MY_ASSIGNMNT

DATA TYPES
1. What are they?
a. A data type (or datatype) in programming languages is a set of values and the operations on those values.

2. What roles do they play in database?
a. They determine what kind of data will be processed or will become input.

3. 3 Database Management Systems Program
a. Visual FoxPro
Visual FoxPro is a data-centric object-oriented and procedural programming language produced by Microsoft. It is derived from FoxPro (originally known as FoxBASE) which was developed by Fox Software beginning in 1984.
b. SQL
SQL (Structured Query Language) (pronounced /ˌɛskjuːˈɛl/)[1] is a database computer language designed for managing data in relational database management systems (RDBMS). Its scope includes data query and update, schema creation and modification, and data access control. SQL was one of the first languages for Edgar F. Codd's relational model in his influential paper, "A Relational Model of Data for Large Shared Data Banks".[2] and became the most widely used language for relational databases[3][4]
c. FoxPro
FoxPro is a text-based procedurally-oriented programming language and DBMS, originally published by Fox Software and later by Microsoft, for MS-DOS, MS Windows, Apple Macintosh, and UNIX.

Kinds of Data Types and Description
a. integer : In more common parlance, whole number; a number that has no fractional part.
b. floating-point : A number with a decimal point. For example, 3 is an integer, but 3.5 is a floating-point number.
c. character (text ): Readable text

MVvsdataF

MEMORY VARIABLE

The memory of a computer is organized into a regular pattern of containers for information. These containers for information are called "words". Each one has a numeric address and each one is the same size as each of the others. For most applications, it is inconvenient to refer to portions of memory by their numeric addresses, so programming languages allow us to allocate portions of memory by name. When we store information in the memory of a computer we need to decide on how much we need for various purposes and on how it will be organized. Programming languages provide mechanism for "types" of information in memory. They also provide mechanisms to identify repetitive arrays of items of the same type and to aggregate possibly heterogeneous types under a common name.

Conceptually the memory in a computer is very much like building lots laid out by lot number on a map of the streets of a city before any houses have been built.

It may be convenient to refer to buildings by names that help us remember who lives there. In using computer memory, can be helpful to refer to allocated portions of computer memory by names that help us remember the uses to which we are putting those portions of storage. In computing we call such names "variable" names.

A house has rooms into which we may cram only a certain amount of furniture. The words in a computer have a certain capacity, given in "bits", "nibbles", "characters", "bytes", "octets" "half-words" and other terms intended to convey a sense of smaller or larger portions of a word.

On modern computers, all the units of storage are effectively given in terms of "bits". A bit is a portion of memory which can hold either a "0" or a "1". The other terms mentioned above gone through historic changes and are likely to change again. Different computer manufacturers favored different numbers of bits in, say, a byte.At present, for the most popular desk-top computers and workstations, there is considerable agreement on the following sizes:

DATA FIELD

A data field is a place where you can store data. Commonly used to refer to a column in a database or a field in a data entry form or web form.

The field may contain data to be entered as well as data to be displayed.

A specific area of an electronic record allocated for a particular category of data, usually one data element, such as a name.

A data field is the smallest subdivision of the stored data that can be accessed. A data field can be used to store numerical information such as price, count or a date or time, or even a data and time. A pair of data fields can be used in combination to hold a geo-spatial coordinate. Also, a data field can be used to hold a block of text. A data field takes up permanent storage within the data-store.

The data-store is composed of a number of data records which are, in turn, composed of a number of predefined data fields. Each of these data fields must be defined within the Load Definition File with a unique name.

Data Types
A data field can be any one of four types:

Type	Description
Signed numeric data	Includes numeric values, bit masks, times and dates. May be filtered, sorted, displayed and used within formulas of all types.
String data	Consists of text blocks not exceeding 255 characters. May be sorted and displayed by Flexible Search.
Text data	Consists of text blocks of unlimited size. May only be displayed by Flexible Search, not sorted.
Attribute data	An array of boolean flags that can be turned on or off to set and check specific criteria. An attribute type can hold up to 1024 different attribute flags, each of which can be set to either true or false. However, space should only be set aside for the number of attributes required.

Temporary Fields
In addition, a numeric, string or text data field can be marked as temporary. Temporary fields are used for calculating values or indexing data. A temporary field is like a data field, but it does not take up any permanent storage within the data-store. It is used as a scratch location for holding temprorary data while it is being indexed or used within an expression to generate permanent data for a data field.

_TERMCONTRAST_

DATA vs. INFORMATION

Data is raw material & unorganized facts
that need to be processed
When data are processed, organized, structured or
presented in a given context so as to make them useful,
they are called Information.

Data are plain facts. The word "data" is plural for "datum."
When data are processed, organized, structured or presented in a
given context so as to make them useful, they are called Information.

It is not enough to have data (such as statistics on the economy).
Data themselves are fairly useless. But when these data are interpreted
and processed to determine its true meaning, they becomes useful and
can be called Information. Data is the computer's language.
Information is our translation of this language.

COMPUTER STORAGE vs. DATA STORAGE

Computer storage - an electronic memory device; "a memory and the CPU form
the central part of a computer to which peripherals are attached"
Computer data storage, often called storage or memory, refers to computer
components, devices, and recording media that retain digital data used
for computing for some interval of time. Computer data storage provides
one of the core functions of the modern computer, that of information
retention. It is one of the fundamental components of all modern computers,
and coupled with a central processing unit (CPU, a processor), implements
the basic computer model used since the 1940s.
In contemporary usage, memory usually refers to a form of semiconductor
storage known as random access memory (RAM) and sometimes other forms of
fast but temporary storage. Similarly, storage today more commonly refers
to mass storage - optical discs, forms of magnetic storage like hard disks,
and other types slower than RAM, but of a more permanent nature. Historically,
memory and storage were respectively called primary storage and secondary storage.
The contemporary distinctions are helpful, because they are also fundamental
to the architecture of computers in general. The distinctions also reflect
an important and significant technical difference between memory and mass
storage devices, which has been blurred by the historical usage of the term storage.
Nevertheless, this article uses the traditional nomenclature.

Data Storage
Data storage can refer to:

* Computer data storage; memory, components, devices and media that retain digital computer data used for computing for some interval of time.
* Any data storage device; that records (stores) or retrieves (reads) information (data) from any medium, including the medium itself.


OPERATING SYSTEM vs. COMPUTER SYSTEM

Operating system (commonly abbreviated to either OS or O/S) is an
interface between hardware
and user; it is responsible for the management and coordination
of activities and the sharing of the resources of the computer.
The operating system acts as a host for computing applications that are
run on the machine. As a host, one of the purposes of an operating system
is to handle the details of the operation of the hardware. This relieves
application programs from having to manage these details and makes it
easier to write applications. Almost all computers (including handheld
computers, desktop computers, supercomputers, video game consoles) as
well as some robots, domestic appliances (dishwashers, washing machines),
and portable media players use an operating system of some type. [1] Some of
the oldest models may however use an embedded operating system, that may be
contained on a compact disk or other data storage device.

Computer System:
A complete, working computer. The computer system includes not only
the computer, but also any software and peripheral devices that are
necessary to make the computer function. Every computer system, for example,
requires an operating system.

SEARCH

A. DEFINITIONS: -DATA STRUCTURE-

1.Data Structure is the structure that is formed and used by users or programmers to facilitate the processed datas that are needed to be stored. Making or providing structure depends on how or what certain kind of datas it would be stored to properly hold the datas in a memory. Memory is a part when we take data structures. With data structure, it would be convenient to work with datas in memory. Examples of structures are:stacks, linked-list, queues, arrays, graphs, trees, etc. It is also a way of storing data into the computer so that it would be used efficiently with the use of certain algorithms to operate it in the memory space.-personal definition...

2. Data structure in computer science is a way of storing data in a computer so that it can be used efficiently. It is an organization of mathematical and logical concepts of data. Often a carefully chosen data structure will allow the most efficient algorithm to be used. The choice of the data structure often begins from the choice of an abstract data type -http://en.wikipedia.org/wiki/Data_structure

3.An organization of information, usually in memory, for better algorithm efficiency, such as queue, stack, linked list, heap, dictionary, and tree, or conceptual unity, such as the name and address of a person. It may include redundant information, such as length of the list or number of nodes in a subtree.
-http://www.itl.nist.gov/div897/sqg/dads/HTML/datastructur.html

4. In computer science, an organization in software of data that allows more optimal searching, categorizing, or storage of information. Examples: matrix, stack, queue, dequeue, list, vector, scene graph.
-http://en.wiktionary.org/wiki/data_structure

5.A data structure is a specialized format for organizing and storing data. General data structure types include the array, the file, the record, the table, the tree, and so on. Any data structure is designed to organize data to suit a specific purpose so that it can be accessed and worked with in appropriate ways. In computer programming, a data structure may be selected or designed to store data for the purpose of working on it with various algorithms.
-http://searchsqlserver.techtarget.com/sDefinition/0,,sid87_gci804744,00.html

6. A means of storing a collection of data. Computer science is in part the study of methods for effectively using a computer to solve problems, or in other words, determining exactly the problem to be solved. This process entails (1) gaining an understanding of the problem; (2) translating vague descriptions, goals, and contradictory requests, and often unstated desires, into a precisely formulated conceptual solution; and (3) implementing the solution with a computer program. This solution typically consists of two parts: algorithms and data structures.
-http://www.answers.com/topic/data-structure

7. A data structure is a group of data elements grouped together under one name. These data elements, known as members, can have different types and different lengths.
http://www.cplusplus.com/doc/tutorial/structures.html

8. The way data is encoded by a computer. Data structure is not usually the concern of the user. However, in certain cases, e.g. when the user tries to read a text file produced by a different word processor he or she may become aware of the fact that similar screen display does not necessarily mean identical data structure for the computer.
-http://www.uni-duisburg-essen.de/CP/key_terms.htm

9. A way to store and organize data in order to facilitate access and modifications.
- www.azdoqit.com/LS4/Glossary%20of%20EHR%20Terms.doc

10. An organised aggregate of data items. -http://www.cs.ucc.ie/~dgb/courses/swd/glossary.html

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B. 3 DATA STRUCTURES UNCOVERED

B.1 VLIST DATA STRUCTURES

-In computer science, the VList is a persistent data structure designed by Phil Bagwell in 2002 that combines the fast indexing of arrays with the easy extension of cons-based (or singly-linked) linked lists.^[1]

OPERATIONS TO ENTER ELEMENTS(DATA)

The primary operations of a VList are:

• Locate the kth element (O(1) average, O(log n) worst-case)
• Add an element to the front of the VList (O(1) average, with an occasional allocation)
• Obtain a new array beginning at the second element of an old array (O(1))
• Compute the length of the list (O(log n))

STRUCTURE

The underlying structure of a VList can be seen as a singly-linked list of arrays whose sizes decrease geometrically; in its simplest form, the first contains the first half of the elements in the list, the next the first half of the remainder, and so on. Each of these blocks stores some information such as its size and a pointer to the next.

The average constant-time indexing operation comes directly from this structure; given a random valid index, we simply observe the size of the blocks and follow pointers until we reach the one it should be in.

DATA RETRIEVAL

Any particular reference to a VList is actually a <base, offset> pair indicating the position of its first element in the data structure described above. The base part indicates which of the arrays its first element falls in, while the offset part indicates its index in that array. This makes it easy to "remove" an element from the front of the list; we simply increase the offset, or increase the base and set the offset to zero if the offset goes out of range. If a particular reference is the last to leave a block, the block will be garbage-collected if such facilities are available, or otherwise must be freed explicitly.

Because the lists are constructed incrementally, the first array in the array list may not contain twice as many values as the next one, although the rest do; this does not significantly impact indexing performance. We nevertheless allocate this much space for the first array, so that if we add more elements to the front of the list in the future we can simply add them to this list and update the size. If the array fills up, we create a new array, twice as large again as this one, and link it to the old first array.

B.2 HASH TABLE

-In computer science, a hash table, or a hash map, is a data structure that associates keys with values.

THE STRUCTURE

The primary operation that hash functions support efficiently is a lookup: given a key (e.g., a person's name), find the corresponding value (e.g., that person's telephone number). It works by transforming the key using a hash function into a hash, a number that is used as an index in an array to locate the desired location ("bucket") where the values should be.

Hash tables support the efficient lookup, insertion and deletion of elements in constant time on average (O(1)) that does not vary with the number of elements stored in the table; although may vary somewhat depending on how full the table is.

BASIC OPERATION

A hash table works by transforming the key using a hash function into a hash, a number that is used as an index in an array to locate the desired location ("bucket") where the values should be. The number is normally converted into the index by taking a modulo operation, or sometimes bit masking is used where the array size is a power of two. The optimal hash function for any given use of a hash table can vary widely, however, depending on the nature of the key.

It is also possible to create a hash table statically where, for example, there is a fairly limited fixed set of input values - such as the values representable by a single byte (or possibly two bytes ) from which an index can be constructed directly (see section below on creating hash tables). The hash table can also be used simultaneously for tests of validity on the values that are disallowed.

LOAD FACTOR: ACCOMODATE

An important property of a hash table is how "full" the table is, that is the ratio between the number of entries n and the size s of the hash table (i.e. the size of the array it uses to store values). The quotient n/s is therefore called the load factor of the hash table.

Most hash table implementations only perform well if the load factor is kept in acertain range.

RETRIEVAL

Hash tables store data in pseudo-random locations, so accessing the data in a sorted manner is a very time consuming operation. Other data structures such as self-balancing binary search trees generally operate more slowly (since their lookup time is O(log n)) and are rather more complex to implement than hash tables but maintain a sorted data structure at all times.

B.3 HEAP DATA STRUCTURE

THE STRUCTURE
-In computer science, a heap is a specialized tree-based data structure that satisfies the heap property: if B is a child node of A, then key(A) ≥ key(B). This implies that an element with the greatest key is always in the root node, and so such a heap is sometimes called a max heap. (Alternatively, if the comparison is reversed, the smallest element is always in the root node, which results in a min heap.) This is why heaps are used to implement priority queues. The efficiency of heap operations is crucial in several graph algorithms.

OPERATION TO GET CONTENTS ON THE NODES:

The operations commonly performed with a heap are

• delete-max or delete-min: removing the root node of a max- or min-heap, respectively
• increase-key or decrease-key: updating a key within a max- or min-heap, respectively
• insert: adding a new key to the heap
• merge: joining two heaps to form a valid new heap containing all the elements of both.

Comparison of theoretic bounds for variants

The following complexities^[1] are worst-case for binary and binomial heaps and amortized complexity for Fibonacci heap. O(f) gives asymptotic upper bound and Θ(f) is asymptotically tight bound (see Big O notation). Function names assume a min-heap.

Operation	Binary	Binomial	Fibonacci
createHeap	Θ(1)	Θ(1)	Θ(1)
findMin	Θ(1)	Θ(lg n) or Θ(1)	Θ(1)
deleteMin	Θ(lg n)	Θlg n)	O(lg n)
insert	Θ(lg n)	O(lg n)	Θ(1)
decreaseKey	Θ(lg n)	Θ(lg n)	Θ(1)
merge	Θ(n)	O(lg n)	Θ(1)

For pairing heaps the insert and merge operations are conjectured^{[citation needed]} to be O(1) amortized complexity but this has not yet been proven. decreaseKey is not O(1) amortized complexity [1] [2]

HEAP RETRIEVAL

Heaps are a favorite data structures for many applications.

• Heapsort: One of the best sorting methods being in-place and with no quadratic worst-case scenarios.
• Selection algorithms: Finding the min, max or both of them, median or even any k-th element in sublinear time^{[citation needed]} can be done dynamically with heaps.
• Graph algorithms: By using heaps as internal traversal data structures, run time will be reduced by an order of polynomial. Examples of such problems are Prim's minimal spanning tree algorithm and Dijkstra's shortest path problem.

Interestingly, full and almost full binary heaps may be represented using an array alone. The first (or last) element will contain the root. The next two elements of the array contain its children. The next four contain the four children of the two child nodes, etc. Thus the children of the node at position n would be at positions 2n and 2n+1 in a one-based array, or 2n+1 and 2n+2 in a zero-based array. Balancing a heap is done by swapping elements which are out of order. As we can build a heap from an array without requiring extra memory (for the nodes, for example), heapsort can be used to sort an array in-place.

One more advantage of heaps over trees in some applications is that construction of heaps can be done in linear time using Tarjan's algorithm.

HEAP IMPLEMENTATION

• The C++ Standard Template Library provides the make_heap, push_heap and pop_heap algorithms for binary heaps, which operate on arbitrary random access iterators. It treats the iterators as a reference to an array, and uses the array-to-heap conversion detailed above.

Array Implementation-ITS 116(MWF-3-4)

When accessing datas using the Array Data Structure, the datas are called the elements in Array. Elements are declared into a single index size like, array[10]={DATA_1, DATA_2, DATA_3, DATA_4}.

We have 4 datas to be accesed in the structure which means we will have 4 elements. (*Think that the 4 datas are the 4 grades of 4 students in a class. The 4 grades has also 4 remarks each whether above average, average, below average depending on their grades.)

We named the four datas as: DATA_1, DATA_2, DATA_3, DATA_4 thus, we will have the syntax to declare as array[10]={DATA_1, DATA_2, DATA_3, DATA_4}. Our flag pointer here is the name 'array' itself where all access of the 4 datas take place. When we input the DATA_1(first data) to the 'array', the array holds it until another data will come(DATA_2). Now, the 'array' holds 2 datas, we will add again another data(DATA_3) to the array and the last data(DATA_4) to the array also. This time the array holds 4 datas. When there's no more data to be added, the array will now index the datas which means each of the unique data will be processed. When all had been done, we wish to empty the array. We can choose which one should we emptied or it can be that all the datas will be emptied inside so that the array would be empty again and ready to contain another datas.

116B Survey KH21

Linear Structure & Non-linear Structure in Data Structures

A data structure is linear if every item is related (or attatched) to its previous and next item(e.g.array, linked list) and it is non-linear if every item is attached to many other items in specific ways to reflect relationships(e.g, n-ary tree). In linear data structure data items are arranged in a linear sequence. In non-linear data structure data items are not in a sequence.

116B Survey KH14

THE EARTH STRUCTURE
A. The Earth is not a round.
B. It is an Oblate Spheroid.

C. It is made up of three major composition
(lithosphere,hydrosphere,& atmosphere).

D. There are three layers of the Earth(Crust,Mantle,& Core).
E. Three-fourths of its part is composed of water while the one-fourth is the land mass.
F.The atmosphere is filled with various kind of gases.

THE STRUCTURE OF THE EGG
A. The egg is oval in shape.
B. It has outer covering called egg shell.
C. Inside of it is the semi-fluid called egg yolk which is color yellow.
D. The white part of it is called egg-white.
E.Its size resembles that of human fist.