ER Design phase 1. Requirements analysis: what problem is being solved? What does the DB need to do? 2. Logical design: Identification of entities and their relationships (ER model) 3. Normalization: systematic simplification and clarification of the logical design 4. Physical Design: implementation in DBMS ER model concepts 1. Entity: thing, A noun 2. Attribute: a property, An adjective (PK mar..

Relational Algebra: Formalisation of Operations(SELECT, JOIN, etc.), Uses operations on relations(set of tuples), Allows us to understand and create more efficient queries Unary Operations SELECT Operation [ σ (r) ] : Select the rows of the relation where the condition is true σ salary >10000 (Employee) : It is commutative, which means it can be applied in any order. Plus, it can be cascaded. σ ..

Structured Query Langauge, Manipulating relational databases, International standard since 1986(ANSI, ISO) SQL is language, and MySQL is DBMS. Web interfaces( e.g., phpMyAdmin) Several notes VARCHAR(20): By specifying the number of characters for memory management purposes. Schema Management: Definition of the table, key management, modify the table - CREATE table, ALTER table, DROP table(NO UND..

SQL은 기본 테이블 형식으로 되어 있어 이해하기가 쉽다. 추후에 NoSQL를 정리할테지만, NoSQL은 정형화되어 있지 않아 처음 데이터베이스 설계시 애를 많이 먹었다. 이 자료는 대학원 석사과정 수업 내용을 요약한 내용입니다. What is a database?: Precisely know what the database means and is worth. : A structured collection of meaningful data. Timeline of Databases 1970-1960: in-company applications - SQL, COBOL, usually per-company, no standardisation, data access slow(Data was stored in t..

1. History of Python : Appeared in 1991, Guido Van Rossum : interpreted, object-oriented, high-level programming language with dynamic semantics 2. Why Python? : Attractive for Agile software development : use as a scripting language, powerful, applicable for GUI, games and more : Open-source, simple and easy, shortcodes, No compilation step(fast edit-test-debug cycle, increased productivity) : ..

1. Data Quality Dimensions Data quality is the capability of data to be used efectively, economically and rapidly to inform and evaluate decisions.” Karr and Sanil (2002) : A dimension is a data item, a record of a dataset or a database that can be used as a parameter of data quality : Measuring data parameters against data standards to evaluate the level of quality of the data or dataset ** For..

1. Metadata: data about data with the attribute - Data that provides information about a specific dataset, focusing on different aspects such as source, resolution, production or accuracy - Multiple purposes: to manage datasets, to report information - It's stored in metadata repositories(which are databases in themselves) 1) Metadata General properties - Sufficiency: Can an object describe itse..

1. Most common data types : Data can be classified according to its main production source 1) Primary Data: Generated/developed and implemented by the user 2) Secondary Data: Collected from Databases which were processed and available by third parties. Primary Data Secondary Date - Own controlled data - generated by the research like surveys, interviews, observations, data mining methods etc. - ..

Database means knowing precisely what the data means and its worth. In other words, it is a structured collection of meaningful data. 1. Timeline of databases 1960 - 70s (In-company applications) 1980 - 2000 (Wider Applications) 2000 + social (Figures are monthly active users) COBOL, SQL(1976) numeric/textual data accounting usually per-company no standardisation data access is slow (think about..

People usually think they know themselves more than anybody. Is it really true? My standard is always quite high. I wanted to be good and better whatever I do. To be honest, I didn't compare with others when it comes to a good outcome. Instead, I often refer to the very high standard or very good outcomes that the other made, and then I compared myself with them. I don't know how, but somehow I ..