- Data – some values obtained by observation or measuring.
- Information – interpretation of data and relations between them.
- Data which lower entropy of the systems.
- Repeated / duplicated data bear no information.
- Database – a generic structure for storing data;
- could be even a file system.
- Database system – an application managing data in a database.
- Interface – means for connecting systems together.
- The goal is to obtain information from data.
- The majority of BDP applications are Information Systems:
- Company Information Systems
- contain a collection of many different agendas (SIS),
- e.g. finance, inventory, facility,
- they are not just the software.
- Specialized Information Systems
Separate Information Systems
- The company information system is composed of unrelated sub-systems (SIS):
- each system has its own application code,
- each system has its own data store.
- Format and structure of data are tied to each sub-system requirements:
- therefore they are incompatible,
- where there is incompatibility, there is isolation,
- where there is isolation, there is redundancy,
- where there is redundancy, there is inconsistency.
- No one wants inconsistency.
Separate Information Systems
- Isolation and incompatibility – data can be used only by the ‘owning’ application.
- Data is unreadable (unknown or proprietary format).
- Data is unintelligible (no documentation).
- Redundancy – one piece of data in multiple locations.
- Do not confuse with backups (no master – copy).
- Inconsistency – occurs when redundant data is incompletely updated.
- Civil service is a good (bad ?) example.
- Ad-hoc queries are very expensive (substantial effort or new application).
- Difficult to ensure data integrity and security.
- Integrity – the state of the data (database) when all data is complete and correct.
- What is correct is determined by integrity constraints, e.g:
- Age is a positive integer.
- Every person is of some age (her age cannot be empty).
- Every person has an address (his address cannot be empty).
- Integrity constraints are not easy!
- Integrity violation occurs usually as a result of bad data sanitization.
Separate Information Systems
- How it happens:
- development of the company – leftover legacy systems which do not integrate;
- company merger – difficult to integrate information systems together (imagine a bank);
- lack of money – cheap solution which does not adapt to existing systems (and does not integrate well);
- surplus of money – expensive solution – DTTO;
- laziness – no one cared for integration effort.
Integrated Information System
- Ensures that data has one true master version:
- using a centralized database:
- all applications connect to a single database server;
- does not need to be physically a single machine;
- classic approach.
- using distributed database or a collection of APIs:
- data may be distributed over various systems;
- each piece (or rather class) has master origin.
(Centralized) Database system
- Data is stored and managed in one place.
- Data files have set structure, hidden to outside world.
- Data may be accessed only through the DBS interface.
- Database system takes care of concurrent access of multiple users, permissions and data integrity.
- Database system operations are optimized to lower time complexity.
- OLTP – Online Transaction Processing:
- the foundation of all – processing of daily operations,
- every information system must have this,
- DWH – Data Warehouse:
- analytical systems, analytical queries,
- large amount of read data, almost no data written.
- special analysis – text processing, image processing, predictions, etc.
- Different technologies, but SQL language is used in most DBS.
- Focus on OLTP, because that is the starting point.
- A set of resources to model and describe data.
- The output of DM is a database schema – declaration of the database structure (database template).
- Different tools:
- graphs (from graph theory),
- relations (sets),
- Database is something which can hold data.
- Database schema is the description of a database structure.
- Object data model and relation data model are two approaches to the same problem.
- Data is organized in tree-like structures.
- The relation between records is parent-child.
- A child has one parent.
- One parent can have more children.
- It is not very suitable for general-use databases, special uses:
- DNS, LDAP,
- file systems (links ignored),
- XML (partially HTML).
- An extended hierarchical model.
- Each record (vertex) can be connected to any number of different vertices.
- Handles relations 1:N, M:N and cyclic relations.
- Very universal and flexible, no usable implementations.
- Considered as a Network model with limitations:
- a file system (links not ignored),
- HTML DOM (Document Object Model).
- Describes data with relations (something like a table, will explain later).
- Designed around 1970 (E. F. Codd, in IBM).
- Built on hard maths – relational algebra.
- Relational database system – RDBS.
- Gave birth to and uses the SQL language for querying.
- DB2 (IBM), Firebird, MySQL,
- Oracle Database, PostgreSQL, SQL Server (Microsoft), etc.
- A combination of the object and relational model:
- The SQL query language or similar;
- relational implementation of a database structure;
- data results in form of objects;
- supports class hierarchy, inheritance and encapsulation;
- supposedly faster than converting from RDBS;
- supports multi-valued attributes.
- Instead of records, objects are returned.
- Pure object databases do also exist.
- Transaction – one action, optionally composed of multiple operations
(e.g. insert a person together with contact information and meetings, …).
- Atomicity – either all operations in a transaction must be performed,
or none of them (rollback).
- Consistency – before and after the transaction, the database is in
a consistent state, during the transaction it may not be (imagine buying something).
- Isolation – concurrently running transactions behave as if they
are running sequentially.
- Durability – a finished transaction is permanent.
- ACID is what common sense expects from a database.
SQL × NoSQL
- Virtually all ACID databases use the SQL language or some SQL dialect or a similar language.
- The other option is BASE:
- Basically Available, Soft state, Eventual consistency;
- if a record is not updated any more, all queries to that record will
eventually return consistent results;
- unusable for an ordinary information system;
- required for massive distributed services;
- somewhat related to NoSQL databases (key-value databases) = associative array, graph, document, …);
- There are also columnar and key-value databases which may by either ACID or BASE.
- May one database system contain multiple databases?
- What is the direct outcome of redundant data in an information system?
- Is is possible to run two transactions at once in an ACID database?
- Is an information system only software?
- Is data better than information?
- How is information transmitted?
- Does every DBS have to use the SQL language?
- Should accounting use an ACID or a BASE database ?
- What are differences between the object data model and the relational data model?