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MS DB Proposal Scott Canaan B. Thomas Golisano College of Computing & Information Sciences.

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Presentation on theme: "MS DB Proposal Scott Canaan B. Thomas Golisano College of Computing & Information Sciences."— Presentation transcript:

1 MS DB Proposal Scott Canaan (srcdco@rit.edu) B. Thomas Golisano College of Computing & Information Sciences

2 Advanced Certificate in Database Administration – Fall, 2007 4 courses (16 credits) –Data Object Development –System Administration –Fundamentals of DBMS Architecture and Implementation –Database Performance and Tuning

3 MS in Database (Proposal) * = course in development Program prerequisites: –1 year object oriented programming –Statistics (recommend “Statistics for Data Mining”)

4 Core Courses (24 credits) –Object Technologies This is a course in the principles and techniques of designing and implementing software objects. Current software environments are used to explore effective design methods and concepts. Topics include basic object design, class definition and syntax, object- oriented design, software quality and object evaluation. Software design and programming projects are required. –Data Object Development Introduction to analysis and design of data representations and data object implementation. Current software environments are used to explore effective database design and implementation concepts. Topics include conceptual modeling, methodologies, logical/physical database design, data query and manipulation, and transaction design. Database design and implementation project is required.

5 –Data Architecture & Management This course will focus on data architectures, issues, and strategies for managing enterprise data as an organizational information asset. The fundamental meaning and management of data is emphasized as an enabler to enterprise data integrity, enterprise data structure, and satisfaction of enterprise business requirements. Topics include metadata management, business process integration, data and process governance, repository management, data quality, data architectures, and current technologies in information exchange. Data integration and programming projects are required. –*NIX Fundamentals Students will use a Unix-like operating system as it pertains to the support of web, application and database systems. This course allows students to explore design requirements for production servers as applied to domain areas such as web servers, web services, database applications and multimedia content distribution. Topics will include: file system organization and permissions, user interfaces, package management, and services.

6 –Fundamentals of DBMS Architecture and Implementation Students will be introduced to issues in client/server database implementation and administration. Topics such as schema implementation, storage allocation and management, user creation and access security, transaction management, data backup and recovery, and performance measurement and enhancement will be presented in lecture and investigated in a laboratory environment. Students will configure and demonstrate successful management of a database server for client access. –Data Quality *

7 3 tracks: –Data Analytics –Database Administration –Data Architecture

8 Data Analytics requirements: –Data Warehousing This course covers the purpose, scope, capabilities, and processes used in data warehousing technologies for the management and analysis of data. Students will be introduced to the theory of data warehousing, dimensional data modeling, the extract/transform/load process, warehouse implementation, dimensional-data analysis, and summary-data management. The basics of data mining and importance of data security will also be discussed. Hands-on exercises include implementing a data warehouse. –Introduction to Data Mining This course provides an introduction to the concepts and techniques used in the field of data mining. The course covers the knowledge discovery process that included data selection, cleaning, coding: different statistical, pattern recognition, and machine learning techniques: and reporting and visualization of general structures. Computing projects, a term paper, and presentations are required.

9 –Business Intelligence / Data Presentation * This course covers the purpose, scope, capabilities, and processes used in data warehousing technologies for the management and analysis of data. Students will be introduced to the theory of data warehousing, dimensional data modeling, the extract/transform/load process, warehouse implementation, dimensional-data analysis, and summary-data management. The basics of data mining and importance of data security will also be discussed. Hands-on exercises include implementing a data warehouse. –Elective (Statistics for Data Mining recommended) –Elective (one “Special Topics” course)

10 Database Administration requirements: –Database Performance & Tuning Students will explore database theory as it applies to the performance and tuning of database systems. Topics in database performance will be explored including: physical and logical design issues, the hardware and software environment, SQL statement execution, and front-end application issues. Techniques in performance monitoring and tuning will be investigated. –Secure Database Systems This course explores policies, methods and mechanisms for protecting enterprise data. Topics include data reliability, integrity, and confidentiality; discretionary and mandatory access controls; secure database architectures; secure transaction processing; information flow, aggregations, and inference controls, and auditing; security models for relational, object- oriented, statistical, XML, and real time database systems. Programming projects are required. –Special Topics in Enterprise Database and Technologies * –Elective

11 Data Architecture requirements: –Secure Database Systems This course explores policies, methods and mechanisms for protecting enterprise data. Topics include data reliability, integrity, and confidentiality; discretionary and mandatory access controls; secure database architectures; secure transaction processing; information flow, aggregations, and inference controls, and auditing; security models for relational, object-oriented, statistical, XML, and real time database systems. Programming projects are required. –Special Topics in Unstructured Data Management *

12 –Fundamentals of Database Client / Server Students will investigate strategies for client-server and server- server communication against single or multiple database servers. Specifically, students will configure, test, and demonstrate successful communication between multiple database servers and multiple clients. Similarities and differences between commercially available connectivity packages, and issues impacting performance will be explored. Programming exercises are required. –Information Assurance This course provides an introduction to the topic of information assurance as it pertains to awareness of the risks inherent in protecting digital content in today’s networked environments. Topics in secure data and information access will be explored from the perspectives of software design, data storage, and network communications. Current software exploitation issues and techniques for information assurance will be investigated. –Elective

13 Electives: –CS Seminars – Active Data Systems / Sensor Network Data / Advanced Data Mining Current topics in the field. the format of this course is a combination lecture and seminar. Students may register for this course more than once. Topics covered each quarter will focus on current developments in database and transaction systems; covered areas could include, for instance, data mining, or secure database systems, or temporal database systems, or secure transaction processing. Programming projects are required. –GIS Course (from CAST) –Data Cleaning and Preparation This course provides an introduction to the concepts and techniques used in preparing data for subsequent data mining. Topics include the knowledge discovery process; data exploration and its role; data extraction, cleaning, integration and transformation; handling numeric, unstructured, text, web, and other forms of data; and ethical issues underlying data preparation and mining. Computing projects, a term paper and presentations are required. –Information Assurance * –Statistics for Data Mining *

14 Possible advanced topics: –Geospatial data –Handling XML –Unstructured data – BLOB / metadata tagging –Bioinformatics –Embedded databases –Persisting data – Object relational mapping –Physical design – BCNF never deployed / partitioning / indexing

15 Advanced topics continued: –Physical data storage –Solid state memory – caching –Enterprise content management –Data security –Data grids and clustering –Managing rich content –Information lifecycle management

16 Advanced Topics continued: –Event management –Games data management –VLDB –Managing individual data – across enterprise and outside of enterprise –Computing in the “cloud” –Media – particularly interactive media –Social computing

17 Suggestions? Ideas? Did we miss anything important?


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