DTAN - Data Analytics

This course introduces students to general principles of data analysis and business analytics for business problem solving. Topics covered include the general process of data analytics, data sources, validation, selection, and statistical analysis. Students will learn how to optimize, predict, forecast, and visualize data for presentation development. Emphasis on working with data software tools along with understanding the importance and associated risks will be presented. Essential technologies in data analytics like databases, Big Data, and knowledge management will be covered. Students will learn how to think critically about using data and applying general concepts and tools in data analysis for insights and knowledge. The creation of statistical narratives and visual presentations that reflect data analyses interpretation used in business decision-making will be addressed. Students will apply biblical and ethical principles to concepts covered in this course. Prerequisite: STAT-535

This course introduces students to general principles of data visualization for business problem solving. Topics covered include data summarization, graphing, and presentation techniques. Students will learn how to think critically about the ways to properly visualize data. The creation of a statistical narrative to gain insights that only a visual representation can do well. Emphasis on working with data while understanding the importance and associated risks of misinterpretation will be presented. Students will apply biblical and ethical principles to visualization concepts covered in this course.

This course introduces students to general principles of data manipulation and statistical software for business problem solving. Topics covered include data preparation, Structured Query Language (SQL), and other software tools. The creation of statistical narratives to gain insights using common statistical methods will be supported with appropriate software tools. Students will work with data and complete statistical analyses needed for data mining. Students will apply biblical and ethical principles to data sources and systems.

This course introduces the life cycle, data types, datasets, data analysis, and data analytics involved in Big Data. Students are introduced to the motivations and benefits for business in adopting Big Data. Big Data enterprise technologies, data warehouses, data marts, and business intelligence (BI) will be covered. The course addresses storage, processing technologies, and database applications for Big Data. Three fundamental techniques for Big Data Analysis will be presented in the course. Students will apply biblical and ethical principles related to Big Data concepts, technology, and applications. Prerequisites: DTAN-500 and STAT-535

In this course, basic concepts and theory in text mining applications will be presented. Students will learn how natural language processing can collectively capture, classify, and interpret words and their contexts. State-of-the art algorithms and techniques in clustering, classification, anomaly, event detection, and stream analysis for text mining will be presented. Students will learn to investigate linguistic, statistical, and machine learning analysis methods and techniques for modeling information in textual sources. The fundamental theory of text analytics, such as, information retrieval, text extraction, natural language processing, text classification, text clustering, and software algorithms will be addressed. Current research on how text mining techniques are applied in social media platforms and cybercrime prevention will be presented. Advancements in automated text analysis, mining and visualization techniques based on machine learning, knowledge discovery, and natural language processing will be discussed. Information retrieval models and algorithms used in text mining processes and applications will be explored. Students will apply biblical and ethical principles to text mining concepts and processes. Prerequisites: DTAN-500 and STAT-535

The Data Mining Concepts course will present concepts and methods on data mining to gain insights relevant to meet business needs. Students will learn how to discover data set patterns utilizing pattern recognition technologies, mathematical and statistical methods, programming, and database systems, which are critical to analysis and mining development. The basic concepts of data warehousing and tools used to help discover key information from collected data will be addressed. Students will learn methods for pattern evaluation, data classification, and clustering analysis. Biblical and ethical principles will be applied to data mining concepts and processes throughout the course. Prerequisite: Successful completion of all program courses.

This course will focus on introducing students to the Python programming language while exploring preprocessing different types of data from files or databases. Students will learn how to prepare and analyze data that will be used in data analysis to support business decision making and solutions. The Structured Query Language (SQL) in database operations will also be explored. Students will learn how SQL works with other programming languages and relational databases for data preparation, exploration, processing, and reporting functions. Using SQL to query, modify, process, and present results will be addressed. Students will also be introduced on how SQL, database and programming languages, such as Python or R, work together to prepare, analyze, and report data results. Students will apply a biblical worldview and ethical framework to data preparation and reporting concepts. Prerequisites: DTAN-500 and STAT-535

This course introduces students to general principles of utilizing data mining concepts to help with business decision-making. Students will learn how to use data models, find and summarize data patterns that identify issues and help shape solutions. Analytical techniques and technologies used for proposal preparation will be presented. Modeling and merging business strategy with data science concepts and its impact on competitive advantage will be addressed. Students will apply a biblical worldview and ethical framework to data analytics consulting practices. Prerequisites: DTAN-500 and STAT-535

This course is designed to integrate the content, tools, and techniques from core program courses into a culminating project. The project will focus on developing and writing a business solution proposal based on the project and data analysis results. Students will apply data analytics concepts such as: source identification, acquisition, extraction, cleaning, and preparation on a dataset. As part of the project development, students will utilize data analysis, visualization, text mining, and data mining. SQL and relational databases, Python programming, and R programming software will be used to support the project. Students will apply a biblical worldview and an ethical framework in the development and finalization of their project. Prerequisites: Successful completion of all program courses

In this course students further develop and refine the application of Data Analysis theory. Students will draw on critical and creative mastery of their choice of concepts by demonstrating advance application through a specific deliverable approved by the instructor. These may be either data visualization, data sources or systems analytics, big data, data mining, or another approved topic. This course can be repeated up to four times, provided the repeat includes a topic area not previously submitted.

This course advances student learning of principles of data visualization for business problem solving. Topics covered include data summarization, graphing, and presentation techniques. Students will think critically about the ways to properly visualize data. The creation of statistical narratives to gain insights into visual representation will be discussed. Emphasis on working with data while understanding the importance and associated risks of misinterpretation will be presented. Students will apply biblical and ethical principles to visualization concepts covered in this course. Students who completed DTAN-505 will be required to take DTAN-701 in order to apply concepts at the doctoral level.

This course advances student learning on principles of data manipulation and statistical software for business problem solving. Topics covered include data preparation, Structured Query Language (SQL), and other software tools. The creation of statistical narratives to gain insights using common statistical methods will be supported with appropriate software tools. Students will work with data and complete statistical analyses needed for data mining. Students will adapt biblical and ethical principles to use of data sources and systems. Students who completed DTAN-510 will be required to take DTAN-701 in order to apply concepts at the doctoral level.

This course advances learning in the life cycle, data types, datasets, data analysis, and data analytics involved in Big Data. Students evaluate the motivations and benefits for business in adopting Big Data. Big Data enterprise technologies, data warehouses, data marts, and business intelligence (BI) will be addressed. The course presents storage, processing technologies, and database applications for Big Data. Fundamental techniques for Big Data Analysis will be presented in the course. Students will adapt biblical and ethical principles related to Big Data concepts, technology, and applications. Students who completed DTAN-515 will be required to take DTAN-701 in order to apply concepts at the doctoral level.

The Data Mining Concepts course will advance learning of concepts and methods on data mining to gain insights relevant to meet business needs. Students will examine dataset patterns utilizing pattern recognition technologies, mathematical and statistical methods, programming, and database systems, which are critical to analysis and mining development. Data warehousing and tools used to help discover key information from collected data will be explored. Students will consider and utilize methods for pattern evaluation, data classification, and clustering analysis. Biblical and ethical principles will be adapted data mining concepts and processes throughout the course. Students who completed DTAN-525 will be required to take DTAN-701 in order to apply concepts at the doctoral level.

In this course students further develop and refine the application of Data Analysis theory. Students will draw on critical and creative mastery of their choice of concepts by demonstrating advance
application through a specific deliverable approved by the instructor. These may be either data visualization, data sources or systems analytics, big data, data mining, or another approved topic. Prerequisites: Successful completion of DTAN-505, DTAN-510, DTAN-515 and DTAN525 or DTAN-705, DTAN-710, DTAN-715 and DTAN-725

In this course, students further develop and refine their voices as scholar-practitioners through active exchange within communities of practice and scholarship. Students will draw on critical and creative mastery of a broad range of concepts, theories, and practices, as well as be aware of the assumptions underlying them from perspectives which go beyond individual disciplines and contexts. Grounded in theory and research, informed by experiential knowledge, motivated by personal values, and through the lens of a virtuous worldview, students will synthesize new business administration knowledge and skills for application in the global workplace. These reflect solutions to real-world business administration problems using new applications of theory or changes in present practice. Students will develop skills to effectively communicate their findings in a variety of formats including peer-reviewed written or oral venues. Prerequisite: Completion of all other required DBA program courses with the exception of BADM-785 and BADM-792.