1. LECTURE 2: DATA MINING

2. WHAT IS DATA MINING? 2

3. D ATA M INING AND D ATA W AREHOUSES ? It evolved in to being as the science of databases evolved Database  Datawarehouses  Data Mining Process similar to how science evolved Data Mining and Data Analytics is the fastest growing discipline worldwide with plenty of jobs 3

4. E VOLUTION OF S CIENCES Before 1600, empirical science Science from practical experience Arab and muslim scientists were at the forefront 1600-1950s, theoretical science Underpinned the importance of theory or hypothesis Next stage involved proving it empirically 1950s-1990s, computational science Over the last 50 years, most disciplines have grown a third, computational branch (e.g. empirical, theoretical, and computational ecology, or physics, or linguistics.) Computational Science traditionally meant simulation. It grew out of our inability to find closed-form solutions for complex mathematical models. 4

5. E VOLUTION OF S CIENCES 1990-now, data science The flood of data from new scientific instruments and simulations The ability to economically store and manage petabytes of data online Scientific info. management, acquisition, organization, query, and visualization tasks scale almost linearly with data volumes. Data mining is a major new challenge! Jim Gray and Alex Szalay, The World Wide Telescope: An Archetype for Online Science, Comm. ACM, 45(11): 50-54, Nov. 2002 5

6. E VOLUTION OF D ATABASE T ECHNOLOGY 1960s: Data collection, database creation, IMS and network DBMS 1970s: Relational data model, relational DBMS implementation 1980s: RDBMS, advanced data models (extended-relational, OO, deductive, etc.) Application-oriented DBMS (spatial, scientific, engineering, etc.) 6

7. 1990s: Data mining, data warehousing, multimedia databases, and Web databases 2000s Stream data management and mining Data mining and its applications Web technology (XML, data integration) and global information systems 7

8. C LASS W ORK 1.How did data mining evolve from databases? Ans. Database  Datawarehouses  Data Mining 2. Why is Data Science possible today i.e. 1990s onwards? Ans. Availability of a huge amount of data in various types of databases. 3. When did or in which years did computation science become a branch of most other sciences? Ans. Between 1950s and 1990s. 4. Arabs and muslim scientists are considered the founders of which kind of sciences? Ans. Empirical Sciences. 8

9. D ATA M INING D EFINITION Data mining (knowledge discovery from data) Extraction of interesting patterns or knowledge from huge amount of data Data mining: a misnomer? Alternative names Knowledge discovery (mining) in databases (KDD), knowledge extraction, data/pattern analysis, data archeology, data dredging, information harvesting, business intelligence, etc. Watch out: Is everything “data mining”? Simple search and query processing (Deductive) expert systems 9

10. C LASS W ORK Define what is Data Mining? Extraction of information i.e. implicit, previously unknown, potentially useful and non-trivial. State whether the following is simple search (SS) and/or data mining (DM). 1.Retrieving name of students from database. SS 2.Finding whether a first year student will complete studies or not. DM 3.Looking up which customer buys dates. SS 4.Investigating whether a customer buying dates buys milk as well or not. DM 5.Investigating which cars have been fined for high speed today. SS 6.Predicting what amount of fines a student will receive in an year. DM 7.Finding which cars compete with Toyota Corolla in KSA. SS 8.Identifying which models sold by Toyota are likely to be popular in different regions of Saudia in the next year. DM 9.Finding which products were bought by a customer in a month. SS 10.Identify which customer would be highly valuable. DM