We produce a huge amount of data every second with our personal computers, phones, smart watches and home appliances. In order to imagine the magnitude of the amount of data produced, it is enough to remember the fact that we now produce more data every year than the total amount of data produced since the creation of mankind until the year 2000.
Today's business world is now a data-driven world. With the introduction of the Internet and other digital technologies, companies collect more data than ever before, and with integrated solutions, they can analyze forgotten data stuck in administrative departments throughout the company.
This recent data explosion has also brought with it some challenges and opportunities. Storing data correctly, revealing useful information, visualizing real-time data, and using information correctly in the process of making strategic and operational decisions have become very vital.
Ibn Haldun University Big Data and Business Analytics Master's Program is designed on three pillars for the purpose. The program cover business, data science and analytics. In Big Data and Business Analytics Master's program, we emphasize the practical application of knowledge and skills to effectively support students aspiring to advance their careers in data science, business analytics, business intelligence, and the big data fields. Business analytics at the strategic level, development of information at functional level, business analytics at the analytical level, descriptive analytics and applications, predictive analytics and applications, prescriptive analytics and applications are employed during the programme.
The MSc in Big Data and Business Analytics is designed to provide students with comprehensive knowledge and skills in processing big data to enable optimal decision-making, increased efficiency, and reduced costs. The program aims to provide fundamental concepts and tools used in data analytics, as well as various technologies used in the analysis of both large and small-scale data. Students will also acquire the ability to apply business data analytics technology and decision support systems effectively to solve real-world business problems.
Graduates of the MSc in Big Data and Business Analytics program will develop a unique skill set that is highly sought after in today's data-driven business landscape.
Prof. Selim Zaim
The dizzying developments in the field of technology; It has created a significant demand for human resources who have integrated knowledge in the fields of production, distribution, marketing and finance, have high managerial skills and are competent in data analysis.
In today's world, traditional methods are no longer sufficient to extract useful information from the large amounts of data obtained. For this reason, the purpose of the big data and business analytics program is;
Within the Big Data and Business Analytics Program
Topics such as will be given based on applications.
| IBN HALDUN UNIVERSITY SCHOOL OF GRADUATE STUDIES BIG DATA AND BUSINESS ANALYTICS (IN TURKISH) WITH THESIS PROGRAM COURSE PLAN |
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| I. Semester | |||||
| Course Code | Course Name | Hours | Credit | ECTS | |
| T | U | ||||
| BIA 502 | Veri Odaklı İşletme Yönetimi | 3 | 0 | 3 | 8 |
| BIA 503 | Uygulamalı İstatistik | 3 | 0 | 3 | 8 |
| BIA 521 | Dijital Pazarlama ve Pazarlama Analitiği | 3 | 0 | 3 | 8 |
| BIA… | Program Seçmeli | 3 | 0 | 3 | 8 |
| Total Credit | 12 | 32 | |||
| II. Semester | |||||
| Course Code | Course Name | Hours | Credit | ECTS | |
| T | U | ||||
| BIA 500 | Seminer | 3 | 0 | 0 | 3 |
| BIA 501 | Araştırma Yöntemleri ve Yayın Etiği | 3 | 0 | 3 | 8 |
| BIA 505 | R ile Yapay Zekâ ve İş Analitiği | 3 | 0 | 3 | 8 |
| BIA… | Program Seçmeli | 3 | 0 | 3 | 8 |
| BIA… | Program Seçmeli | 3 | 0 | 3 | 8 |
| Total Credit | 12 | 35 | |||
| III. Semester | |||||
| Course Code | Course Name | Hours | Credit | ECTS | |
| T | U | ||||
| BIA 599 | Yüksek Lisans Tezi | 0 | 0 | 0 | 30 |
| Total Credit | 0 | 30 | |||
| IV. Semester | |||||
| Course Code | Course Name | Hours | Credit | ECTS | |
| T | U | ||||
| BIA 599 | Yüksek Lisans Tezi | 0 | 0 | 0 | 30 |
| Total Credit | 0 | 30 | |||
| Overall Total Credit | 24 | 127 | |||
| COMPULSORY COURSES | |||||
| Course Code | Course Name | Hours | Credit | ECTS | |
| T | U | ||||
| BIA 500 | Seminer | 3 | 0 | 0 | 3 |
| BIA 501 | Araştırma Yöntemleri ve Yayın Etiği | 3 | 0 | 3 | 8 |
| BIA 502 | Veri Odaklı İşletme Yönetimi | 3 | 0 | 3 | 8 |
| BIA 503 | Uygulamalı İstatistik | 3 | 0 | 3 | 8 |
| BIA 505 | R ile Yapay Zekâ ve İş Analitiği | 3 | 0 | 3 | 8 |
| BIA 521 | Dijital Pazarlama ve Pazarlama Analitiği | 3 | 0 | 3 | 8 |
| DEPARTMENTAL ELECTIVE COURSES | |||||
| Course Code | Course Name | Hours | Credit | ECTS | |
| T | U | ||||
| BIA 504 | İş Analitiğinde Yeni Yaklaşımlar | 3 | 0 | 3 | 8 |
| BIA 510 | Pazarlama Analitiği | 3 | 0 | 3 | 8 |
| BIA 511 | Derin Öğrenme | 3 | 0 | 3 | 8 |
| BIA 512 | Optimizasyon için Nicel Yöntemler | 3 | 0 | 3 | 8 |
| BIA 513 | Karar Verme ve Veri Görselleştirme | 3 | 0 | 3 | 8 |
| BIA 514 | Büyük Veri Kullanımında Hukuk ve Etik | 3 | 0 | 3 | 8 |
| BIA 515 | Finansal Teknolojiler: Blok Zinciri, Kripto Paralar | 3 | 0 | 3 | 8 |
| BIA 516 | İşletmeler İçin Metin Madenciliği | 3 | 0 | 3 | 8 |
| BIA 517 | Gelir Yönetimi | 3 | 0 | 3 | 8 |
| BIA 518 | Makine Öğrenmesi | 3 | 0 | 3 | 8 |
| BIA 519 | Optimizasyon İçin Sezgisel Yöntemler | 3 | 0 | 3 | 8 |
| BIA 520 | Veritabanı Yönetim Sistemleri | 3 | 0 | 3 | 8 |
| ISL 510 | Yenilikçilik ve Girişimcilik | 3 | 0 | 3 | 8 |
| ISL 513 | Veri Analizi ve Karar Verme | 3 | 0 | 3 | 8 |
| ISL 519 | Tüketici Davranışları | 3 | 0 | 3 | 8 |
| ISL 520 | Marka İletişimi ve Stratejik Marka Yönetimi | 3 | 0 | 3 | 8 |
| ISL 522 | İş Süreçleri Analizi | 3 | 0 | 3 | 8 |
| ISL 527 | Veri Analitiği ve Yenilikçi Pazarlama | 3 | 0 | 3 | 8 |
| ISL 545 | Uygulamalı İşletme Stratejileri | 3 | 0 | 3 | 8 |
| ISL 547 | Sosyal İnovasyon İçin Veri Analitiği | 3 | 0 | 3 | 8 |
This course provides an environment for students to discuss and generate ideas on a variety of applied social research-related topics. Students conduct an in-depth study on a research topic of their choice, discuss problems with experts in the research field, work in discussion groups, debate and solve problems on selected topics. In the Seminar Course, students are given the opportunity to integrate the knowledge, skills and practical experiences they have acquired in the program.
The aim of this course is for students to develop their knowledge and understanding of research design and methodology, with a particular focus on quantitative research methods and ethical guidelines. The content of the course is as follows: (i) research methods, i.e. how to formulate a hypothesis and formulate a research question for it, how to design and carry out experiments to investigate a research question, how to analyze the results of an experiment and draw conclusions; (ii) research and publication ethics; that is, the ethical issues that arise when doing research and writing academic texts; (iii) how to write academic texts; that is, the style, organization, and outline of academic texts such as conference proceedings, journal articles, and theses.
Data, information and knowledge have always played a critical role in the business world. The amount of various data that can be collected and stored is increasing, so companies need new solutions for data processing and analysis. The course offers reflections on the concept of Big Data. The aim of the course is to show that Big Data analytics is an effective support in company management. Additionally, areas and activities where Big Data analytics can provide more effective support to companies will also be discussed.
This course provides the foundations of probability and statistics for data analysis in the research process. Topics include data collection using computers and statistical software, exploratory data analysis, random variables, joint discrete and continuous distributions, sampling distributions, estimation, confidence intervals, hypothesis testing, basic simulation and bootstrapping, distribution-free techniques, linear regression, analysis of variance, two-way tables are included.
With Web 2.0, companies have gained the ability to collect more data about their customers. Companies have the ability to correlate micro-level data they obtain about their customers' transactions with other data sets. The content of this course is to create powerful and simple statistical models that can be applied to this data to create useful forecasts for companies. The course will go beyond pattern identification, clustering, and correlation in data to create data-generating rational consumer behavior models. Therefore, the goal is to create a “model” of consumer behavior and apply that model to the data to test how accurate that model is and make adjustments if necessary. In addition, predicting what the results will be if the company changes strategy in line with the models obtained is also among the subjects of the course.
Students will gain familiarity with software platforms that provide artificial intelligence solutions. They will address problems from different business-related application areas and practically use artificial intelligence packages offered in R. Tools related to supervised learning, unsupervised learning, sentiment analysis will be presented to increase practical expertise.
This course aims to take a case-based approach to learning outstanding practices in marketing. Marketing analytics can be broadly defined as “the collection, processing and analysis of marketing-related data to make accurate business decisions.” This course covers practical topics such as segmentation, targeting, perceptual maps, product planning, market response models, campaign design and direct marketing.
The aim of this course is to provide students with the ability to use optimization techniques and numerical methods in business problems. The course will cover topics such as linear programming, integer linear programming, and population-based heuristic models. In the course, the use of these approaches in a business
This course provides a hands-on introduction to modern techniques for the field of data visualization and uses these techniques with the relevant problem-solving skills necessary to contribute to specific strategic decision-making. The student will learn to use data visualization package programs.
The following topics will be covered in the course. Introduction to Blockchain, Crypto and Cryptocurrencies. Virtual money mechanics: Virtual money printing, Virtual money mining and Virtual money transfer structure. Cryptographic building blocks used in blockchain. Anonymous Cryptocurrencies. Consensus Mechanisms. Smart Contract Technology. Other applications and use cases in Blockchain: Identity Management, Supply Chain, Logging systems, Certificate Management. Current Blockchain topics and publications.
In this course, participants will gain awareness about the sources, structure and dynamics of entrepreneurial innovation. Students will develop innovative ideas individually or in groups and gain the ability to apply these ideas to current problems in different industries. Topics to be covered within the course include topics such as entrepreneurial thinking, innovation management, recognizing and evaluating new opportunities, sector and market research, business strategy, business model and plan, financial forecasting and venture financing, access to resource providers, negotiation and starting new ventures. .
It aims to provide students with analytical modeling and statistical analysis techniques that can help the managerial decision-making process. The use of computer software to perform various analyzes is an integral feature of the course. The main topics to be covered are; decision analysis, statistical decision making, regression analysis, linear programming and simulation. The course also creates the infrastructure necessary for probability.
Examining consumer behavior, which is defined as people's decisions and related activities, especially in purchasing and using economic products and services, provides significant benefits to businesses in marketing and sales management, evaluation and analysis of market opportunities. The purpose of this course is to provide students with the knowledge and skills to accurately understand the needs, desires, desires, and purchasing reasons of target consumers and to develop a marketing program to satisfy their needs. The course will focus on customer-oriented culture in marketing, the importance of consumer behavior in marketing, creating customer satisfaction and customer loyalty, the phenomenon of consumption, needs and demands, the concept and characteristics of consumer behavior, consumer behavior and marketing strategy, consumers' purchasing behaviors and decisions, influencing consumers' purchasing behavior. It covers issues such as factors, purchasing decision process, and consumers' purchasing habits.
This course focuses on the importance of the role of the brand within the framework of integrated marketing strategies. The course focuses on topics such as what a brand is, why it is an important component, what it represents to consumers, and what institutions should do to manage them correctly. Additionally, students will learn about topics such as how brand value is created, how it is measured, and how it is used within the framework of global business development opportunities. Various brand simulations and case studies will also be used in the course.
This course is designed to introduce students to the fundamentals of business process analysis. Business processes exist throughout businesses and span many functional departments. While the concept of business processes is deceptively simple, the complexity lies in the details and the countless different ways companies structure these processes. After initially looking at business process analysis concepts, the main emphasis of the course will be on how the underlying information technology supports the management of business process innovation.
The purpose of this course is to provide businesses and executives with the foundation needed to apply data analytics to the real-world challenges they face daily in their professional lives. Students will learn to identify the ideal analytical tool for their specific needs; They will prepare for the future by understanding valid and reliable ways to collect, analyze and visualize data and use data to make decisions for their institutions, organizations or customers. Modern business analytics requires executives and managers to be familiar with programming and data architecture. This course will provide participants with the fundamental knowledge and practices needed to evaluate the challenges and opportunities associated with developing robust and scalable systems that are at the core of business analytics, emphasizing the importance of high-level concepts and design decisions. It also includes formulating critical management problems, developing relevant hypotheses, analyzing data, and most importantly, drawing inferences and telling compelling narratives to produce actionable results; It will cover measuring, analyzing and applying big data in marketing.
This course aims to develop students' conceptual skills in creating and implementing business strategies through simulation-oriented applications in a competitive market condition. It also aims to develop students' analytical thinking, communication skills, teamwork abilities and superior management skills (planning, organizing, leading and controlling) in a variety of challenging simulation-led scenarios.
buyukveri@ihu.edu.tr