Lecture 9: Business Intelligence and Data Mining – Flashcards
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Online Transaction Processing (OLTP)
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updating (ie. inserting , modifying, and deleting), retrieving and presenting data from databases for operational purposes
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Online Analytical Processing (OLAP)
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querying and presenting data from data warehouses and/or data marts for analytical purposes
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OLAP/BI Tools
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-OLAP tools designed for analysis of data in data warehouses and data marts -Business Intelligence tooks
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OLAP Tools allows users to retrieve....
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needed data from data warehouses and data marts by using simple point and click mechanisms
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Point-and-Click Actions
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by users of the OLAP/BI tools, the tool writes and executes the code in the language of the DBMS that hosts the data warehouse or data mart that is being quiried
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OLAP Query 1
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For each indicidual store, show separately for male and female shoppers that number of products sold for each product category
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Basic OLAP/BI Tool features
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-slice and dice -pivot (Rotate) -Drill Down/ Drill Up
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Slice and Dice
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Adds, replaces, or eliminates specified attributes (or particular values) from the already displayed result
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OLAP Query 2
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For stores 1 and 2, show separately for male and female shoppers the number of product units sold for each product category
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Pivot (Rotate)
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Reorganizes the values displayed in the original query result by moving cvalues of a dimension column from one axis to another
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Drill Down
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makes the granularity of the Data in the query result finer
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Drill Up
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makes the granularity of the data in the query result coarser
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OLAP/BI Tools are...
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web based
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OLAP Tools Functionalities
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Basic features- slice/ dive/ pivot/ drill
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Data Visualization
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graphically visualizing the answers
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Additional functionalities
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-creating and examining calculated data -determining relative differences -performing analysis
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Accessing Data in Data Warehouses and Data Marts
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-LAP/BI Tools -Front-End applications -Executive Boards using it for direct access
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Front-End/ BI Applications
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-for indirect access -Front-end applications accessing analytical data are also known as BI applications -Most users who need to access analytical data in Data warehouses can not engage in direct access -instead access to front-end Application
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Executive Dashboards
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For a quick glance at Data -for users with a higher level decision makers in organization -organized easy to read display of important queries -little or no effort in trainting -can be web based
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Data Mining
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-discovering novel and interesting patters in large amounts of data -mining is an intersection of database management, artificial intelligence, and statistics
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Patters of Data Mining
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-Accurate -Meaningful -Understandable -Actionable
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Predictive Analytics
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-using past data to predict future events -There are numerous data mining techniques
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One Widely used data mining technique
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Market Basket Analysis
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Market Basket Analysis (Aka association rule mining)
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find groups of items that tend to appear together in transactions
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Market Basket Analysis
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-association rule: X-> Y -Correlations are expressed in the form: Transactions that contain X are likely to contain Y as well
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Measures of Market Basket Analysis
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Support and Confidence
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Support
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measures the significance of the rule, so we are interested in rules with relatively high support
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Confidence
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measures the strength of the correlation, so rules with low confidence are not meaningful, even if their support is high
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Market Basket Analysis-Find rules of form/mythical association rule
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people who buy x, tend to by y -bread, mild, cheese -babies and alcohal
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Most appropriate and fertile source of data for meaningful and effective data
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Enterprise Wide Corporate Data Warehouse - which contains all the information from the operational data sources that has analytical value
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Mining Transaxtional Databases
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Containing data related to current day-to-day organizational activities can be of use in certain situations
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Business Intelligence
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encompassing analytical data see and use large amounts of data
