Advanced Enterprise Data Management
Master enterprise data management strategies, from relational databases to big data technologies, in this comprehensive course.
Master enterprise data management strategies, from relational databases to big data technologies, in this comprehensive course.
This advanced course delves into the crucial role of high-quality information in successful business management. It covers the entire spectrum of enterprise data management, from operational processing systems to data warehouses and big data technologies. You'll learn to design and query relational databases, understand data quality issues, and master data management principles. The course explores data integration, data warehouse architecture, and data visualization techniques. You'll gain insights into data governance and learn to leverage both structured and unstructured data for decision-making. By the end of the course, you'll be equipped to implement comprehensive enterprise data management strategies that drive business advantage and potential.
3.9
(10 ratings)
Instructors:
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What you'll learn
Design and implement relational databases for operational systems
Master Structured Query Language (SQL) for querying relational databases
Understand and address data quality issues in enterprise settings
Implement data profiling and master data management techniques
Explore data integration strategies and data warehouse architectures
Develop effective data visualization skills using various graphical methods
Skills you'll gain
This course includes:
Live video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This comprehensive course covers the full spectrum of enterprise data management. It begins with the fundamentals of relational databases and SQL, progressing to advanced topics such as data warehousing, big data technologies, and data lakes. Students will learn about data quality management, data profiling, and master data management techniques. The course also covers data integration strategies, data warehouse architecture, and effective data visualization methods. A significant focus is placed on data governance, addressing key questions in managing enterprise data assets. Throughout the course, students will gain practical skills in designing databases, querying data, and creating impactful data visualizations. The curriculum balances theoretical knowledge with practical applications, preparing students to tackle real-world data management challenges in enterprise settings.
Fee Structure
Instructors
Expert in Healthcare Analytics and Business Intelligence Systems
Aaron Perry serves as a Senior Lecturer in the Operations and Decision Technologies department at Indiana University's Kelley School of Business, bringing extensive expertise in healthcare informatics and predictive analytics. His professional background includes significant experience in pharmacy consulting and algorithm development for both healthcare organizations and sports teams. Perry has made notable contributions to healthcare efficiency by developing sophisticated ranking algorithms that help pharmacists and physicians prioritize patient care based on case severity rather than proximity. His teaching portfolio encompasses business analytics, database management, and big data courses, with particular focus on enterprise data management frameworks. Perry's practical experience includes developing data-driven solutions that have improved clinical workflow efficiency, allowing healthcare providers to maximize patient care time. He specializes in sports information systems, data mining, predictive modeling, and health and clinical informatics. As an educator, he actively contributes to both undergraduate and graduate programs, teaching essential courses like Technology and Business Analysis (BUSK 303) and Enterprise Data Management, where he focuses on helping students understand complex data management frameworks and their practical applications in business settings.
Distinguished IT Professional and Data Analytics Educator
Jie Li is a Lecturer in the Operations and Decision Technologies department at Indiana University's Kelley School of Business, bringing over two decades of IT industry experience to academia. Her diverse educational background includes an MBA from Indiana University's Kelley School of Business, along with degrees in Computer Science and Law. Before transitioning to full-time faculty in 2017, she served as Director of Project Management and Data Services at the Kelley School of Business. Her expertise spans data analytics, software development, optimization and simulation modeling, data visualization, and database design. She teaches both undergraduate and graduate courses in various formats, covering enterprise data management, data mining, machine learning, programming, and information systems. As a member of the Center for Learning Analytics and Student Success since 2017, she has contributed to multiple research projects examining factors influencing student success and course sequencing. Her practical experience and academic expertise enable her to bridge theoretical concepts with real-world applications in her teaching
Testimonials
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3.9 course rating
10 ratings
Frequently asked questions
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