The document is an overview of databases, explaining definitions, types, and functionalities like DBMS, database models, and data integrity. It highlights the relational database model introduced by E.F. Codd in 1970, detailing its structure, advantages, and use of SQL. Additionally, it discusses the evolution towards post-relational databases and the emergence of NoSQL and NewSQL systems.

1. Data and its
representation
Ruhulla Abdul
1st year IFF student
Financial University under the Government of
the Russian Federation
Moscow
2014

2. Content
 Database
 DBMS
 Database model
 Relational database
 Ensuring Data Integrity
 Understanding data and data-gathering
 Different parts of a database
 The database planning process
 Post-relational database

3. What is a database?
A database is a storage space for content / information (data)
Data is factual information about objects and concepts, such as:
• measurements
• statistics
You can find it in:
 filing cabinets
 spreadsheets
 folders
 ledgers
 lists
 colleagues’ memories
 piles of papers on your desk

4. Database System
 Database:
A collection of related data.
 Data:
Database System:
DBMS + Database
Known facts that can be recorded and have an
implicit meaning.
 Database Management System (DBMS):
A software package/system to facilitate the
Define, Construct, Manipulate and Share functions of a
computerized database.

5. DBMS
 Software package for defining and managing a database.
 Examples:
 Proprietary: MS Access, MS SQL Server, DB2, Oracle, Sybase
 Open source: MySql, PostgreSQL

6. DBMS Advantages
 Program-data independence
 Minimal data redundancy
 Improved data consistency & quality
 Access control
 Transaction control
 Improved accessibility & data sharing
 Increased productivity of application development
 Enforced standards

7. Typical DBMS Functionality
 Define a particular database in terms of its data types, structures,
and constraints
 Construct or Load the initial database contents on a secondary
storage medium
 Manipulate the database:
 Retrieval: Querying, generating reports
 Modification: Insertions, deletions and updates to its content
 Accessing the database through Web applications
 Share a database allows multiple users and programs to access the
database simultaneously

8. Database model
A database model is a type of data model that determines the logical structure of a database and
fundamentally determines in which manner data can be stored, organized, and manipulated.
Common logical data models for databases include:
 Hierarchical database model
 Network model
 Relational model
 Entity–relationship model
 Enhanced entity–relationship model
 Object model
 Document model
 Entity–attribute–value model
 Star schema
An object-relational database combines the two related structures.
Physical data models include:
 Inverted index
 Flat file
Other models include: Associative, Multidimensional, Multivalue l, Semantic, XML database Named
graph, Triplestore

9. Common types of data models
A database model is a specification describing how a database is structured and used.
Several such models have been suggested. Common models include:
 Flat model - This may not strictly qualify as a data model. The flat (or table) model consists of a
single, two-dimensional array of data elements, where all members of a given column are
assumed to be similar values, and all members of a row are assumed to be related to one
another.
 Hierarchical model - In this model data is organized into a tree-like structure, implying a single
upward link in each record to describe the nesting, and a sort field to keep the records in a
particular order in each same-level list.
 Network model - This model organizes data using two fundamental constructs, called records and
sets. Records contain fields, and sets define one-to-many relationships between records: one
owner, many members.
 Relational model - is a database model based on first-order predicate logic. Its core idea is to
describe a database as a collection of predicates over a finite set of predicate variables,
describing constraints on the possible values and combinations of values.
 Object-relational model - Similar to a relational database model, but objects, classes and
inheritance are directly supported in database schemas and in the query language.
 Star schema - The simplest style of data warehouse schema. The star schema consists of a few
"fact tables" (possibly only one, justifying the name) referencing any number of "dimension tables".
The star schema is considered an important special case of the snowflake schema.

10. Types of data model
Flat model
Hierarchical model
Network model
Relational model
Object-relational model Star schema

11. Relational database
A relational database is a collection of data items organized as a set of
formally-described tables from which data can be accessed or reassembled
in many different ways without having to reorganize the database tables. It is
the most popular example of a database model, which uses a table-based
format.
The relational database was invented by E. F. Codd at IBM in 1970.
The standard user and application program interface to a relational database
is the structured query language (SQL). SQL statements are used both for
interactive queries for information from a relational database and for
gathering data for reports.
In addition to being relatively easy to create and access, a relational
database has the important advantage of being easy to extend. After the
original database creation, a new data category can be added without
requiring that all existing applications be modified.
SQL statements are used to retrieve and update data in a database.

12. Structure of relational model
A relational database is a set of tables containing data fitted into
predefined categories. Each table (which is sometimes called
a relation) contains one or more data categories in columns.
Each row contains a unique instance of data for the categories
defined by the columns. For example, a typical business order
entry database would include a table that described a customer
with columns for name, address, phone number, and so forth.
Another table would describe an order: product, customer, date,
sales price, and so forth.
The Employees table illustrates some of
these relational database concepts. It
has five columns and six rows, with each
row representing a different employee.

13. Structure of relational model
The primary key for this table would generally be the employee number because each one is
guaranteed to be different. (A number is also more efficient than a string for making
comparisons.) It would also be possible to use First_Name and Last_Name because the
combination of the two also identifies just one row in our sample database. Using the last name
alone would not work because there are two employees with the last name of "Washington." In
this particular case the first names are all different, so one could conceivably use that column as
a primary key, but it is best to avoid using a column where duplicates could occur. If Elizabeth
Jones gets a job at this company and the primary key is First_Name, the RDBMS will not allow her
name to be added (if it has been specified that no duplicates are permitted). Because there is
already an Elizabeth in the table, adding a second one would make the primary key useless as a
way of identifying just one row. Note that although using First_Name and Last_Name is a unique
composite key for this example, it might not be unique in a larger database. Note also that the
Employees table assumes that there can be only one car per employee.

14. Databases everywhere
Because of the versatility of databases, we find them powering all sorts
of projects:
 A web site that is capturing registered users
 A client tracking application for social service organisations
 A medical record system for a health care facility
 Your personal address book in your e-mail client
 A collection of word processed documents
 A system that issues airline reservations

15. Ensuring Data Integrity
Information first - Database second

16. Understanding data and data-gathering

17. Different parts of a database
Fields
Records
Queries
Reports

18. Fields
 Database storage units
 Generic elements of content

19. Records
A simple table showing fields (columns) and records(rows):
And as part of an MS Access database table:

20. Queries
 Queries are the information retrieval requests you make to the
database
 Your queries are all about the information you are trying to gather

21. Reports
 If the query is a question...
...then the report is its answer
 Reports can be tailored to the needs of the data-user, making the
information they extract much more useful

22. The database planning process
What kind of database are you working on?
 Information and referral database
 Contact/client database
 Donation database (donorbase)
 Other

23. Information and referral databases
 Store information about service providers
 Track and match requests for referral
 Use a simple design
 Need to be maintained with up-to-date and complete information

24. Contact/client databases
 Store contact information for client base
 Sortable by criteria like:
 Client interests
 Services provided
 Subscription expiry dates
 Last contacted date

25. Donation databases (donorbases)
 Generate reports of donations
 Order or sort donors according to different conditions
 Record the various donation details of each donor
 Create and sort lists of potential and current donors
 Print letters, labels and reports

26. Post-relational database
The relational model, first proposed in 1970 by Edgar F. Codd, departed from this
tradition by insisting that applications should search for data by content, rather than by
following links. The relational model employs sets of ledger-style tables, each used for a
different type of entity. Only in the mid-1980s did computing hardware become powerful
enough to allow the wide deployment of relational systems (DBMSs plus applications). By
the early 1990s, however, relational systems dominated in all large-scale data processing
applications, and as of 2014 they remain dominant except in niche areas. The dominant
database language, standardised SQL for the relational model, has influenced
database languages for other data models.
 Object databases were developed in the 1980s to overcome the inconvenience
of object-relational impedance mismatch, which led to the coining of the term "post-relational"
and also the development of hybrid object-relational databases.
 The next generation of post-relational databases in the late 2000s became known
as NoSQL databases, introducing fast key-value stores and document-oriented
databases. A competing "next generation" known as NewSQL databases attempted
new implementations that retained the relational/SQL model while aiming to match
the high performance of NoSQL compared to commercially available relational
DBMSs.

27. Questions
1) What is a database? Give an example of everyday life database
2) Use the table below to break each content type into fields. Refer to the list of
example fields for suggestions
3) What is DBMS. Why is it so popular?
4) Tell about common types of data models or Draw them
5) Relational Database – what is it? Why it is so popular?
6) Why we use SQL language in relational database?
7) Structure of Relational Database
8) List part of database. Describe them
9) What kind of databases do you know?
10) What is Post-relation database?
11) Difference between Relation and post-relation database

28. References
 http://fakit.narod.ru/uch2003/p4_6_2_3.html
 http://habrahabr.ru/post/152477/
 http://citforum.ru/seminars/cbd99/ardent_1.shtml
 http://en.wikipedia.org/wiki/Database
 https://en.wikipedia.org/wiki/Relational_model
 http://www.webopedia.com/TERM/D/database.html
 http://www.databasejournal.com/
 http://en.wikipedia.org/wiki/Database_model