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Questions and Answers

Which of the following is the MOST accurate representation of the initial stage in a typical data science process?

  • Exploratory Analysis
  • Inference / Prediction
  • Problem Definition (correct)
  • Data Preparation

In the context of machine learning, what type of question does supervised learning primarily address?

  • Identifying patterns in data without prior knowledge.
  • Predicting a continuous value for a given input. (correct)
  • Determining the underlying structure of unlabeled data.
  • Clustering data points into unknown groups.

Which stage of the data science process focuses primarily on cleaning, transforming, and structuring raw data?

  • Problem Definition
  • Data Preparation (correct)
  • Exploratory Analysis
  • Inference / Prediction

Consider a scenario where a machine learning model is used to predict whether a customer will default on a loan. Which type of question does this BEST exemplify?

<p>Is this of type X or Y? (A)</p> Signup and view all the answers

A data science team is tasked with predicting the price of a house based on features like location, size, and number of bedrooms. Which machine learning question type ALIGNS with this task?

<p>How Much / How Many? (D)</p> Signup and view all the answers

A newly established online retailer wants to implement a machine learning model to categorize incoming customer service emails into predefined categories such as 'Shipping Issues', 'Product Returns', 'Payment Problems', and 'General Inquiries'. Which question aligns with this objective?

<p>Is this of type A, B, C, or D? (D)</p> Signup and view all the answers

A research team is investigating the impact of various marketing strategies (A, B, C, and D) on product sales. They want to determine not only which strategy yields the highest sales but also quantify the precise sales increase attributable to each strategy relative to a baseline. Which question type does this multifaceted goal BEST represent?

<p>A combination of 'Is this of type A, B, C, or D?' and 'How Much / How Many?' (A)</p> Signup and view all the answers

Which of the following questions falls under the domain of unsupervised learning?

<p>Which customers exhibit similar purchasing patterns regarding insurance plans? (D)</p> Signup and view all the answers

Which of the following best exemplifies the characteristics of today's customers as highlighted in the material?

<p>Well-informed, highly expectant, and impatient. (D)</p> Signup and view all the answers

In the context of product development, why is understanding customer behavior paramount?

<p>To create products that are customer-centric and meet their needs. (B)</p> Signup and view all the answers

What type of learning is exemplified when determining if a customer will buy insurance B, given they bought insurance A?

<p>Supervised Learning (B)</p> Signup and view all the answers

In a highly dynamic and competitive environment, what key characteristic should a product or business possess to thrive?

<p>Adaptability (D)</p> Signup and view all the answers

Which of the following questions exemplifies the application of data science in product development?

<p>What common behaviors lead customers to stop using our product? (A)</p> Signup and view all the answers

Consider an e-commerce platform where the price of a product fluctuates based on demand. What customer expectation is most likely being challenged in this scenario?

<p>Consistent Pricing (B)</p> Signup and view all the answers

Imagine a scenario where an AI-powered search engine takes an excessively long time (e.g., 1 minute) to display search results. Which of the following customer attributes is most directly affected?

<p>Level of Patience (C)</p> Signup and view all the answers

Given the increasing accessibility of information and the expectation for rapid service, which business strategy would be LEAST effective in maintaining customer satisfaction?

<p>Relying solely on traditional marketing methods without adapting to current trends. (C)</p> Signup and view all the answers

What does a top-down analysis of business requirements primarily represent?

<p>The truly required needs of end-users and the business. (D)</p> Signup and view all the answers

During the 'Design, Build, Test' phase, which activity focuses on capturing market trends and opportunities?

<p>Designing based on specifications from data gathered. (D)</p> Signup and view all the answers

What is the primary purpose of collecting data during the building and testing phase?

<p>To prepare data for hypothesis testing and analysis. (A)</p> Signup and view all the answers

In the context of product development, what happens during iterative testing in the deployment phase?

<p>Adjusting the product based on collected data to create new versions. (B)</p> Signup and view all the answers

Which of the following is NOT a key reason for collecting data related to product/service updates?

<p>To determine the employees satisfaction. (D)</p> Signup and view all the answers

What is the ultimate goal of checking if products or services are 'market-ready'?

<p>To verify that products meet requirements and are suitable for launch. (B)</p> Signup and view all the answers

What does 'essential' refer to in the context of top-down analysis of business requirements?

<p>The needs or requirements of end-users. (B)</p> Signup and view all the answers

What does 'Enterprise' refer to in the context of business requirements?

<p>The whole business or specific business functions/operations. (A)</p> Signup and view all the answers

How can an Electronics company improve new product development, according to Tan, K.H.and Zhan, Y.?

<p>By using Big Data. (C)</p> Signup and view all the answers

During the 'Design, Build, Test' phase of product development, what is the most critical reason for rigorously testing hypotheses with collected data?

<p>To rigorously validate assumptions and ensure the product meets market needs and specifications, minimizing potential failures post-launch. (C)</p> Signup and view all the answers

Which of the following best describes the primary purpose of the CRISP-DM methodology?

<p>To standardize the process of data mining across various industries. (D)</p> Signup and view all the answers

In the context of product development, what is the MOST important reason for understanding how data will be used during the 'Initialize specifications' stage?

<p>To identify and meet data requirements effectively. (B)</p> Signup and view all the answers

During the 'Initialize specifications' stage of product development, which type of data is LEAST likely to be considered?

<p>Real-time sensor data from deployed products. (D)</p> Signup and view all the answers

What is the direct output of a data requirement analysis during the initial specification phase?

<p>Business rules and constraints. (D)</p> Signup and view all the answers

Which of the following is a potential pitfall of simply automating existing business processes without careful analysis?

<p>It can result in complex, restrictive, and inflexible systems. (B)</p> Signup and view all the answers

In the CRISP-DM model, what phase directly follows 'Data Preparation' and precedes 'Evaluation'?

<p>Modeling (C)</p> Signup and view all the answers

Which of the following best summarizes the role of 'Business Requirement Analysis' during the 'Initialize specifications' stage?

<p>To translate end-user needs into technical specifications. (B)</p> Signup and view all the answers

Which of the following is the MOST accurate description of how organizations typically evolve over time, impacting their systems?

<p>They generally become more complicated. (B)</p> Signup and view all the answers

If a company decides to skip the 'Business Understanding' phase of the CRISP-DM model, what is the MOST likely consequence?

<p>They might address the wrong problem or fail to meet business objectives. (A)</p> Signup and view all the answers

An organization aims to implement a new AI-driven customer service system. They meticulously automate their existing, but highly inefficient, call center processes without conducting a thorough business requirement analysis or process re-engineering. What is the MOST probable outcome?

<p>A system that perpetuates existing inefficiencies at a higher speed and potentially introduces new complexities due to the rigid automation of flawed processes, ultimately leading to limited improvements and potential customer frustration. (B)</p> Signup and view all the answers

What is a key benefit of connecting and communicating with customers through social media platforms for product development?

<p>It allows for extremely quick and effective feedback and idea generation. (C)</p> Signup and view all the answers

In a normal product development cycle, which step typically follows the launch of a product?

<p>Gathering feedback from users and partners. (C)</p> Signup and view all the answers

Approximately how frequently does Xiaomi update its operating system, based on the information?

<p>Weekly (D)</p> Signup and view all the answers

What is the primary operational implication of designing a product to be highly customizable, as exemplified by Xiaomi's approach?

<p>It necessitates a robust system for analyzing user feedback and suggestions. (B)</p> Signup and view all the answers

Given Xiaomi's operational tempo of launching a new phone product every 3 months and updating its OS weekly, which strategic challenge would be MOST critical for them to continuously address?

<p>Balancing innovation with thorough testing to prevent user dissatisfaction due to bugs or instability in new releases. (A)</p> Signup and view all the answers

Flashcards

Data Science

A multidisciplinary field using scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.

Data Science Process

The process of understanding the problem, preparing the data, exploring and analyzing, inferring/predicting and finding alternative solutions to the original problem.

Importance of the Question

The starting point of any effective solution is a well-defined question.

Supervised Learning

Machine learning tasks where the algorithm learns from labeled data to predict categories.

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Is this of type X or Y?

An example of a question that can be answered using supervised learning.

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How Much / How Many?

An example of a question that can be answered using supervised learning.

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Fraudulent claim detection

An example of a question that can be answered using supervised learning.

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Relationship between Variables

Predicting relationships and dependencies between different variables in a dataset.

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Customer Expectations

Customers today expect quick results and have higher expectations.

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Dynamic and Competitive Environments

Environments that change rapidly and involve intense competition among businesses.

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Customer-Centric

Designing products and services that prioritize the needs and experiences of customers.

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Need to know your customers

The necessity of understanding customer preferences, behaviors and needs to tailor products effectively .

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Data Science for Product Development

Using data insights to drive and improve various stages of product creation.

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Product Analytics

The use of analytical techniques applied to product-related data to guide decision-making.

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CRISP-DM

A structured approach to planning and executing data mining projects, consisting of six phases: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment.

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Data Driven Model

A product development approach using data insights at each stage.

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Initialize Specifications

Understand data use, identify requirements, internal/external sources, and outputs.

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Internal Development Data

Strategic, financial, project data, simulations for physical products

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Internal/External Data

Customer behavioral data, needs, wants, and technical information.

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Externally Available Data

Competitor, regulatory, and public data.

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Data as an asset

Treat data like a valuable item

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Business Requirement Analysis

Capturing needs and constraints from the user.

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Business Rules/Constraints

The results of Business Requirement Analysis.

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Complicated Organizations

Automating outdated processes leads to complex, inflexible systems.

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Normal Development Cycles

A cyclical process of product development involving launching, gathering feedback, fixing, and repeating.

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Social Media Data Use

Collecting and analyzing data from social media to interact with customers, gather feedback, and announce product details.

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Product Customization

Designing a product to allow high levels of customization based on user suggestions and feedback.

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Co-Creation Benefits

Direct access to customer thoughts and feeling leading to faster, effective feedback improving customer relations.

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Xiaomi's Fast Development

Updating their operating system weekly and releasing a new phone every three months.

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Top-down analysis

Analysis that starts with business needs to define true requirements.

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Essential requirements

Needs or requirements directly from the users.

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Enterprise scope

The entire business or specific functions/operations.

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Product/Service Requirement Alignment

Determining if products or services satisfy defined needs.

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Data-Driven Design

Design solutions based on data from specifications and market trends.

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Data Acquisition

Collecting data during building and testing phases to prepare data for hypothesis testing.

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Market-Ready Check

Verifying products and services are ready for market release.

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Iterative Deployment Testing

Iteratively testing and collecting data during deployment to refine the product.

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Update Specification

Specification for any update to products/services.

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Impact Measurement

Assessing the effects of updates on products/services.

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Study Notes

  • ITCT101 Computer Technologies covers AI, Machine Learning (ML), and Data Science.
  • The lecture will cover the Data Science Process, Product Development, and Data Science case studies.

Data Science Definition

  • Concerns Computer Science/IT, Math and Statistics, and Domains/Business Knowledge.

Data Science Process

  • Starts from a Problem, undergoes Data Preparation, Exploratory Analysis, Inference/Prediction, and an Alternative Solution, to produce Results.
  • Addressing a solution should start with the question itself.

ML Question Types and Approaches

  • Yes/No questions indicate Supervised Learning.
  • Finding the data organization relies on Unsupervised Learning.

Data Science for Product Development

  • Requires Khashayar Khosravi, "Why You Need Data in Your Product Development Processes"
  • Requires Yali Sassoon, "Product Analytics: Digital Products"
  • Include informed, impatient customers with high expectations.
  • Dynamic and competitive environments are growing.
  • Adaptable products/businesses are essential.
  • Customer focus is a need.

KDD (Knowledge Discovery in Databases) Process

  • Involves Selection, Preprocessing, Transformation, Data Mining, Interpretation/Evaluation, and Knowledge.

CRISP-DM Data Mining Process

  • Requires Business Understanding
  • Requires Data Understanding
  • Requires Data Preparation
  • Requires Modeling
  • Requires Evaluation
  • Requires Deployment

Data Driven Model in Product Development

  • The three common stages include:
    • Initializing specifications
    • Design, build, and test
    • Setting final specifications and commercialization.

Initialize Specifications

  • Understand how data will be used
  • Have a way to Identify Data requirements
    • Includes Internal development, Internally and externally developed information, Externally available information,
    • Data must be considered an asset
  • Capture all requirements from end-users with Business Requirement Analysis
  • Output of Data requirement analysis becomes "Business Rules/Constraints."

Business Requirement Analysis

  • Happens because Organizations become complicated, simply automating business results in complex, restrictive and inflexible systems.
  • The solution includes:
    • Top-down analysis of business requirements which represents what's truly required
    • Essential: End-users’ needs or requirements
    • Enterprise: the whole business, or specific business functions/operations.
    • Products/Services: Determine whether products or services met requirements.

Design, Build, Test

  • Designs are based on data gathered from previous specifications.
  • Market trends and opportunities are captured.
  • Data are tested during building.
  • Products/services are verified as "market-ready."

Deployment and Following Up

  • Deploys iteratively to test and collect data to adjust/create new versions/products.
  • Conduct testing with any new features and verify output to meet requirements

Summarization

  • Updates must specify effects on Products/Services
  • Describe the impact the update should have
  • Impacts must feature The measurement criteria
  • Conclude with a decision of whether or not to proceed with updates.

Case study: Xiaomi

  • Normal Development Cycles consist of launching, receiving feedback from user/partners, fix the product with new functions/features, and then rinse and repeat.

Connect & Communicates

  • Data must be collected and analyzed from social media platforms.
  • Interact with customers on Xiaomi forums, Wechat, QQ, and Weibo
  • Provide Feedback with Product details, announcements, feedback, and discussions
  • Design products to be highly customizable
  • Analyze User Suggestions and Feedbacks
  • Get feedback and ideas quickly and effectively
  • Develop customer relations with firm improvement commitment through co-creation with customers.

Case study: Facebook

  • Includes the Use of targeted advertising with user data from other websites and apps.

Homework

  • Write a 3-5 page report demonstrating how to apply and use Data Science to support your innovation
  • Assignment must be uploaded to the eLearning System by Tuesday, 18 February 2025 before 12:00 pm.

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