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IS451

Digital Analytics Technology

1 CreditsBoth

Description

The Digital Analytics Technology (DAT) is a SMU course that will be delivered in collaboration with Google. This course is designed to equip students with essential knowledge and skillsets in digital analytics so that students can apply the skillsets into practical solutions for a real organization. Besides concepts related to digital marketing and analytics, relevant measurements and development of a strategy will be covered. The course will focus on helping students gain a good understanding of different aspects of digital analytics, such as effective dashboard visualisation, campaign and conversion tracking, by leveraging the Google Analytics Platform. Students will acquire techniques in text analytics and advanced analytics and make use of available AI services for developing feasible analytics solution for real-world problems.

Requisites

Prerequisites: ANLY104/IS217/MGMT108 - Pre-req

Co-requisites: None

Anti-requisites: None

Attributes

Department: SCIS

Course Level: Undergraduate

Tracks: IS/T4BS: Business Analytics Track

Areas: Advanced Business Technology Major Analytics Major Business Options Econ Major Rel/Econ Options IS Depth Electives IT Solution Development Electives Social Sciences/PLE Major-related Technology & Entrepreneurship

Learning Outcomes

1) Explain the scope of digital analytics and how it impacts business of an organisation 2) Identify business objectives, KPIs and performance targets 3) Explain the three phases - 1. installation (measurement strategy, site tracking documentation); 2. configuration (goal setup, campaign tracking); 3. Insights 4) Analyse the essential Google Analytics reporting on audience, acquisition and behaviour 5) Analyse campaign and conversion tracking 6) Explain the online advertisement ecosystems 7) Identify the key consideration for defining KPIs 8) Explain the concepts and processes required for ETL 9) Implement SQL commands 10) Extract relevant data using BigQuery and Python 11) Explain the techniques and best practices in visualising various types of data 12) Identify effective visualisation methods to present information 13) Explain the various analytics techniques and AI services and how they can be applied in analytics projects 14) Work as a group to deliver and present an analytics assignment 15) Write an executive report to highlight the analysis insights

Graduate Learning Outcomes

Multidisciplinary Knowledge, Interdisciplinary Knowledge, Critical thinking & problem solving, Innovation and enterprising skills, Collaboration and leadership, Communication, Intercultural understanding and sensitivity

Competencies

Data Analytics, Consumer Intelligence Analysis, Customer Behaviour Analysis, Integrated Marketing

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