This document discusses programming concepts, data management, and technology applications. It covers topics such as programming logic, object-oriented programming, data types, file structures, databases, and database models. Specifically, it defines key terms related to programming semantics, pseudocode, sequential logic, looping logic, decision logic, and event-driven programming. It also defines terms related to objects, classes, methods, and data structures like arrays, stacks, queues, and trees.

1. Programming Concepts, Data
Management and Technology
Applications
This section will make up 25% of the questions on the exam.

2. Programming
 Semantics – the study of the interpretation (meaning) of a word or statement.
 Pseudocode – the act of writing a computer algorithm in a manner that can be read.
(instead of using machine language, human language is used for the logic of a program”
 Programming logic – using human thinking in order to give reason (logic) to a program
that will be used to do a certain task or calculation.
 Sequential programming logic – statements that are executed a single time.
 Looping programming logic – statements that are executed a specific number of times.
 Decision (Selection) programming logic – selects a choice from a number of things that
can be performed based on the outcome of another condition. (An “If” “And” statement)
 Event-driven programming – programming that triggers a certain response when an
event (something that has occurred) happens.

3. Cont.
 Object oriented programming (OOP) – sees everything as an
object (an entity that exists by itself in the world) and operates
under the assumption that every object has a unique identity.
 State of objects – every object has a “state.”
 Behavior – an objects behavior is controlled by methods.
 Classes – objects that are of the same type are considered to be
in the same class. All objects in the same class are associated
with the same methods and data fields.
 Object instantiation – the process of creating an object.
 Object and instance can be used synonymously.

4. Cont.
 Method – something that can be done to change the state of an object.
 Static (class) method – when a method is associated with a class as a whole.
 Instance method – a method that is related to an object or instance of a class.
 Accessor method – provides access to a different state of an object.
 Constructor method – is used when an object belonging to a class is created.
 Destructor method – is used when an object belonging to a class doesn’t exist anymore.
 Mutator method – a method that modifies the state of an object.
 Dummy codes – are used to simulate a process in order to avoid receiving an error code.

5. Data
 Data type – sets the standard for what kind of data can be entered into a table and the
kind of operations that can be performed on that data.
 Integer data – whole number values.
 Real number (floating) data – data that holds a value. Ex. GPA
 Single character data – used to store a single character. Ex. ‘D’
 String data – stores a sequence of values (bytes).
 Enumerated data– allow a programmer to insert their own data into a program.
 Binary (machine-readable) data – binary data that is intended to be read by computers.
 GIF, JPEG Files – animated images.
 Boolean data – uses 0’s and 1’s.

6. Cont.
 Data structure- how data is stored in a system.
 Abstract data type (ADT) – a user-defined data type that is used to set pre-programmed data types ex.
Data/Time.
 File – data that is interpreted as a single unit.
 Program files – a folder where all applications not involved with the OS are stored by default.
 Binary files – unformatted files that stores data exactly how it looks to a computer.
 Text files – formatted files that store formatted data.
 Data files – contain data that can be read/processed by a program file.
 Sequential access files – files that contain data that must be read sequentially.
 Random access files – files that can be accessed without having to go through other files.
 Digital files –files stored as either 0 “off” or 1 “on”

7. Cont.
 File name extensions – Let your OS know what kind of file it is or what program was
used to create it. (ex. .Doc or .PPT)
 File path – begins with the letter of the drive, followed by folders and subfolders until you
reach your desired file. A files path can be represented as a hierarchical tree.
 File structure – how a data is stored within a file.
 Hierarchical file structure – displays folders as a “family tree”
 Parent node – “letter drive” or the root directory level
 Level 1 – child nodes of the parent node and parent nodes of the level 2 nodes
 Level 2 – child nodes of the level 1 node and parent nodes of the level 3 nodes
 Level 3 – child nodes of the level 2 nodes

8. Cont.
 Network file structure – arranges files into groups know as sets, which are connected to
one another in various ways.
 Sequential file structure – a file that is structured in the order of which the contents/data
were created.
 Hash table – created when a hash function is used to a record store in RAM
 Hashing scheme – is divided up into buckets which can store several records.
 One-dimensional array (List) – stores data that is of the same type under one group
name. In order to access each element you use its “subscript” which is its position in
respect to the starting position
 Heterogeneous array- data types that are different
 String – a collection of characters (each character takes up one byte of memory”
 Homogenous two-dimensional array – a collection of data items (of the same type) that
are displayed in columns and rows.

9. Cont.
 Stack data structure – items are only inserted and removed from the top of the
stack. “Last in, first out”
 Queue data structure – items are added to the end and taken from the
beginning. “First in, first out”
 Head – the beginning of a queue data structure.
 Tail – the end of a queue data structure.
 Tree data structure – data is stored in a hierarchical chart. Each location is a
node. The top node is called the “root node.” Any node above another node is
a parent node and any node that is the last in its sequence is a “leave” or
terminal node. Two nodes with the same parent are considered siblings.
 Binary tree – a tree that does not allow for a parent node to have more than
two child nodes.

10. Structure
 Array (list) – data is stored in a sequential order deepening on the field it falls into.
 Linked lists – is used when items from the list are deleted or added frequently. It differs from an array
because an additional field is used. The additional field is called a pointer, it is used to quickly
find/identify the next record in the list. Data can be added to the beginning or end of a lined list.
 Head pointer – the first item on a list.
 Tail pointer – the last item on a list.
 Single linked lists – each item has a pointer pointing to the next piece of data and not the one behind
it.
 Double linked lists – each item has a pointer pointing to the piece of data before and after it.
 Database Manage System (DBMS) – allows one to interact with a database.
 Data management – is used to manage the data that is stored in a database or computer’s memory.
 Data browsing – the process of going through files to find a specific file or piece of information.

11. Cont.
 Data modeling – is the structure used to create a database. It allows for easier collection,
storage, modification and retrieval of information.
 Data maintenance – is used to keep data up-to-date and accurate.
 Database administration – is performed by the Databases administrator.
 Data mining – a process that searches through and analyzes data for useful information.
Data Mining Tasks
1. Collecting the data
2. Creating groups of data
3. Creating associations between the data
4. Establishing patterns between the data

12. Cont.
 Data warehousing – a spot that stores data from multiple databases in one area.
 Centralized warehousing – stores data in one location.
 Decentralized warehousing – stores data regionally.
 Data mart – a small subset of a data warehouse.
 Metadata – data about data.
 Data integrity – makes sure that the data being stored is accurate.
 Data consistency – makes sure that the same value of data is present in different
locations in the database.
 Data corruption – when data that was stored can no longer be read because it was
damaged.
 Data loss – when data that was stored can no longer be retrieved.

13. Databases
 Database models – explain the relationships among the components of a database.
 Hierarchical data model – a tree like structure that is not efficient for showing repeating data
(explained earlier).
 Network data model – a model were each record is joined in a 1:M relationship, where each point can
have multiple parents.
 Relational data model – the most widely used model today.
 Structured query language (SQL) –is used to create database structure.
 Functions of SQL – Creating objects in a database and performing manipulative operations on that
data.
 Hybrid database – a combination of multiple database types.
 Entity relationship model (ERM) – describes relationships between entities.
 Data bases maintain integrity and consistency by establishing relationships among entities.

14. Cont.
 Data redundancy occurs when the same data is stored in multiple locations, this can cause data
inconsistency.
 Backup and recovery procedures – protect against lost data by being able to restore it.
 Physical security – actual security of the area where a computer or data is stored.
 Logical security – logins, passwords etc.
 SQL – allows for users to interact with a database without knowing how the database acts internally.
Ex. Of SQL commands: INSERT, UPDATE, DELETE, SELECT etc.
 Batch processing – data is collected for a period of time and then processed at once.
 Transactional processing – data is processed as it is collected. When a failure occurs, you can view
the data up to the failure. Using a batch processing all of the data would be lost.
 Online transaction processing (OLTP) – occurs when a purchase is made online.

15. Cont.
 Bit – the smallest unit of data (8 bits = 1 byte)
 Computers only understand binary or machine language.
 Character –the most simple unit of meaningful information.
 Entity – anything that data can be collected on.
 Field – the most simple unit of data in a database table.
Requirements to Describe a Field
1. Name of the field
2. Data types in the field
3. Length (size) of the field
4. Format of the values

16. Cont.
 Record – a group of fields that are related.
 File (relation or table) – where data is stored in either columns, rows or both.
 Relational database (RDB) – a collection of tables that have a common
attribute. This allows for cross checking of data between different tables.
 Primary key (PK) – a column name that is used to identify a row or record in a
table.
 Composite primary keys – two columns that when used together identify a
record in a table.
 Foreign key – a column in one relation that serves as a primary key in another
relation. Foreign keys can repeat themselves.
 Domain – a collection of values that can be used for a field in a table. Ex. For
a letter grade A, B, C and D would all be “acceptable” values.

17. Cont.
Relationships between Two Tables
1. 1:1 relationship – when only 1 row in table #1 matches only 1 row
in table #2 and vise versa.
2. 1:M relationship – when 1 row in table #1 matches more than
one row in table #2 and only 1 row from table 3#2 matches at
most one row in table #1.
3. M:N relationship – if more than one row in table #1 matches more
than one row in table #2 and vise versa.
 Constraints – restrictions placed on data that is stored in a certain
field.
 Query – a question that is used to retrieve data from a database.