Data mining & Data Warehousing

Features Data mining & Data Warehousing

The app is a complete free handbook of Data mining & Data Warehousing which cover important topics, notes, materials on the course.This Data mining & Data Warehousing App lists 200 topics with detailed notes, diagrams, equations, formulas & course material, the topics are listed in 5 chapters.
The app is must have for all the computer science & engineering students.The App is designed for quick learning, revisions, references at the time of exams and interviews.
This app cover most of related topics and Detailed explanation with all the basics topics.
Some of the topics Covered in the data warehousing and data mining app are:1.
Introduction to Data mining2.
Data Architecture3.
Data-Warehouses (DW)4.
Relational Databases5.
Transactional Databases6.
Advanced Data and Information Systems and Advanced Applications7.
Data Mining Functionalities8.
Classification of Data Mining Systems9.
Data Mining Task Primitives10.
Integration of a Data Mining System with a Data Warehouse System11.
Major Issues in Data Mining12.
Performance issues in Data Mining13.
Introduction to Data Preprocess14.
Descriptive Data Summarization15.
Measuring the Dispersion of Data16.
Graphic Displays of Basic Descriptive Data Summaries17.
Data Cleaning18.
Noisy Data19.
Data Cleaning Process20.
Data Integration and Transformation21.
Data Transformation22.
Data Reduction23.
Dimensionality Reduction24.
Numerosity Reduction25.
Clustering and Sampling26.
Data Discretization and Concept Hierarchy Generation27.
Concept Hierarchy Generation for Categorical Data28.
Introduction to Data warehouses29.
Differences between Operational Database Systems and Data Warehouses30.
A Multidimensional Data Model31.
A Multidimensional Data Model32.
Data Warehouse Architecture33.
The Process of Data Warehouse Design34.
A Three-Tier Data Warehouse Architecture35.
Data Warehouse Back-End Tools and Utilities36.
Types of OLAP Servers: ROLAP versus MOLAP versus HOLAP37.
Data Warehouse Implementation38.
Data Warehousing to Data Mining39.
On-Line Analytical Processing to On-Line Analytical Mining40.
Methods for Data Cube Computation41.
Multiway Array Aggregation for Full Cube Computation42.
Star-Cubing: Computing Iceberg Cubes Using a Dynamic Star-tree Structure43.
Pre-computing Shell Fragments for Fast High-Dimensional OLAP44.
Driven Exploration of Data Cubes45.
Complex Aggregation at Multiple Granularity: Multi feature Cubes46.
Attribute-Oriented Induction47.
Attribute-Oriented Induction for Data Characterization48.
Efficient Implementation of Attribute-Oriented Induction49.
Mining Class Comparisons: Discriminating between Different Classes50.
Frequent patterns51.
The Apriori Algorithm52.
Efficient and scalable frequently itemset mining methodsAll topics are not listed because of character limitations.Features :* Chapter wise complete Topics* Rich UI Layout * Comfortable Read Mode* Important Exam Topics* Very simple User Interface* Cover Most Of Topics* One click get related All Book* Mobile Optimized Content * Mobile Optimized ImagesThis app will useful for quick reference.
The revision of all concepts can be finished within Several hour using this app.Data mining & Data Warehousing is part of computer science, software engineering, AI, Machine learning & Statistical Computing education course and information technology & business management degree programs at various universities.
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