Data Mining and Warehousing Solved Question Paper, Notes and Question Bank

Data mining and warehousing.
Types of Data MiningPredictive | Prescriptive | Descriptive
What is data mining?Discovery of patterns and information
Benefits of data warehousingMakes it possible to extract valuable information by joining various datasets

Introduction:

This article is giving brief of “Data Mining and Warehousing Solved Question Paper, Notes and Question Bank”.

We have included question papers from various universities so that one can have enough idea about field of data mining and warehousing.

Hope you will like this, if yes then please let us know in comments.

Collection of 100s of questions on wireless and mobile computing sort of question bank with some solved question papers and links to notes for study material.

Questions from different universities have been collated to give a comprehensive list of questions.

Important Questions on Data Mining and Data Warehousing:

Q. What is data mining?

Ans. So, data mining is discovery of patterns and information from possibly data sources using different statistical and computing techniques.

Q. What is the difference between data mining and data warehousing?

Ans. Data warehousing is the process of collating all the data from different sources into one common database, where data mining is the process of using various techniques to extract useful actionable information from data.

Q. Why data warehousing is important?

Ans. Data warehousing makes it possible to extract valuable information by joining various datasets for e.g.

  • We can join marketing and sales data to understand which marketing campaign lead to most sales and has higher ROI,
  • We can join website pages data with search data and understand what kind of search queries is driving traffic to my website.

Q. What are 3 types of data mining?

Ans. Different types of data mining are:

  • Predictive Data Mining: Predictive data mining helps in finding what will happen next in the business gives certain conditions.
    • for e.g. What will be the sales next year or next quarter based on historical data.
  • Prescriptive Data Mining: Prescriptive data mining is used to prescribe relevant steps to be taken for some process or business improvement.
    • For e.g. Spending more money on a particular sales campaign on Linkedin as it leads to more sales.
  • Descriptive Data Mining: Descriptive data mining analyses data and tells what happens actually in business or product for e.g.
    • For e.g. North America customers are buying monthly plan, whereas Europe customers are more inclined towards semi-annual plans. -or- Traffic from North America on website decreases during thanks giving and during Christmas season.

One Full Solved Question Paper on Data Mining and Warehousing of RGPV University Bhopal:

So, this two solved question paper is not enough to get full idea about data mining and warehousing.

But, still one can have some idea of what is asked in different question papers and some important points related to it.

Also, to help further we are adding links of notes pdfs from various universities.

Data Mining and Warehousing Notes pdf:

Notes on data warehousing and mining from different universities. We have also added page numbers so that you can download the notes as per your need, time and requirement.

  • Data mining and warehousing – Lecture Notes – 84 pages
    • Total of 4 modules with topics including what is data mining, association rules, mining basket analysis, classification, prediction, cluster analysis etc.
  • Digital Notes on Data Warehousing and Data Mining – MRCET – 88 pages
    • A total of 6 units with objective to give brief about data warehousing principles and working, data mining concepts, studying classification algorithms and knowledge about how data is grouped using clustering techniques etc.
  • cvr.ac.in – Data Warehousing and Data Mining – 80 pages
    • No index but topics included in the pdf are data mining primitives, kind of knowledge to be mined, presentation and visualisation of discovered patterns, classification and prediction explanation with issues related to it etc.
  • dei.unipd.it – Data Warehousing and Data Mining – 62 pages
    • Not in depth content but a presentation to some sort for teaching to students with topics includes introduction and terminology, data warehousing, data mining – association rules, sequential patterns, classification, clustering etc.

You can refer these links to download and save these notes on your mobile, laptop etc. and can refer it whenever you want learn about this topic.

Data Mining and Warehousing Previous Year Question paper RGPV:

Attaching set of question papers on data mining and warehousing from previous years for getting an idea of how normally RGPV sets paper every year.

  • CS 703 DATA MINING AND WARESHOUSING DEC 2020
    • 70 marks question paper,
    • Attempt any 5 out of 8,
    • Each question carry 2 questions except 8th which has 4 parts,
    • Some questions includes OLAP, MOLAP, rule generation in Apriori algorithm etc.
  • IT 8004 DATA MINING AND WAREHOUSING DEC 2020
    • 70 marks question paper,
    • Attempt any 5 out of 8,
    • Almost every question has 2 parts except 6th which has 3 parts,
    • Some questions includes data cleaning, data mining functionality, web mining, spatial mining etc.
  • IT 840 DATA MINING AND WAREHOUSING JUN 2020
    • 70 marks question paper,
    • Attempt any 5 out of 8,
    • Few questions has 1 part and few has multiple parts,
    • Some questions includes architecture of data warehouse, roll-up, drill down operation, FP growth algorithm, clustering methods, financial data analysis etc.
  • IT 8004 DATA MINING AND WARE HOUSING MAY 2019
    • 70 marks question paper,
    • Attempt any 5 out of 8,
    • Every question has 2 parts except 4 which has 1 part only,
    • Some questions includes OCAP, ROCAP, MOCAP, k-means clustering, spatial mining, association rules mining etc.
  • IT 840 DATA MINING AND WAREHOUSING JUN 2017
    • 70 marks question paper,
    • Attempt any 5 out of 7,
    • Every questions has 2 sub-parts except 7th one which has 3 parts,
    • Some questions includes: information processing, analytical processing, data mining, star and snowflake schemas, data discretization and concept hierarchy generation, data cube aggregation and attribute subset selection, data mart, confusion matrix, metadata repository etc.
  • IT 840 DATA MINING AND WAREHOUSING JUN 2016
    • 70 marks question paper,
    • Total 5 question each has 4 sub-parts with certain choices in each one of them,
    • Some question includes: data mart and it’s types, data cleaning and transformation, OLAP and OLTP, computation of data cubes, database and knowledge base, text mining applications etc.
  • IT 8 SEM DATA MINING AND WAREHOUSING MAY 2018
    • 70 marks question paper,
    • Attempt any 5 out of 8,
    • Some questions has 2 sub-parts while other has only 2 parts,
    • Some questions includes: data transformation, data reduction, spatial database and text database, data mining system, bayesian classification, outlier analysis etc.

Sometimes, looking at the old question papers helps in understanding the exam pattern even further and increase chances of scoring more that is why we have added these question papers from previous years from RGPV website.

Data Mining and Warehousing Question Paper from Different Universities (DU, JNTUH, VTU etc.):

Question papers from different universities for giving an idea about type of questions asked in different universities.

  • Visvesvaraya Technological University(VTU) – 6th Sem – Jan 2020
    • 5 modules with each containing 2 questions. Attempt one full question from each module.
    • Some questions includes: data warehouse, data cube measure, data cube computation, approach for solving classification problem, K-means algorithm etc.
  • Data Mining and Warehousing Question Paper JNTUH – 7th Sem – Dec 2016
    • Part A compulsory of 25 marks,
    • Part B has 5 modules with 2 parts in each, have to attempt any one from each module.
    • Some important questions includes: three measures of similarity, classifier techniques, pre puning and post puning, discovery driven exploration etc.
  • Data Mining and Warehousing Question Paper JNTUH – 6th Sem – Dec 2018
    • Part A compulsory of 25 marks,
    • Part B has 5 modules with 2 parts in each, have to attempt any one from each module.
    • Some important questions includes: dimensionality reduction, attribute subset selection, types of OLAP servers, relational databases, naice bayesian classification etc.
  • SIETK – Question bank – 5th Sem
    • 40 questions spread around 4 units each containing 10 questions.
    • Questions examples: KDD, motivated data mining, 3-tier data warehouse architecture, dice operation, pivot operation, FP-growth algorithm, Bayes theorem etc.
  • Data Warehouse And Data Mining Question Paper – Dec 2014 – 6th Sem – Mumbai University (MU)
    • 7 question with sub-parts in each one of them,
    • Questions includes: dimension tables, snowflake schema, ETL cycle, association mining, meta data in data warehouse etc.

Although, it is not of much importance of students unless they are keen to know more about data mining and warehousing.

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So, the above links contains notes from other subjects and that is clearly mentioned in the link titles.

So, if you are from CS or IT we have solved quite a few question papers for your reference.

Final Words:

Please note only first question paper is solved followed by several links for notes on data mining and warehousing all of them are downloadable and then question from different universities and colleges.

So, please let us know if you want us to help you with any of the answers on same or any other topic we will be more than happy to help you with that.

I hope this article Data Mining and Warehousing Solved Question Paper, Notes and Question Bank has provided you some value, if your answer is yes please let us know in comments.

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