Misc Topics 2 Amol Deshpande CMSC424 Topics OLAP Data Warehouses Information Retrieval OLAP On line Analytical Processing Why Exploratory analysis Interactive Different queries than typical SPJ SQL queries Data CUBE A summary structure used for this purpose E g give me total sales by zipcode now show me total sales by customer employment category Much much faster than using SQL queries against the raw data The tables are huge Applications Sales reporting Marketing Forecasting etc etc Data Warehouses A repository of integrated information for querying and analysis purposes Tend to be very very large Typically not kept up to date with the real data Specialized query processing and indexing techniques are used Very widely used Data Mining Searching for patterns in data Typically done in data warehouses Association Rules When a customer buys X she also typically buys Y Use Move X and Y together in supermarkets A customer buys a lot of shirts Send him a catalogue of shirts Patterns are not always obvious Classic example It was observed that men tend to buy beer and diapers together may be an urban legend Other types of mining Classification Decision Trees Information Retrieval Relational DB Structured data Information Retrieval Unstructured data Evolved independently of each other Still very little interaction between the two Goal Searching within documents Queries are different typically a list of words not SQL E g Web searching If you just look for documents containing the words millions of them Mostly useless Ranking This is the key in IR Many different ways to do it E g something that takes into account term frequencies Pagerank from Google seems to work best for Web
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