Lec.1.Intro.D.S. spring 2024.pdf

Lec.1. Introduction to  Task date Grades Assignment 1 Week 4 2.5 Quiz 1 Week 6 2.5 Midterm exam Week 8 20 Assignment 2 Week 11 2.5 Quiz 2 Week 12 2.5 Practical exam Week 14...

Lec.1. Introduction to  Task date Grades Assignment 1 Week 4 2.5 Quiz 1 Week 6 2.5 Midterm exam Week 8 20 Assignment 2 Week 11 2.5 Quiz 2 Week 12 2.5 Practical exam Week 14 10 Final Project Week 14 10 Final exam Week 15,16 50 Total __________ 100 Data is the new Oil  Lots of data is being collected and warehoused ◦ Web data, e-commerce ◦ Financial transactions, bank/credit transactions ◦ Online trading and purchasing ◦ Social Network  Aggregation and Statistics  Data warehousing and OLAP Online analytical processing  Indexing, Searching, and Querying  Keyword based search  Pattern matching (XML/RDF)  Knowledge discovery  Data Mining  Statistical Modeling  Data, Information, and Knowledge: Data: are any facts, numbers, or text that can be processed by a computer. today, organizations are accumulating vast and growing amounts of data in different formats and different databases. This includes:  operational or transactional data such as, sales, cost, inventory, payroll, and accounting  nonoperational data, such as industry sales, forecast data, and macro economic data  meta data - data about the data itself, such as logical database design or data dictionary definitions  Information The patterns, associations, or relationships among all this data can provide information. For example, analysis of retail point of sale transaction data can yield information on which products are selling and when.  Knowledge Information can be converted into knowledge about historical patterns and future trends. For example, summary information on retail supermarket sales can be analyzed in light of promotional efforts to provide knowledge of consumer buying behavior. Thus, a manufacturer or retailer could determine which items are most susceptible to promotional efforts.