Data Warehousing and Data Mining - Syllabus
Embark on a profound academic exploration as you delve into the Data Warehousing and Data Mining course () within the distinguished Tribhuvan university's CSIT department. Aligned with the 2065 Syllabus, this course (CSC-451) seamlessly merges theoretical frameworks with practical sessions, ensuring a comprehensive understanding of the subject. Rigorous assessment based on a 60+20+20 marks system, coupled with a challenging passing threshold of , propels students to strive for excellence, fostering a deeper grasp of the course content.
This 3 credit-hour journey unfolds as a holistic learning experience, bridging theory and application. Beyond theoretical comprehension, students actively engage in practical sessions, acquiring valuable skills for real-world scenarios. Immerse yourself in this well-structured course, where each element, from the course description to interactive sessions, is meticulously crafted to shape a well-rounded and insightful academic experience.
Units
Key Topics
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Compiler Structure
UN-1.1Analysis and Synthesis Model of Compilation, including different sub-phases within analysis and synthesis phases.
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Compiler Concepts
UN-1.2Basic concepts related to Compiler, including interpreter, simple One-Pass Compiler, preprocessor, macros, symbol table, and error handler.
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Institutional Infrastructural Preparedness
UN-1.3Institutional infrastructural preparedness refers to the readiness of government agencies and institutions to adopt and implement e-governance systems.
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Human Infrastructural Preparedness
UN-1.4Human infrastructural preparedness involves the development of skills and capacities of public officials and citizens to effectively use e-governance systems.
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Technological Infrastructural Preparedness
UN-1.5Technological infrastructural preparedness refers to the availability and quality of technology infrastructure, including computers, internet connectivity, and other digital tools.
Key Topics
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E-readiness
UN-1E-readiness refers to the state of preparedness of a country or organization to participate in the digital economy. It involves assessing the availability and quality of digital system infrastructure, legal frameworks, institutional arrangements, human resources, and technological capabilities.
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Evolutionary Stages in E-Governance
UN-2The evolutionary stages in e-governance refer to the different phases of development and implementation of e-governance initiatives, from basic online presence to integrated and transformative e-governance systems.
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Internetworking
UN-3Bridges and routers in distributed networking, enabling communication between different networks.
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Internet Design and Evolution
UN-4History and development of the internet, including its design principles and evolution over time.
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Data Cubes
UN-5A multidimensional representation of data, where each dimension represents a different aspect of the data, used for fast querying and data analysis.
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Schemes for Multidimensional Database
UN-6Different schemes used to design and implement multidimensional databases, including Stars, Snowflakes, and Fact Constellations.
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Stars
UN-7A type of multidimensional database scheme, characterized by a central fact table surrounded by dimension tables.
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Snowflakes
UN-8A type of multidimensional database scheme, characterized by a central fact table surrounded by multiple levels of dimension tables.
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Fact Constellations
UN-9A type of multidimensional database scheme, characterized by multiple fact tables connected by dimension tables.
Key Topics
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Symbol Table Design
UN-3.1Function of Symbol Table, Information provided by Symbol Table, Attributes and Data Structures for symbol table
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Run-time Storage Management
UN-3.2Managing storage during runtime
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Database Recovery
UN-3.3Failure Classification, The Storage Hierarchy, Transaction Model, Log-Based recovery, Buffer Management, Checkpoints, Shadow Paging, Failure with Loss of Non-volatile Storage.
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Querying Role Information
UN-3.4Querying role information involves retrieving information about roles and their associated privileges. This topic covers the different methods for querying role information.
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Database Security and Auditing
UN-3.5Database security and auditing involve ensuring the confidentiality, integrity, and availability of database data. This topic covers the different security measures and auditing techniques.
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Creating and Managing Databases
UN-3.6Creating and managing databases involves designing, creating, and modifying database structures. This topic covers the basics of database creation and management.
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Creating and Managing Tables
UN-3.7Creating and managing tables involves designing, creating, and modifying table structures. This topic covers the basics of table creation and management.
Key Topics
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Intermediate Code Generation
UN-4.1This topic covers the generation of intermediate code, including high-level and low-level representations, syntax trees, and three-address code. It also discusses the generation of intermediate code for declarations, assignments, control flow, boolean expressions, and procedure calls.
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Code Generation
UN-4.2This topic explores the factors affecting code generation, including target language, basic blocks, and flow graphs. It also covers dynamic programming code-generation algorithms.
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Code Optimization
UN-4.3This topic discusses the need and criteria for code optimization, as well as basic optimization techniques to improve code efficiency.
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Compiler Case Studies
UN-4.4This topic presents case studies of compilers, including C and C++ compilers, to illustrate the application of compiler design principles.
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Testing the Backup and Recovery Plan
UN-4.5Validating the effectiveness of a backup and recovery strategy through regular testing and simulation exercises.
Key Topics
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Introduction to Virtual Reality
UN-5.1This topic covers the fundamental concepts and principles of Virtual Reality (VR), including its history, applications, and key technologies.
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Introduction to Animation
UN-5.2This topic provides an overview of the basics of animation, including its history, types, and key concepts, as well as its applications in computer graphics.
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Automatic Storage Management
UN-5.3Automatic storage management is a feature that automates the management of database storage, including disk space allocation and deallocation. This topic covers the concepts and best practices of automatic storage management.
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RMAN (Recovery Manager)
UN-5.4RMAN is a utility provided by Oracle for backing up, restoring, and recovering databases. This topic covers the features, benefits, and usage of RMAN in database administration.
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Data Mining Applications
UN-5.5Examining the various applications of Data Mining in different industries, including marketing, finance, and healthcare. Understanding the benefits and challenges of Data Mining in real-world scenarios.
Data mining query languages, data specification, specifying knowledge, hierarchy specification, pattern presentation & visualization specification, data languages and standardization of data mining.
Mining Association Rules in Large Database: Association Rule Mining, why Association Mining is necessary, Pros and Cons of Association Rules, Apriori Algorithm.
Key Topics
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Classification and Prediction Issues
UN-8.1Discussion of common issues and challenges in classification and prediction, including data quality, class imbalance, and overfitting.
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Classification by Decision Tree Induction
UN-8.2Introduction to decision tree induction as a method for classification, including how to construct and prune decision trees.
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Introduction to Regression
UN-8.3Overview of regression analysis, including simple and multiple regression, and its applications in data mining.
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Types of Regression
UN-8.4Exploration of different types of regression, including linear, logistic, and nonlinear regression.
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Introduction to Clustering
UN-8.5Fundamentals of clustering, including types of clustering, clustering algorithms, and applications in data mining.
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K-Mean and K-Mediod Algorithms
UN-8.6In-depth look at K-Mean and K-Mediod algorithms, including how they work, advantages, and limitations.
Mining complex Types of Data: Mining Text Databases, Mining the World Wide Web, Mining Multimedia and Spatial Databases.