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Terms in this set (103)The most important V of the big data issue is the ______. Value Which of the following is the Veracity of big data? The quality or uncertainties of data _________ are all possible data we can collect to support the decision-making in education industry? -How much time it takes a learner to answer a specific question The term big data refers to all of the following except: datasets with fewer than a billion records The following are technologies used to store, analyze, and manage big data. Hadoop, In-memory computing, analytical platforms The ever-increasing different forms that can come in, such as text, images, voice, and spatial data is called the ____ dimension of big data. Variety A household appliances manufacturer has hired you to help analyze its social media datasets to understand how customers evaluate its refrigerators. Which of the following techniques would you use to analyze this data?
Text Mining Tools Strategy What our competitive gameplay will be The basic elements of Strategy Objective, Scope, Advantage Objective defines the ENDS that the strategy is designed to achieve within a specific time frame Scope Is the DOMAIN of the business, the part of business landscape in which your firm will operate Advantage Determines what you will do differently or better than competitors to achieve your objective Growing interdependence between a firm's Information Systems and its Business Capabilities means... changes in strategy, rules, and business processes increasingly require changes in hardware, software, databases, and telecommunications Why do firms invest heavily in information systems? To achieve six strategic Business Objectives of Information Systems Operational Excellence (6 Business Objectives of IS) -Improved efficiency results in higher profits. New Products, Services, and Business Models (6 Business Objectives of IS) Information systems and technologies enable firms to create new products, services, and business
models. Customer and Supplier Intimacy (6 Business Objectives of IS) -Customers who are served well become repeat customers who transact with your firm more. Improved Decision Making (6 Business Objectives of IS) -Without accurate information: Managers must use forecasts, best guesses, luck. Poor outcomes raise costs, lose customers. Competitive Advantage (6 Business Objectives of IS) Often results from achieving previous 4 business objectives. Involves charging less for superior products, better performance, and better response to suppliers and customers. Survival (6 Business Objectives of IS) -Information
technologies as necessity of business Porter's Competitive Forces Model 1. Potential threats of new entrants strategic objectives of Leveraging Big Data 1. Improving Operational Excellence 1. Improving Operational Excellence (LBD) Cost reduction and time reduction 2. Developing New Offerings (LBD) Recommendation systems, such as "people you may know" 3. Improving Decision Making (LBD) How to best place products, what offers to present to a customer, which customers are likely to go away, or which engineers are most likely to quit The US real estate market was... Inefficient, highly fragmented, and highly competitive How was Redfin different from other broker companies? Redfin was a register broker unlike Zillow and Trulia. It sought to be a tool for real estate agents instead of competing with them. Redfin still losing money as a whole in 2020. Were Redfin agents earning more or less than other brokerages? Their lead agents in 2020 earned a median income that was twice as much as agents at competing brokerages. If the data capture and the sharing of this data among third parties is poorly understood by consumers and often not communicated transparently by websites and applications, this is classified as __________. A) Active Data Capture Passive Data Capture Which of the following is the illustration of passive data capture in healthcare industry? A) Ginger.io (an app) measures users' communication with friends, physical movement, and exposure to natural light to identify early warning signs of chronic illnesses and conditions. Ginger.io (an app) measures users' communication with friends, physical movement, and exposure to natural light to identify early warning signs of chronic illnesses and conditions. Shopping cart alerts customers to bananas on sale in supermarkets and suggests recipes is which type of interaction? A) Machine to Machine (M2M) Machine to People (M2P) Which one of the following is NOT included in an IoT architecture? A) Connected machines generate data Business Intelligence systems make it easy to visually display data and information on a variety of user interfaces Which of the following is the feature of an active data capture process? A) Data process is manually initiated by a distinct human decision to share or transmit data All of the above Which of the following statements is correct? A) Sensors of an intelligent watering system read the air and soil temperatures, and humidity information, and activate to water. Actuators in the intelligent watering system are the valve and solenoid that start and stop waterflow Companies implementing IoT projects are expecting the following advantages EXCEPT FOR: A) Improved
operational efficiency Guaranteed customer privacy Which characteristic allows IoT devices to coordinate novel applications that each of them individually could not perform? A) Dynamic nature Interconnectivity Microcontroller (MCU) connects sensors and actuators. Has CPU, RAM, ROM embedded in chip. Unlike microprocessors. Big Data Volumes too great for typical DBMS. Usually in petabytes and exabytes range. Today data is more hetergeneous Big data has sets of... unstructured/semi-structured data from different sources, not suitable for relational databases. Data Volume (3 V's) Huge data size, petabytes. Data Variety (3 V's) Various data sources, (social, mobile, M2M, structured and unstructured data) Data Velocity (3 V's) High speed of data flow, data change, and data processing Veracity Quality, accuracy of data, reliability of data source, and the context within analysis. Valence Connectedness. Two data items are connected when they are related to each other. Increases over time Business VALUE of Big Data Most important V, at the center of the other V's. Can reveal more patterns, relationships, and anomalies. Uncovers insight for firms. Big Data leads to better models and higher precision Three types of Analytics? Descriptive Analytics Data Mining Finds hidden patterns, relationships in datasets, such as customer buying patterns. Infers rules to predict future behavior. Association (DM) Type of information from data mining. They are occurrences linked to a single event. Such as the diapers and beer being bought on friday's. Sequences events linked over time Classification recognizes patterns that describe group to which items belong Clustering similar to classification when no groups have been defined; finds groupings within data Text Mining extracts key elements from large unstructured data sets. Tools that analyze survey responses, emails, tweets, product reviews, etc to help businesses gain insights and make data based decisions Web Mining discovery and analysis of useful patterns and information from the web. Includes web content mining, web structure mining, and web usage mining Data Visualization often combined with mining. Helps users see patterns and relationships that would be difficult to see in text lists Active Data Capture the process is clearly and distinctly initiated. Data is defined and limited, decisions driven by specific customer actions Passive Data Capture occurs without any overt consumer interaction. Generally includes capturing user preferences and usage behavior, such as location data from personal mobile devices. No direct involvement or awareness or transmission The Internet of Things (IoT) the interconnected network of physical objects, devices, electronics contacting software, sensors, and network connectivity. Enabling them to collect and exchange data. Application examples of IoT Medical and healthcare remote health monitoring, emergency notification systems. Sensors reads something about the environment (FEEL), don't take action Actuators take input and transforms input into tangible action, it makes things happen (ACT). Are in close collaboration with sensors Microcontroller (MCU) a tiny, self contained computer hosted on a microchip, acting as the "brain" that connects sensors and actuators IoT Architecture has how many steps? 5 steps First step of IoT architecture Connected machines generate data Second step of IoT architecture Edge computing processes some data Third step of IoT architecture Networks transmit remaining data to cloud or local servers Fourth step of IoT architecture Platforms organize the data and send it to apps Fifth step of IoT architecture Apps process the data, creating insights and solutions IoT Advantages Enables operational efficiency, better costumer experience, cost reduction, problem prediction and analysis, and improves safety and security. IoT Challenges Figuring out how to best utilize IoT devices, The IoT strategy development, focus on value. Enablers technology oriented companies that develop and implement the underlying technology. (Google, Cisco, IBM) Engagers businesses that design, create, integrate, and deliver IoT services. (Nest Learning Thermostat) Enhancers
devise their own value-added services on top of the services provided by engagers (Progessive's UBI) Data Fusion Combine Data to produce economic value. Synergy: 1+1 > 2. (Ex: Real estate industry) Artificial Intelligence Systems that take data inputs, process them, and produce outputs. Can learn and improve performance over time. Why is AI important? AI automates reptile learning and discover through data. AI analyzes more data as well as deeper data. Incredible accuracy through deep neural networks. Machine Learning A specific way to realize AI. How computer programs improve performance without explicit programming. Begins with
very large data sets, automatically finds patterns, and uses statistical inference. Arthur Samuel (1959, ML) Field of study that gives computers the ability to learn without being explicitly programmed Tom Mitchell (1998 ML) A computer program is said to learn from experience (E) with respect to some task (T) and some performance measure (P). (If its performance on T, as measured by P, improves with experience E) Supervised Learning A type of model creation, derived from the field of machine learning, in which the target variable is defined. Right answers given for each example in data. Has training set and test set Unsupervised Learning A type of model creation, derived from the field of machine learning, that does not have a defined target variable. No right answer, finds similarities Linear Regression (Supervised Learning) predicts continuous valued output (house price) Error in the Model RMSE, or mean absolute error. The closer to 0, the better the model Classification (Supervised Learning) to predict which class, or category, something belongs to. A discrete valued output (0 or 1) Clustering (Unsupervised Learning) a technique that is used to find natural groupings in data based on similarities, such as behavior and demographics A cluster is a group of data points or objects in a dataset that are similar to other objecting in the group, and dissimilar to data points in other clusters Through clustering a company may discover -One segment of customers who make their purchases on a regular basis, and buy the same beans in larger
quantities Common applications of clustering -discover customer clusters to identify market segmentation to market more efficiently Natural Language Processing Understand, and speak in natural language. Read natural language and translate Text Analytics Hospitals, spam filtering, sentiment analysis Speech Recognition Customers services, intelligent assistants Translation Real world AI, such as Skype translator in the classroom Neural Network Find patterns in massive amounts of data too complicated for humans to analyze. Learn patterns by searching for relationships, building models, and correcting over and over. Humans train networks by feeding it data to learn solutions by example How does Supervised Learning differ from Unsupervised Learning? Uses regressions and classifications. Has more evaluation methods than unsupervised learning. A more controlled environment How does Unsupervised Learning differ from Supervised Learning? Finds patterns and groupings from unlabeled data. Has fewer evaluation methods than supervised learning. A less controlled environment A computer program is said to learning from experience E with respect to some task T and some performance measure P if its performance on T, as measured by P, improves with experience E. Suppose we feed a learning algorithm a lot of historical weather data, and have it learn to predict weather. What would be a reasonable choice of P? A) The action of predicting weather The probability of it correctly predicting a future day's weather The term supervised learning refers to the fact that we give the learning algorithm a data set, in which the "right answers" were given. This data set is usually called A) Training set Training set The following statement of machine learning are correct except _________. A) Two broad kinds of machine learning are supervised learning and unsupervised learning Machine learning algorithms simulate the neurons in human brains to find patterns Deep learning networks ________. A) rely on humans to help it identify patterns use multiple layers of neural networks to detect patterns in input data Which of the following is NOT an example of supervised machine learning? A) Identifying a breast tumor as malignant or benign Google News displays news stories about the same topic together Clustering algorithm can be used to _________. A) All of the above All of the above Unsupervised machine learning requires a gold standard to train the algorithm to correctly identify a new input. True or False False Which of the following is not true about AI technologies? A) AI systems take data from the environment and produce outputs like other computer programs AI programs today have mastered common sense thinking similar to humans Other sets by this creatorMGT 3374 (Feruzan-Williams) Exam 1 Review52 terms MichaelRod BECO 3310 Exam 2 Fitzgerald6 terms MichaelRod ISQS 3348 Exam 1 (Graue)15 terms MichaelRod BLAW 3391 Final (Mcinturff)85 terms MichaelRod Verified questions
physics A wave on a string is described by $y(x, t) = 15.0 \sin(\pi x/8 - 4\pi t)$, where x and y are in centimeters and t is in seconds. What is the magnitude of the maximum transverse acceleration for any point on the string? Verified answer biology When the reproductive system becomes fully functional ______ (a). corticosteroid (b). puberty (c). epididymis (d). fertilization (e). hormone Verified answer
health Define each vocabulary term in your own words. scratch cooking, convenience cooking, recipe, ingredient, yield, customary measurement system, metric system, volume, weight, level off, heaping, herb, spice, rub, condiment, transfer, project. Verified answer
engineering Estimate the theoretical density of $\alpha$-Sn. Assume $\alpha$-Sn has the diamond cubic structure and obtain the atomic radius information from Appendix B. Verified answer Recommended textbook solutions Introduction to Algorithms3rd EditionCharles E. Leiserson, Clifford Stein, Ronald L. Rivest, Thomas H. Cormen 726 solutions Information Technology Project Management: Providing Measurable Organizational Value5th EditionJack T. Marchewka 346 solutions Information Technology Project Management: Providing Measurable Organizational Value5th EditionJack T. Marchewka 346 solutions Service Management: Operations, Strategy, and Information Technology7th EditionJames Fitzsimmons, Mona Fitzsimmons 103 solutions Which of the following is not an example of artificial intelligence?Answer. are both AI, but a leader is not.
What is not under artificial intelligence?Sensors in your office can recognise shadows or movements, but that doesn't make them artificial intelligence. If the sensors had recognised you as a person freezing, for instance, and then turned up the heat, then we are talking.
What are the 4 components of AI?As such, the five basic components of artificial intelligence include learning, reasoning, problem-solving, perception, and language understanding.
What are the 3 components of artificial intelligence?The three artificial intelligence components used in typical applications are:. Speech Recognition.. Computer Vision.. Natural Language Processing.. |
Which of the following is not one of artificial intelligence enablers Quizlet
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