JNTUK R19 B.Tech CSE 3-1 DWDM Material/ Notes PDF Download

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JNTUK R19 B.Tech CSE 3-1 DWDM Material/ Notes PDF Download: Embark on a journey of knowledge with JNTUK R19 CSE B.Tech 3-1 DWDM Material, meticulously curated to unravel the intricacies of Data Warehousing and Data Mining. Discover the world of Data Warehousing and Data Mining with JNTUK R19 CSE B.Tech 3-1 DWDM Material, specially crafted for B.Tech CSE students. This resource covers key concepts like data warehouse architecture, business analysis, and practical tools. Learn essential skills in data pre-processing and visualization techniques to analyze information accurately. Dive into algorithms that uncover hidden patterns within data, and grasp the application of classification and clustering techniques using user-friendly tools. Download the easy-to-access PDF material to enhance your understanding and excel in your studies.

JNTUK R19 CSE B.Tech 3-1 DWDM Material – Units

Unit 1 Syllabus PDF Download | JNTUK R19 B.Tech DWDM Material

Data Warehousing: Business Analysis and On-Line Analytical Processing (OLAP): Basic Concepts, Data Warehousing Components, Building a Data Warehouse, Database Architectures for Parallel Processing, Parallel DBMS Vendors, Multidimensional Data Model, Data Warehouse Schemas for Decision Support, Concept Hierarchies, Characteristics of OLAP Systems, Typical OLAP Operations, OLAP and OLTP.

Unit 2 Syllabus PDF Download | JNTUK R19 B.Tech DWDM Material

Data Mining – Introduction: Introduction to Data Mining Systems, Knowledge Discovery Process, Data Mining Techniques, Issues, applications, Data Objects and attribute types, Statistical description of data, Data Preprocessing – Cleaning, Integration, Reduction, Transformation and discretization, Data Visualization, Data similarity and dissimilarity measures.

Unit 3 Syllabus PDF Download | JNTUK R19 B.Tech DWDM Material

Data Mining – Frequent Pattern Analysis: Mining Frequent Patterns, Associations and Correlations, Mining Methods, Pattern Evaluation Method, Pattern Mining in Multilevel, MultiDimensional Space – Constraint Based Frequent Pattern Mining, Classification using Frequent Patterns

Unit 4 Syllabus PDF Download | JNTUK R19 B.Tech DWDM Material

Classification: Decision Tree Induction, Bayesian Classification, Rule Based Classification, Classification by Back Propagation, Support Vector Machines, Lazy Learners, Model Evaluation and Selection, Techniques to improve Classification Accuracy

Unit 5 Syllabus PDF Download | JNTUK R19 B.Tech DWDM Material

Clustering: Clustering Techniques, Cluster analysis, Partitioning Methods, Hierarchical methods, Density-Based Methods, Grid Based Methods, Evaluation of clustering, Clustering high dimensional data, Clustering with constraints, Outlier analysis, outlier detection methods.

JNTUK R19 CSE B.Tech 3-1 DWDM Notes – Outcomes

• Data Warehouse System: Develop a comprehensive data warehouse system for efficient data storage and retrieval, integrating diverse sources for business insights.
• OLAP Tools for Business Analysis: Utilize OLAP tools to perform interactive business analysis, navigating through multidimensional data to understand trends and performance metrics.
• Pre-processing and Visualization: Employ data pre-processing techniques for clean and enhanced data. Use visualization tools to represent data intuitively, aiding in pattern identification.
• Frequent Pattern and Association Mining: Apply advanced mining techniques to discover meaningful relationships within the dataset, uncovering co-occurrence patterns and sequences.
• Classification and Clustering: Implement classification for predictive modeling and clustering for grouping similar data points, providing insights into customer behavior and dataset structures.

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