ETI3647 Supply Chain Management (6.3)
In the SCOR metrics case, ____________ made it possible to identify how the selected metrics are affected if the assumptions of the analysis changed. data visualization web scraping sensitivity analysis multi-criteria decision methods
sensitivity analysis
In the SCOR metrics case, analytical hierarchy process (or factor rating or weighted scoring method) was used across the system using three new scenarios to evaluate how the model changed. True False
False
__________ uses bots (automated software agents) to extract content and data from a website using underlying HTML code for later use. Crawling Web scraping Data Sets API Stores
Web scraping
_____________ creates structured information or new data from electronic words, which as integrating customer comments or reviews on social media forums for more accurate prediction models. Clustering or unsupervised modeling Text analytics Interactive data visualization Association-rule learning
Text analytics
What is the purpose of data mining? To evaluate geological data to identify location of raw materials, such as coal, copper, and other items. To react to e-commerce users such that obsolete inventory or ineffective promotions are eliminated. To discover knowledge that is used to gain insights to drive better actions across organizations. To extract data from competitors to gain an unfair advantage over them improving the supply chain.
To discover knowledge that is used to gain insights to drive better actions across organizations.
In the SCOR metrics case, a group of experts was selected and surveyed to build criteria or attributes, as well as weights, for using the analytical hierarchy process (or factor rating or weighted scoring method). True False
True
U.S. courts have acknowledged that users of 'scrapers' or 'robots' may be held liable for committing trespass chattels. Question options: True False
True
__________ is a computer software technique of extracting or harvesting data and information from websites. Web scraping Analytics Sorting and Filtering Prototyping
Web scraping
________________ allows the ability to search web connected services in a way that is agreed about with the service provider simplifying legality issues with its terms of use. Web scraping API Stores Crawling Data Sets
API Stores
Which reason for data mining would build charts or figures to evaluate extracted data? Web scraping Analytics Prototyping Sorting and Filtering
Analytics
_____________ searches for relationships among variables, such as market basket analysis regarding products frequently bought together, which can lead to further recommendations for purchase. Text analytics Interactive data visualization Association-rule learning Clustering or unsupervised modeling
Association-rule learning
_____________ identifies groups or structures in the data that are similar, beyond the structures otherwise visible in the data. Interactive data visualization Text analytics Clustering or unsupervised modeling Association-rule learning
Clustering or unsupervised modeling
__________ uses bots (automated software agents) to systematically browse other websites over the Internet repeating the processes of extracting content and data for further use. Web scraping Crawling API Stores Data Sets
Crawling
________________ a table or statistic matrix that can be leveraged or used to analyze variables, may not real-time, but gives a lot of data. Data Sets API Stores Web scraping Crawling
Data Sets
___________ is a variable that is influenced by other factors and when examining relationships between variables you want to find out what makes it change the way it does. Sensitivity Analysis Independent variable Dependent variable Scientific method
Dependent variable
___________ is a variable that stand alone and is not changed by other variables you are trying to measure and when examining relationships between variables it causes some kind of change in other variables. Scientific method Independent variable Dependent variable Sensitivity Analysis
Independent variable
_____________ presents results graphically and lets users interact with the graphs to more easily identify important patterns or anomalies with the data that might have an impact in the model-building stage. Association-rule learning Clustering or unsupervised modeling Text analytics Interactive data visualization
Interactive data visualization
In the SCOR metrics case, ____________ graphically represented the magnitude of problem with a decision tree for each level to set up a structured approach. Question options: Step 1 Step 2 Step 4 Step 3
Step 2
Which step in the analytical life cycle is focused on collecting attributes and transforming raw data that can be used as an input for data mining and machine learning that often includes a training and testing set? Question options: Step 1: Turn a business question into an analytical hypothesis. Step 3: Explore the data. Step 2: Prepare the data for data mining. Step 4: Model the data.
Step 2: Prepare the data for data mining.
Which step in the analytical life cycle searches for anticipated relationships or distributions, unanticipated trends or patterns, and anomalies (i.e. data errors, missing data, etc.) to gain an understanding of the information working with and to further refine ideas and questions? Step 2: Prepare the data for data mining. Step 3: Explore the data. Step 4: Model the data. Step 1: Turn a business question into an analytical hypothesis.
Step 3: Explore the data.
Which reason for data mining evaluates an idea by trying out a concept for validation purposes? Web scraping Prototyping Sorting and Filtering Analytics
Prototyping
______________ prepares data for predictive analytics, identifies the most significant variables, develops models using modern data mining and machine learning algorithms, validates the accuracy and fitness of the models, and generates assets that allow simple deployment into operational applications for automated decision making. SAS Enterprise Miner SAS Factory Miner SCOR Sensitivity Analysis SCOR Analytic Hierarchy Process
SAS Enterprise Miner
___________ is a tool for performing quantitative risk assessment that evaluates the relationships between process parameters, material attributes, and product or service quality attributes. Scientific method Independent variable Dependent variable Sensitivity Analysis
Sensitivity Analysis
Which reason for data mining assesses topics of interest seeking to understand what key words or topics get people engaged in a website? Question options: Sorting and Filtering Prototyping Analytics Web scraping
Sorting and Filtering
In the SCOR metrics case, ____________ established the objective of the problem (i.e. business question or analytical hypothesis) to approach identifying the criteria that most influences its achievement based on characterization of the supply chain. Question options: Step 4 Step 1 Step 2 Step 3
Step 1
Which step in the analytical life cycle begins the discovery process exploring what you need to know and how you can apply predictive analytics to your data to solve a problem or improve a process? Step 1: Turn a business question into an analytical hypothesis. Step 4: Model the data. Step 2: Prepare the data for data mining. Step 3: Explore the data.
Step 1: Turn a business question into an analytical hypothesis.
In the SCOR metrics case, ____________ graphically represented the magnitude of problem with a decision tree for each level to set up a structured approach. Step 4 Step 2 Step 3 Step 1
Step 2
Which step in the analytical life cycle searches for anticipated relationships or distributions, unanticipated trends or patterns, and anomalies (i.e. data errors, missing data, etc.) to gain an understanding of the information working with and to further refine ideas and questions? Step 4: Model the data. Step 3: Explore the data. Step 1: Turn a business question into an analytical hypothesis. Step 2: Prepare the data for data mining.
Step 3: Explore the data.
Which step in the analytical life cycle applies numerous analytical algorithms to the data to find a robust representation of the relationships in the data that answer the business question reliability predicting a desired outcome? Step 1: Turn a business question into an analytical hypothesis. Step 4: Model the data. Step 2: Prepare the data for data mining. Step 3: Explore the data.
Step 4: Model the data.
Technologies of data mining, machine learning, and advanced analytical modeling are essential for _____________. *automating processes to reduce labor costs and avoid inefficiencies in a more reliable manner *identifying the factors that can improve organizational performance and, when automated in everyday decisions, create competitive advantage *developing robotic systems to overcome a shortage of skills, as well as issues with other resources in order to support digitizing supply chains
identifying the factors that can improve organizational performance and, when automated in everyday decisions, create competitive advantage