Databases Course 1 Overview

Course Information

• Course title: Databases Course 1
• Instructor: Anda Belciu, PhD
• Email: [email protected]
• Office: 2017 C
• Additional resources: bd.ase.ro, online.ase.ro

Course Examination

• Examination weighting:
  • 50% seminar work (30% project, mandatory, 20% activity)
  • 50% exam (multiple choice questions + SQL exercises)
• Minimum mark for both seminar and exam sections: 5
• Re-examination: allowed even if seminar grade is below 5
• Oracle Academy online courses (deadline: 16th December 2024) + final exam (week 12): bonus for seminar

Teaching Staff

• Anda Belciu, PhD (groups 1072, 1076)
• Laurențiu Dincă, PhD-candidate (groups 1074, 1075)
• Alin Văduva, PhD-candidate (group 1073)

Bibliography

• C.J. Date, An introduction to database systems, Addison Wesley, 2004, USA.
• R. Elmasri, S. Navathe, Fundamentals of database systems, 7th edition, Pearson, 2016, USA.
• I. Lungu et al., Baze de date. Organizare, proiectare și implementare (Databases. Organization, design and implementation), ASE Publishing House, Second Edition, 2015, Romania.
• A. Belciu, Introduction to Databases, ASE Publishing House, 2016, Romania.

Course Structure

• Database theory
• Data organization in external memory
• Relational databases
• SQL language
• Database development methodology
• Indexing
• Cluster management in relational databases
• Query optimization
• NoSQL databases and other database types

Data, Information, Knowledge, Insight, and Wisdom

• Example:
  • Information: Employee Smith has 40 customers.
  • Knowledge: Employee Smith has 40 customers, while other employees average 20 customers.
  • Insight: 40 vs 20 customers.
  • Wisdom: Employee Smith will have a salary raise.

Big Data Characteristics

• Volume: huge
• Velocity: high speed
• Variety: unstructured
• Variability: data meaning changes constantly
• Veracity: uncertainty of data
• Visualization: charts and graphs
• Value: adds value to the business

Database Definitions

• Database (DB): organized, coherent, structured data, with minimum redundancy and control, accessible to multiple users efficiently.
• Database: a set of interrelated data and their descriptions, including links between data items.

Database Evolution

• Data storage in computers: initially in internal memory (temporary) and then external memory (permanent).
• Improvements in external storage: faster and more efficient access to data, larger data storage capacity, improved data complexity handling, more sophisticated data collection, storage, transmission, and processing tools.
• Databases evolve from simple file systems to integrated systems considering relationships between data and related applications.

Database Generations

• First generation: hierarchical and network databases (until late 70s)
• Second generation: relational databases (late 70s to present)
• Third generation: object-oriented databases (late 80s to present)
• Advanced databases: spatial, multimedia, mobile, NoSQL databases (distributed, cloud, graph)
• Distributed databases vs. centralized databases
• Network databases vs. graph databases

Network Database Example

• Set type in network database structure: owner node (DEPARTMENT) and member node (PERSON).
• Example: department 100: IT, popa anda, moşiloi, 22
• Person 010: petre ion, eminescu, 10

Graph Database Representation

• Correspondence between table rows and graph nodes, displaying properties and values through key-value pairs.

Data Structure Types: Files and Databases

• Files: Data stored in programs (e.g. C example).
  • Data is in main file (e.g., .txt).
• Databases: Data stored in database dictionary (e.g. oracle example).
  • Data kept separately in a disk file (e.g., .db).

Database Components

• Database structure: files, records, fields, values
• Range of values: possible values for a feature in a system
• Feature (attribute): defining characteristic of an entity
• Family of features: characteristics describing an entity
• Data collection (entity): common characteristics used to derive data connections/meanings