Data Warehousing And Data Mining Question Bank Pdf
Illustrate the algorithm with a relevant example. Yes, dimension table can have numeric value as they are the descriptive elements of our business. How are association rules mined from large databases? Explain the importance of metadata in a data warehouse environment.
Define collective outliers. If there are changes in the dimensions, same facts can be useful. What is data transformation? Fact table has facts and measurements of the business and dimension table contains the context of measurements.
Distinguish between window painter and data windows painter. Write the transformation tools used in Data warehouse? When is data mart appropriate?
List out the functionality of metadata. Explain Multimedia Data Mining.
What are the steps to be followed to store the external source into the data warehouse? Define constraint-Based Association Mining. What is the difference between metadata and data dictionary?
State why the data preprocessing an important issue for data warehousing and data mining. What are the advantages of data warehousing.
Define Data Visualization. Explain in detail about different Vendor Solutions. Describe Tree pruning methods. Metadata is defined as data about the data. Describe the multi-dimensional association rule, giving a suitable example.
Top 50 Data Warehouse Interview Questions & Answers
Explain the architecture of Data warehouse in detail with a neat diagram. What are the steps followed in Backpropagation? What is the use of Regression? Explain k means partitioning method in detail.
Newer Post Older Post Home. Explain Multimedia Queries. Can be queried and retrieved the data from database in their own format. Explain the components of Data warehouse in detail.
Define multimedia data mining. Explain Apriori Algorithm. Foreign keys of dimension tables are primary keys of entity tables. But, Data dictionary contain the information about the project information, graphs, abinito commands and server information.
The metadata contains information like number of columns used, fix width and limited width, ordering of fields and data types of the fields. The Height values have been already discredited into disjoint ranges. List out the different classifications of Association rule mining. What is Frequent pattern-Based Classification?
How to request Study Material? What is the function of power play administrator? Define spatial data mining. Define conceptual outliers. In single sentence, paper targets pdf it is repository of integrated information which can be available for queries and analysis.
DOC) DATA WAREHOUSE AND DATA MINING QUESTION BANK
Star schema is nothing but a type of organizing the tables in such a way that result can be retrieved from the database quickly in the data warehouse environment. What are the means to improve the performance of association rule mining algorithm? Define density based method.
How data mining is used in banking industry? What are the types of outlier analysis. Aggregate tables are the tables which contain the existing warehouse data which has been grouped to certain level of dimensions. Draw a neat diagram for the Distributed memory shared disk architecture. List out the benefits of Data warehouse?
Real-time datawarehousing captures the business data whenever it occurs. What are the elements in Multimedia Data Mining? Mention few approaches to mining Multilevel Association Rules.
It is advised to avoid loop between the tables. Write the goals of Data Mining?
Discuss the approaches for mining multi level association rules from the transactional databases. With relevant examples discuss multidimensional online analytical processing and multi-relational online analytical processing. List out the other Classification Methods? What are the types of data in cluster analysis? What are the requirements for cluster analysis?
Fact table contains the measurement of business processes, and it contains foreign keys for the dimension tables. Even, it helps to see the data on the information itself.
Write down the tools used in Data Mining? Draw the final decision tree without any pruning for the training dataset. What are the things suffering the performance of Apriori candidate generation technique. Name itself implies that it is a self explanatory term.
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