JNTU-K B.TECH R19 3-1 Syllabus For Data warehousing and data mining PDF 2022
January 31, 2022 2022-01-31 19:50JNTU-K B.TECH R19 3-1 Syllabus For Data warehousing and data mining PDF 2022
JNTU-K B.TECH R19 3-1 Syllabus For Data warehousing and data mining PDF 2022
Get Complete Lecture Notes for Data warehousing and data mining on Cynohub APP

Download the APP Now! ( Click Here )
You will be able to find information about Data warehousing and data mining along with its Course Objectives and Course outcomes and also a list of textbook and reference books in this blog.You will get to learn a lot of new stuff and resolve a lot of questions you may have regarding Data warehousing and data mining after reading this blog. Data warehousing and data mining has 5 units altogether and you will be able to find notes for every unit on the CynoHub app. Data warehousing and data mining can be learnt easily as long as you have a well planned study schedule and practice all the previous question papers, which are also available on the CynoHub app.
All of the Topic and subtopics related to Data warehousing and data mining are mentioned below in detail. If you are having a hard time understanding Data warehousing and data mining or any other Engineering Subject of any semester or year then please watch the video lectures on the official CynoHub app as it has detailed explanations of each and every topic making your engineering experience easy and fun.
Data warehousing and data mining Unit One
Data Warehousing
DataWarehousing,BusinessAnalysisandOn-LineAnalyticalProcessing(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.
Data warehousing and data mining Unit Two
Data Mining
DataMining–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.
Get Complete Lecture Notes for Data warehousing and data mining on Cynohub APP

Download the APP Now! ( Click Here )
Data warehousing and data mining Unit Three
Data Mining
DataMining-FrequentPatternAnalysis:Mining Frequent Patterns, Associations and Correlations, Mining Methods, Pattern Evaluation Method, Pattern Mining in Multilevel, Multi-Dimensional Space –Constraint Based Frequent Pattern Mining, Classification using Frequent Patterns
Data warehousing and data mining Unit Four
Classification
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
Data warehousing and data mining Unit Five
Clustering Clustering Techniques
Clustering:ClusteringTechniques,Clusteranalysis,PartitioningMethods,Hierarchicalmethods,DensityBasedMethods,GridBasedMethods,Evaluationofclustering,Clusteringhighdimensionaldata,Clusteringwithconstraints,Outlieranalysis,outlierdetectionmethods.
Data warehousing and data mining Course Objectives
To understand data warehouse concepts, architecture, business analysisand tools To understand data pre-processing and data visualization techniques To study algorithms for finding hidden and interesting patterns in data To understand and apply various classification and clustering techniques using tools
Data warehousing and data mining Course Outcomes
At the end of the course, the students will be able to:Design a Data warehouse system and perform business analysis with OLAP toolsApply suitable pre-processing and visualization techniques for data analysis Apply frequent pattern and association rule mining techniques for data analysisApply appropriate classification techniques for data analysisApply appropriate clustering techniques for data analysis
Data warehousing and data mining Text Books
1)JiaweiHanandMichelineKamber,“DataMiningConceptsandTechniques”,ThirdEdition,Elsevier,201
2)Pang-NingTan,MichaelSteinbachandVipinKumar,IntroductiontoDataMining,Pearson,2016.
Data warehousing and data mining Reference Books
1)AlexBersonandStephenJ.Smith,―DataWarehousing,DataMining&OLAP‖,TataMcGraw–HillEdition,35thReprint2016.2)K.P.Soman,ShyamDiwakarandV.Ajay,―InsightintoDataMiningTheoryandPractice‖,EasternEconomyEdition,PrenticeHallofIndia,2006.3)IanH.WittenandEibeFrank,―DataMining:PracticalMachineLearningToolsandTechniques,Elsevier,SecondEdition.
1)https://www.saedsayad.com/data_mining_map.htm2)https://nptel.ac.in/courses/106/105/106105174/3)(NPTEL course by Prof.Pabitra Mitra) http://onlinecourses.nptel.ac.in/noc17_mg24/preview 4)(NPTEL course by Dr. Nandan Sudarshanam & Dr. Balaraman Ravindran) http://www.saedsayad.com/data_mining_map.htm
Scoring Marks in Data warehousing and data mining
Scoring a really good grade in Data warehousing and data mining is a difficult task indeed and CynoHub is here to help!. Please watch the video below and find out how to get 1st rank in your B.tech examinations . This video will also inform students on how to score high grades in Data warehousing and data mining. There are a lot of reasons for getting a bad score in your Data warehousing and data mining exam and this video will help you rectify your mistakes and help you improve your grades.
Information about JNTU-K B.Tech R19 Data warehousing and data mining was provided in detail in this article. To know more about the syllabus of other Engineering Subjects of JNTUH check out the official CynoHub application. Click below to download the CynoHub application.
Get Complete Lecture Notes for Data warehousing and data mining on Cynohub APP
