University of Technology Sydney

36101 Leading Data Science Initiatives

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2021 is available in the Archives.

UTS: Analytics and Data Science: Transdisciplinary Innovation
Credit points: 8 cp

Subject level:

Postgraduate

Result type: Grade, no marks

There are course requisites for this subject. See access conditions.

Requisite elaboration/waiver:

Any student wishing to enrol in first- and second-year subjects concurrently, needs to apply for a waiver.

Description

This subject focuses on leadership in data environments, management methods and approaches for successful delivery of data initiatives. The project lifecycle is considered in terms of outcome delivery, and integrated with the data management lifecycle and principles. Project management methodologies are explored, as well as methods for planning and execution of data projects. Delivery frameworks and specific deliverables are produced that facilitate a common understanding of the scope, time and cost dimensions of data-driven projects. Documentation and artefacts play a key role in ensuring students can reproduce initial results and communicate development pathways taken during the life of data initiatives. Students also explore the importance of organisational structure in leveraging the data an organisation acquires, processes and stores, as well as project leadership, including stakeholder engagement, communications, team and performance management. In this subject, students develop an understanding of a data management plan, data infrastructure and policies driving the control of data and its lifecycle. Students are also challenged to consider the range of issues related to handling data within the context of project delivery including privacy, security, data preservation, ethics, data storage and data distribution. The subject involves group and individual exercises, as well as the opportunity to work with business clients on real-life data challenges.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:

1. Apply and adapt project management global best practices for specific data related project contexts to build capability in organisations.
2. Integrate the data management lifecycle with tailored project delivery frameworks and deliverables for successful outcomes across different industries and projects.
3. Design and construct project initiation and planning artefacts for a data driven project that define basic project dimensions and associated structures, governance, resources and risks.
4. Design and implement artefacts to successfully manage a data-driven project team, communicate progress to stakeholders and ensure effective delivery of outcomes.
5. Evaluate the impacts of community, organisational or cultural contexts on project structure, governance, delivery and engagement for differing stakeholders.
6. Identify and justify the resource requirements and business case for a specific project case study to support data science capability.
7. Evaluate the ethical and delivery risks for data projects and take a leadership role in recognising and addressing issues for data driven projects and their outcomes.

Course intended learning outcomes (CILOs)

This subject also contributes specifically to the development of the following course outcomes:

  • Understanding relationships & processes within systems
    Identify and represent the human and technical elements and processes within complex systems and organise them within frameworks of relationships (1.1)
  • Developing strategies for innovation
    Explore, interrogate, generate, apply, test and evaluate problem-solving strategies to extract economic, business, social, strategic or other value from data (3.1)
  • Examining and articulating data value
    Critically examine the perceived value of data analytics outcomes and clearly articulate implications for different stakeholders and organisations (3.2)
  • Working together
    Develop a collaborative and team-oriented mindset to harness value for stakeholders to produce innovative solutions to challenges (3.3)
  • Becoming a reflective data practitioner
    Engage in active, reflective practice that supports flexible navigation of assumptions, alternatives and uncertainty in professional data science contexts (5.1)
  • Embracing ethical responsibilities
    Interrogate and justify ethical responsibilities related to data selection, access, analysis and governance to create a framework for practice (5.2)
  • Leading data science
    Take a leadership role in promoting positive change in data science contexts, recognising individual, organisational and community issues (5.3)

Teaching and learning strategies

Blend of online and face to face activities: This subject is offered through a series of block sessions and blends online with face-to-face learning. Students participate in interactive learning experiences in timetabled on-campus sessions, where they make use of the subject materials that they have already engaged with online. In between campus sessions, students will engage in individual and collaborative online activities designed to consider a range of challenges associated with big data and innovation.

Collaborative work: A strong emphasis is placed on group activities and interaction, given that graduates of this course will need to approach professional projects and challenges from a collaborative and consensus position. Insights obtained and developed within the groups is then reworked by individual students to develop the final summative assessment activity. Group assessments and activities enable students to leverage peer-learning and demonstrate effective project and team leadership and participation. This contributes to learning outcomes in the areas of team work, communication and people management.

Transdisciplinary approaches: Starting from an elemental perspective on project management practices and how these can be applied to data-driven projects, students will approach learning from their specific professional and potential future contexts. As the subject progresses students will develop the skills required to tailor and apply project management best practise within specific data-driven project contexts.

Simulated real life experience: Case studies and insights from industry experts will provide 'lived experiences' to accelerate and consolidate student learning. Students will have opportunities to select a case study or to develop a specific work related case study that will contextualise learning outcomes.

Weekly study and preparation activities, as well as detailed assessment information are provided in Canvas.

Content (topics)

  • Project Management Principles
  • Managing teams, stakeholder communication
  • Data projects, roles and organisational structure
  • Data projects lifecycle, technical and organisational environment, dynamics, assets and standards
  • Data projects and governance
  • Outcome-driven data solutions (projects) delivery
  • Innovation and disruption in data project environment
  • Systems development and data projects methodologies (focus on Agile)
  • Strategic alignment, procedural/audit compliance
  • Security, quality, delivery and integration challenges
  • Data projects delivery in operational environment - focus on integration with legacy systems and data stores
  • Case projects review.

Assessment

Assessment task 1: Project Delivery Framework for a Major Data Project

Objective(s):

1, 2, 3, 4 and 6

Type: Project
Groupwork: Group, individually assessed
Weight: 50%
Length:

Part A: 1500 words. Part B: 20 pages.

Assessment task 2: Weekly Group Discussions

Objective(s):

5 and 7

Type: Journal
Groupwork: Group, group assessed
Weight: 20%
Length:

300 words per submission

Assessment task 3: Team Facilitation, Communication and Leadership

Objective(s):

1, 4 and 6

Type: Report
Groupwork: Individual
Weight: 30%
Length:

3000 words

Minimum requirements

Students must attempt each assessment task and achieve an overall pass mark in order to pass this subject.

Late penalties apply to all assessment tasks as outlined in the FTDi FYI student booklet. Please consult this booklet for other useful information including Special Consideration, Plagiarism, Extension, and Student Support Services.

A minimum of 80% of attendance of classes (as outlined in the timetable) is required.

Recommended texts

Texts
There is no recommended text book that covers the entire subject, but there are several references that are useful for each topic that will be covered in this subject.

A Guide to the Project Management Body of Knowledge (PMBOK® Guide), Newtown Square PA, Project Management Institute, 2013, 5th edition, ISBN: 978-1-935589- 67-9

Recommended References and Standards

AIPM (Sponsor), Professional Competency Standards for Project Management. Sydney, Australian Institute of Project Management, June 2008, 2nd edition. Available for free from the AIPM’s website www.aipm.com.au or you can download from the eLearning site.

Professional Competency Standards for Project Management. Sydney, Australian Institute of Project Management, June 2008, 2nd edition

Guide to the Software Engineering Body of Knowledge, 2004, The Institute of Electrical and Electronics Engineers, ISBN: 0-7695-2330-7 – New edition under review at present

The following Australian Standards related to Project Management and very useful You can download these for free by going to the library or using the links provided in the eLearning environment. Alternatively, you can purchase any of these standards online via the Standards Australia website – www.standards.com.au or www.saiglobal.com.

Reading

Project Quality Standard AS ISO 10006

Risk Management Companion HB4360-2005 (check)

Risk Management Standard AS/NZS ISO 31000:2009 (check)

Any data related standards

Recommended Readings

Managing Change in Organizations: A Practice Guide, Newtown Square PA, Project Management Institute, 2013, ISBN: 9781628250152

The Minto Pyramid Principle: Logic in Writing, Thinking and Problem Solving, Minto, B, 2010, Minto Books International, ISBN: TBA

Succeeding with Agile – Software development Using Scrum, Cohn, M, 2009, ISBN: 9780321579362

Managing Successful Projects with PRINCE2 Manual, 2009. ILX Group, ISBN: 978-0- 113310-59-3

Scrum Shortcuts without Cutting Corners, Ilan Goldstein, 2014, Addison-Wesley, ISBN:978-0-321-82236-9 10

Class Curated Readings

Students will undertake online research and share references and articles during the semester with a view to preparing a curated suite of references and readings for all students to share.

Here are some staring points from major research journals including Project Management Journal, Information Systems Management, International Management Review:

Shrnhur, Aurmi J., O. Levy, and D. Dvir. "Mapping the dimensions of project success." Project management journal 28.2 (1997): 5-13.

Ika, Lavagnon A. "Project success as a topic in project management journals." Project Management Journal 40.4 (2009): 6-19.

Pinto, Jeffrey K., and Samuel J. Mantel Jr. "The causes of project failure." Engineering Management, IEEE Transactions on 37.4 (1990): 269-276.

Kappelman, Leon A., Robert McKeeman, and Lixuan Zhang. "Early warning signs of IT project failure: The dominant dozen." Information systems management 23.4 (2006): 31-36.

Ivory, Chris, and Neil Alderman. "Can project management learn anything from studies of failure in complex systems?." Project Management Journal 36.3 (2005): 5.

Al-Ahmad, Walid, et al. "A taxonomy of an IT project failure: Root Causes." International Management Review 5.1 (2009): 93.

Murphy, Justin P. "E-Discovery in Criminal Matters—Emerging Trends & The Influence of Civil Litigation Principles Post-Indictment E-Discovery Jurisprudence." Sedona Conf. J.. Vol. 11. 2010.

Additional References

Managing Change in Organizations: A Practice Guide, Newtown Square PA, Project Management Institute, 2013, ISBN: 9781628250152

The Minto Pyramid Principle: Logic in Writing, Thinking and Problem Solving, Minto, B, 2010, Minto Books International, ISBN: TBA

Scrum Shortcuts without Cutting Corners, Ilan Goldstein, 2014, Addison-Wesley, ISBN:978-0-321-82236-9

Kerzner, Harold R. Project management: a systems approach to planning, scheduling, and controlling. John Wiley & Sons, 2013.

Schwalbe, Kathy. Information technology project management. Cengage Learning, 2015.

Volonino, Linda, and Ian Redpath. e-Discovery for Dummies. John Wiley & Sons, 2009.

Shepherd, Elizabeth, and Geoffrey Yeo. Managing records: a handbook of principles and practice. facet publishing, 2003.

Rubenstein-Montano, Bonnie, et al. "A systems thinking framework for knowledge management." Decision support systems 31.1 (2001): 5-16.