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Data Warehouse Mining Viva

DWMBI (Data Warehouse Mining & Business Intelligence) Viva Questions:
Hey guys, welcome back we @ conceptSimplified are devoted to simplify your task. Following are few of the Most frequently asked Viva questions in DWMBI and would be extremely useful if you are specifically from Mumbai University.

Data Warehouse Mining Viva
CH-1 Introduction to Data Mining

  • What is data mining?
  • What are functionalities of Data Mining?
  • Classify Data Mining systems
  • Explain Integration of Data Mining system with a Database or Datawarehouse
  • Architecture of Typical Data mining System?
  • What are major Data Mining Issues?
  • Explain KDD process?

CH-2 Data WareHousing

  • What is Data warehousing?
  • Difference between Database and Datawarehouse?
  • Explain Star Schema?
  • Explain Snow flake Schema?
  • Difference between Star and snow flake schema?
  • Explain Fact and Dimensional table?
  • Explain Factless Fact table?
  • What is OLAP?
  • What is OLTP?
  • State applications of OLAP.
  • Difference between OLAP and OLTP?
  • State OLAP operations?

CH-3 Data Preprocessing

  • Difference between clustering and classification?
  • What is Data cleaning?
  • What is Data Integration?
  • What is Data Transformation?
  • State Data Reduction techniques ?
  • Explain Data Reduction techniques in short?
  • Which techniques are used for Numerosity Reduction?
  • Give ways of handling Noise Data?
  • What is noisy data?

CH-4 Mining Frequent Patterns,Associations and Correlations

  • What is Market basket analysis?
  • Explain Apriori Algorithm?
  • Explain FP-Tree Algorithm?
  • How FP-Tree is better than Apriori Algorithm?
  • Give formula of Support and Confidence?
  • K-mean Algorithm
  • What are Constraint based association rule mining?
  • Explain mining multilevel association Rules?
  • Explain mining multidimensional association Rules?

CH-5 Classification and Prediction

  • What is Classification?
  • What is Prediction?
  • State Issues regarding Classification and Prediction?
  • State various classification methods?
  • What is Regression?
  • State types of Regression?
  • Explain Linear Regression?
  • Explain Non Linear Regression?
  • Give formulae of a)Information Gain b)Entropy c)Gini index?
  • Explain Decision tree in brief?
  • Explain Bayesian classification?

CH-6 Cluster Analysis

  • What is clustering ?
  • What is Clustering Analysis?
  • State types of data in Clustering Analysis?
  • State Categories of clustering methods?
  • State partitioning methods?
  • What is BIRCH?
  • What is ROCK?
  • Explain DBSCAN?
  • Explain K-means?
  • Explain K-mediods?
  • Explain Agglomerative Clustering?
  • Explain Outliers Analysis?

CH-7 Mining Stream and Sequence Data

  • What is Stream Data?
  • Explain Association mining in stream data?
  • Explain Sequence Mining in transactional database?
  • Explain different Data Stream methodologies?
  • Explain Hoeffding Tree Algorithm?

CH-8 Spatial Data & Text Mining

  • Compare Data Mining and Text Mining.
  • State Spatial Clustering methods.
  • What is Spatial OLAP?
  • What is Spatial data mining?
  • State different approaches in Text Mining?
  • State Spatial Clustering Methods?
  • What is Web mining ?
  • What is Web Content Mining?
  • What is Web Structure Mining?

CH-9 Data Mining for Bussiness Intelligence Applications.

  • What is business intelligence ?
  • State Business Intelligence issues?
  • How Data Mining be used for BI Applications?
  • Explain Data Mining for Market Segmentation?
  • Explain Data Mining for Retail Industry?

Software Engineering viva questions

Hello guys, vivas are around and no clue what to study, we at conceptSimplified simplify your task.Below are few questions which we would recommend you to be prepared before giving your Vivas.

  • Name the software process models. Describe them.
  • What is process metrics and project metrics?
  • Name the software estimation techniques. Give the formula. Explain any one technique?
  • What are the principles of project planning?
  • Function Points & Lines of Code.
  • Define risk analysis. Steps of risk analysis.
  • What is RMMM(Risk Management, Mitigation & Monitoring) plan?
  • What are the principles of project scheduling?
  • What are milestones, WBS chart and Gantt chart?
  • What is software requirement? Requirements in engineering process.
  • Data flow diagrams. Characteristics of good SRS.
  • Software design abstraction and architecture.
  • Definition and types of cohesion and coupling.
  • What are the design issues?
  • Explain SCM process and tools.
  • What is Software quality assurance?
  • Explain Quality metrics ( Defect Removal Efficiency)?
  • What is baseline?
  • Different types of software testing.
  • Difference between blackbox testing and white box testing.
  • What is Software engineering?
  • What is Reverse engineering?
  • Service oriented software engineering.
  • What is alpha-beta testing?(Most asked question)
  • What is requirement analysis and specification?
  • What is use case model?
  • Test case and Test scenario.
  • Draw use case for library management, ATM.
  • What is version control?
  • What is change control?
  • What is requirement gathering?
  • What is FTR (Formal Technical Review)?
  • Explain the steps in FTR?
  • Define Software Engineering?
  • What are estimation techniques?
  • Explain design principles?
  • What is CoCoMo model?
  • What are testing principles?

Note: These are few of the most Frequently Asked Viva Questions. It would be best if you refer Software Engineering A Practitioner’s Approach 7th Edition – Roger Pressman for solutions of viva questions.

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