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Regular version of the site
Master 2024/2025

Research Seminar "Product Approach in Data Analytics"

Type: Compulsory course (Master of Data Science)
When: 1 year, 2-4 module
Open to: students of one campus
Instructors: Armen Beklaryan
Language: English

Course Syllabus

Abstract

The course offers students an in-depth study of the methods and tools required to develop analytical products focused on business needs. Students will learn to apply a product approach to data analysis, including hypothesis formulation, prototyping and solution testing. The workshop includes practical assignments and case-studies to develop skills to work in interdisciplinary teams and make informed decisions based on data.
Learning Objectives

Learning Objectives

  • Understand the fundamentals of product thinking in data analysis
  • Design data products that meet user needs and provide exceptional user experiences.
  • Align technical projects with business objectives to maximize impact.
  • Manage the end-to-end lifecycle of data products, from ideation to deployment and iteration.
  • Address ethical issues related to data privacy, bias, and responsible use
Expected Learning Outcomes

Expected Learning Outcomes

  • Understand the role and responsibilities of a product manager in the IT industry.
  • Describe the key stages of the IT product lifecycle.
  • Differentiate between product management and project management.
  • Explain the importance of data-driven decision-making in product management
  • Apply SWOT analysis to identify strengths, weaknesses, opportunities, and threats of a product.
  • Conduct PESTEL analysis to evaluate external environmental factors affecting the product.
  • Utilize Porter's Five Forces model to assess industry competition and attractiveness.
  • Develop a Business Model Canvas for an IT product, outlining key components such as value propositions, customer segments, and revenue streams.
  • Conduct user research using qualitative and quantitative methods (e.g., interviews, surveys,observations)
  • Create user personas based on research data
  • Map customer journeys to identify user needs and pain points.
  • Apply design thinking principles to ideate and prototype product solutions
  • Develop low-fidelity and high-fidelity prototypes
  • Conduct usability testing and gather user feedback.
  • Understand the principles and values of Agile development.
  • Implement the Scrum framework, including defining roles, artifacts, and ceremonies.
  • Create and manage a product backlog with user stories and acceptance criteria.
  • Prioritize product features using techniques such as MoSCoW or the Kano Model.
  • Utilize Kanban boards to visualize workflow and manage work in progress (WIP)
  • Conduct sprint planning, daily stand-ups, sprint reviews, and retrospectives.
  • Define key performance indicators (KPIs) and metrics relevant to IT products.
  • Set up and configure analytics tools (e.g., Google Analytics, Mixpanel) to track user behavior.
  • Interpret data to identify trends and inform product decisions
  • Design and conduct A/B tests to compare product variations.
  • Analyze experimental results for statistical significance
  • Create data dashboards to monitor product performance over time.
  • Develop a Go-to-Market strategy, including positioning, messaging, and marketing tactics.
  • Plan and execute product launch activities
  • Identify and leverage appropriate marketing channels (e.g., social media, content marketing,SEO)
  • Apply growth hacking techniques to drive user acquisition and engagement.
  • Plan for scalability, including infrastructure and operational considerations
  • Monitor post-launch performance and make adjustments as needed.
  • Manage products through different lifecycle stages (introduction, growth, maturity, decline).
  • Identify strategies for extending product life or planning for end-of-life
  • Understand and apply data privacy laws and regulations (e.g., GDPR, CCPA).
  • Recognize ethical considerations in product development, including bias in AI, user data protection, and responsible design.
  • Develop guidelines for ethical decision-making in product management.
  • Integrate machine learning and artificial intelligence capabilities into products.
  • Design scalable and reliable IT product architectures (e.g., microservices, cloud-based solutions).
  • Develop and utilize APIs for product integration and extensibility.
  • Evaluate emerging technologies (e.g., blockchain, IoT, AR/VR) for potential application in product innovation.
  • Plan technical roadmaps to incorporate new technologies.
  • Grasp the role of product thinking in data projects and distinguish between project and product mindsets.
  • Conduct user research, develop user personas, and map user journeys.
  • Apply design thinking principles to create prototypes and iteratively improve them based on user feedback.
  • Align data projects with key business metrics and communicate technical insights effectively to stakeholders.
  • Implement agile methodologies (Scrum and Kanban) in data product development.
  • Integrate machine learning models into data products and design scalable data pipelines.
  • Develop go-to-market strategies and manage the product lifecycle effectively
  • Address ethical and compliance considerations in data product development, including data privacy and mitigating bias.
Course Contents

Course Contents

  • Foundations of Product. Management in IT
  • Strategic Analysis and Product Planning
  • User-Centric Approach and Product Design
  • Agile Methodologies and Development Management
  • Data and Analytics in Product Management
  • Product Launch and Growth Strategies
  • Product Lifecycle Management and Ethical Aspects
  • Technical Integration and Innovations in IT Products
Assessment Elements

Assessment Elements

  • non-blocking Assignments
  • non-blocking Final Project
Interim Assessment

Interim Assessment

  • 2024/2025 2nd module
    0.6 * Assignments + 0.4 * Final Project
  • 2024/2025 4th module
    0.3 * Rating of 2 modules + 0.3 * Assignments + 0.4 * Final project
Bibliography

Bibliography

Recommended Core Bibliography

  • Cagan, Marty. Inspired: How to Create Tech Products Customers Love. –Wiley, 2018. – ЭБС Books 24x7.

Recommended Additional Bibliography

  • 9781491953570 - Gothelf, Jeff; Seiden, Josh - Lean UX : Designing Great Products with Agile Teams - 2016 - O'Reilly Media - http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1352023 - nlebk - 1352023

Authors

  • Ахмедова Гюнай Интигам кызы