Data mining, a process that involves the extraction of predictive information which is hidden from very large databases (Vijayarani Nithya,2011;Nirkhi,2010) is a very powerful and yet new technology having a great potential in helping companies to focus on the most important data in their data warehouses.
Data Mining interview questions and answers for freshers and experienced In this series, we have covered all about Data Mining and answered the questions that might be asked during an interview.
Data Mining and Ethics. The use of data particularly data about people for data mining has serious ethical implications, and practitioners of data mining techniques must act responsibly by making themselves aware of the ethical issues that surround their particular application.
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Apr 28, 2013· Following are top 101 data ware house and data mining VIVA questions and answers. What is data warehouse? A data warehouse is a electronic storage of an Organization's historical data for the purpose of reporting, analysis and data mining or knowledge discovery.
Data Warehousing and Data Mining JNTU Previous Years Question Papers Download as Word Doc (.doc / .docx), PDF File (.pdf), Text File (.txt) or read online. ... Data Mining Important Questions. STM Important Questions. Web Technology Unit Wise Questions. Linux Programming Lecture Notes. LAB MANUAL CLOUD
Offline Data Warehouse; Real Time Datawarehouse; Integrated Datawarehouse; DATA WAREHOUSE Interview Questions. 6. Define what is Data Mining? Data Mining is set to be a process of analyzing the data in different dimensions or perspectives and summarizing into a useful information. Can be queried and retrieved the data from database in their own format. 7.
Data mining is defined as a process of discovering hidden valuable knowledge by analyzing large amounts of data, which is stored in databases or data warehouse, using various data mining techniques such as machine learning, artificial intelligence(AI) and statistical.
JNTU Data Warehousing and Data Mining IMPORTANT QUESTION:The Important Questions of JNTUH CSE 41 Data Warehousing and Data Mining,JNTUH CSE 41 Study Materials of Data Warehousing and Data Mining,JNTUH CSE 41 Question Papers of Data Warehousing and Data Mining are provided.
use of data mining algorithms for the purpose of knowledge discovery as the basic ... documentation is the most important in selecting of system information and data used for ... M. Suknović, M. Čupić, M. Martić, D. Krulj / Data Warehousing and Data Mining 127 problems better than the system designers so that their opinion is often crucial ...
Data warehousing provides an efficient storage, maintenance, and retrieval of data. OLAP is a service that provides a way to create ad hoc queries against the data warehouse in order to answer important business questions. Data mining is a disciple comprising of several algorithms for discovering knowledge in a large bulk of data.
INSTRUCTIONS: Answer question ONE and any other TWO questions QUESTION ONE a) Define the following terms i) Data mining (2 marks) ii) Data Warehouse (2 marks) iii)Online Analytical Processing (2 marks) b) Outline the phases of decision support lifecycle (10 marks) c) Elaborate the following schemas as used in data warehousing
Data mining is the process of analyzing large amounts of data in an effort to find correlations, patterns, and insights. You can say Data mining is Data Discovery in other word. To discover relationship between two or more variables in your data we require Data Mining.
Here IT6702 DATA WAREHOUSING AND DATA MINING Important Questions Bank Reg 2013 are posted and Students can download the Questions and make use of it. Anna University IT6702 DATA WAREHOUSING AND DATA MINING Important Questions Bank Reg 2013 are provided Below.
A data warehouse is a special type of database. It is used to store large amounts of data, such as analytics, historical, or customer data, and then build large reports and data mining against it.
Data warehousing deals with all aspects of managing the development, implementation and operation of a data warehouse or data mart including meta data management, data acquisition, data cleansing, data transformation, storage management, data distribution, data archiving, operational reporting, analytical reporting, security management, backup ...
Remember that data warehousing is a process that must occur before any data mining can take place. In other words, data warehousing is the process of compiling and organizing data into one common database, and data mining is the process of extracting meaningful data from that database.
Data Mining interview questions and answers for freshers and experienced In this series, we have covered all about Data Mining and answered the questions that might be asked during an interview.
Data Warehousing and Data Mining pdf Notes starts with the topics covering Introduction: Fundamentals of data mining, Data Mining Functionalities, etc Here you can download the free Data Warehousing and Data Mining Notes pdf – DWDM notes pdf latest and Old materials with multiple file links to download.
Fast answers to business questions with data warehousing. A data warehouse stores all your business data. This data can be used for integral analysis, reporting, justification, data mining, and making dashboards.
PART B Data Mining?Explain the steps followed in Mining process? in detail about KDD process. short notes on the following.(a)Data Preprocessing (b)Data Discretization (c)Concept Hierarchy 4.
Data Warehousing and Data Mining Business Analysis Important Short Questions and Answers: Data Warehousing Business Analysis Business Analysis .
Data mining is used to simplify and summarize the data in a manner that we can understand, and then allow us to infer things about specific cases based on the patterns we have observed.
This is a top data warehouse interview questions and answers that can help you crack your data warehousing job interview. You will learn about difference between a data warehouse and a database, cluster analysis, chameleon method, virtual data warehouse, snapshots, ODS for operational reporting, XMLA for accessing data and types of slowly changing dimensions.