.)

Network Security (Version 1) – Network Security 1.0 Practice Final Answers 006

What three tasks can a network administrator accomplish with the Nmap and Zenmap security testing tools? (Choose three.)

• operating system fingerprinting
• assessment of Layer 3 protocol support on hosts
• open UDP and TCP port detection
• security event analysis and reporting
• password recovery
• development of IDS signatures
  

  Answers Explanation & Hints: Nmap is a low-level network scanner that is available to the public and that has the ability to perform port scanning, to identify open TCP and UDP ports, and which can also perform system identification. It can also be used to identify Layer 3 protocols that are running on a system. Zenmap is the GUI version of Nmap.