Masters In Data Science And Business Analytics In Canada – In a data-driven economy, harnessing the power of business analytics can help you create meaningful insights and make strategic and ethical decisions that will improve your organization and your career.
Businesses and institutions of all sizes are using the power of data analytics to innovate and make better decisions. Having the skills to understand how to analyze data and apply it to your industry can help you excel in data-driven organizations. The Master of Science in Business Analytics from the School of Business and Society gives you a unique edge by developing your business skills and analytical decision making.
Masters In Data Science And Business Analytics In Canada
The 18-month STEM-Designated MSBA program is designed for a variety of student backgrounds and experiences to gain critical business and technical skills that are highly valued in this rapidly growing field. A quantitative bachelor’s degree or quantitative course is not a requirement to apply. However, it is highly recommended to study or understand the basics of statistics to be successful.
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As a student of the School of Business and Society, you are welcomed by a network of 30,000+ students and are invited and encouraged to attend speaker series events and activities on a variety of contemporary business topics, including purposeful and ethical leadership.
A prerequisite for all other MSBA courses, this course introduces students to the MSBA curriculum and the graduate-level approach to academic engagement offered at the University’s School of Business and its unique learning community.
This course assesses the ethical, social, and legal validity of the choices we make at different stages of data analysis and information privacy, and the implications of those choices for management decision-making.
This course examines organizational contexts for business analysis. It focuses on creating competitive advantage in business functions such as marketing, operations, finance, human resources, R&D, and supply chain through the strategic use of analytics.
Master Of Science In Business Analytics Practicum Program
This course provides an in-depth understanding of data, data technology, and the techniques necessary for effective analysis. The course also includes basic concepts and skills to effectively manage, clean, integrate, preprocess, and transform analytical data using industry-standard tools such as Python or R.
This course evaluates the role of information analysis, statistical measures and visualization, in delivering organizational value to decision-making contexts. Coursework includes the use of spatio-temporal data for “storytelling” and effective communication of results to organizational decision makers.
This course focuses on descriptive analysis and forecasting for decision making from different business disciplinary perspectives. Key components include identifying contexts for data-driven decision-making in business, defining data needs, analyzing data, interpreting and communicating results, and ultimately the value proposition of analytics.
This course provides an overview of data mining concepts, processes, and popular techniques in a business context. Supervised and unsupervised approaches are used using large, real-life business databases, and statistical modeling and machine learning support provided by the software. Spatial data mining, privacy issues, and data mining pitfalls are discussed.
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This course provides students with an understanding of the role of prescriptive analysis in organizational decision making. Topics include quantitative methods such as optimization, simulation, forecasting, supply chain management and project management to create value in business operations.
This course focuses on the role of accounting and finance in managerial decision making, including how managers acquire capital, invest in resources, budget performance and report economic events.
Students are introduced to the basics of location analysis, including location value and spatial maturity and growth in business performance. Moving from the basics, the course focuses on the marketing domain with a focus on the marketing use of GIS and location analytics to increase customer value by understanding, exploring, and predicting the needs and preferences of the modern customer. Topics include environmental analysis, market segmentation, target marketing and promotion, and integrated marketing plan development using GIS as an analytical tool. This course may be substituted for GISB 691: Introduction to Location and Marketing Analysis.
This course focuses on decision making using various stages of the geographic value chain in businesses using GIS and geographic analytics. Emphasis is on the process models by which GIS projects and spatial analysis and business applications are planned, developed and implemented. Topics include spatial analytics and spatial enablement in business, spatial decision support, spatial analytics to explore big data, social networks, the Internet of Things, mobile technologies and their spatial aspects, and costs, benefits, risks, and ethical implications of space projects and applications. This course may be substituted for GISB 694: Location Analysis and Decision Making.
Master Of Science (msc) In Big Data And Business Analytics
This course provides an overview of financial management tools used in analyzing and developing strategies for making business decisions. Topics include the time value of money, securities and stock valuation, risk and returns, capital budgeting, capital structure and dividend policy, working capital management, options, and their applications in corporate finance.
An examination of the strategic planning process, with an emphasis on resource allocation decisions driven by marketing analysis. Focus on the use of quantitative and data analysis tools to define the best marketing mix, conduct effective customer analysis and digital marketing campaigns, as well as integrate spatial thinking into decision making. This course may be substituted for MGMT 683: Marketing Analytics.
This course examines the theoretical and practical concepts of geographic and economic relations to assess the impact of globalization on business. It aims to assess and develop strategic responses to various political, economic, and social factors regarding the risks presented to international trade and investment, resource allocation decisions, and organizational structures. This course may be substituted for INTB 670: International Area Studies.
This course focuses on key business areas such as managing individual performance, team and group dynamics, leadership, human resource management, organizational structure, decision making, and change management.
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This course examines the key elements of marketing with an emphasis on the customer and the marketing mix and includes the development of analytical and critical thinking skills through case studies, and the design and evaluation of a basic marketing plan.
This course is the culmination of the MSBA program and includes an applied analytics project. Using knowledge gained throughout the program, students work on a real-world project that requires the strategic deployment of analytics. Emphasis is on improving decision making and communicating value derived from analytics. For the academic year 2022/23, applications for admission to the Business Analytics and Data Science programs are open from 1 March to 2 May 2022.
Since 2020, the University of Vienna offers three integrated major programs that focus on the basics of data science (Master in Data Science), interaction with business and economics (Master of Business Analytics) as well as interaction with the humanities (Master of Digital Humanities). . The first two (Statistical Science and Business Analytics) are taught in small groups in English and therefore, have a competitive application process, open to international applicants. The current batch includes students from 38 countries. Applications are open from 1 March to 2 May 2022 and notifications are scheduled to be sent by the end of June 2022.
Application for admission to our main programs Business Analytics and Data Science is possible only once a year within the application period. 40 university places are available per program and per academic year.
Master In Business Analytics And Big Data
The purpose of the Master’s Program in Business Analytics is to familiarize students with predictive and prescriptive analytics techniques and tools needed for business analytics and decision support. The courses will cover how to solve and interpret business decision problems using multiple data sets and make recommendations for action. The field of Business Analytics requires a high level of analytical thinking. The Master’s program will provide an in-depth understanding of the theoretical and practical concepts of statistics, operations research, data science, and information systems design.
The purpose of the Master’s program in Data Science is to provide a practically oriented and scientific education in the field of modern data science. The courses will teach innovative methods in data processing, which you can use in all fields of science and economics. The Master of Data Science at the University of Vienna includes the teaching of all basic skills from the development of efficient algorithms as well as understanding the interpretation, over-reliability of results and asking ethical and legal questions.
As the Business Analytics, Data Science and Digital Humanities programs are designed together, students of all three programs complete the same course content in one semester. Courses offered by the students’ various disciplinary areas allow for a broad interdisciplinary exchange and include the following content:
The purpose of the Master’s Program in Digital Humanities is to train students who will make a significant contribution to the development, anchoring and critical reflection of computational methods in humanities research. After learning how to process and evaluate text, images and other data related to a digital discipline, courses will teach you how to make sense of available data to create new interdisciplinary content. Expected topics during your studies include Digital Humanities, Digital Humanities Theory and Practice, and Specialization in Digital Humanities Groups. Acceptance of Digital Humanities is possible each semester. Data-driven decision-making and the ability to effectively communicate large amounts of information to an audience are essential in any industry. Bringing data to life in meaningful ways
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