Do You Know Where We Store our Computer Data?

8:23 am Unknown 0 Comments

Storage devices are the devices where we electronically store/record data in the computer. Storage devices can be removable or non-removable depend on their type. Most commonly used storage devices are non-removable  can be found inside of CPU casing. Storage devices can be classified into 3 three different categories Primary, Secondary and Tertiary storage devices. These devices are non-volatile storage devices means they don't lose data when powered off. Before we move on you may already know that computer does any kind of data transferring in form of bits (0,1). Some of the common storage devices are:

1. Floppy Disk Drive

Floppy disk drive is basically an input/output device. It was one of the most popular storage device of the past and still it is for some people. However, today USB flash drives replacing it as one of the better alternative of floppy disk drives. Floppy disk is basically a circular shaped flexible plastic which closed inside a solid plastic cover layered with soft foam on both sides.
One of the main reason of floppy disk’s popularity is the cheap price and capability of data read/write. The data stored in floppy disk is portable and you can transport it to any other computer that has floppy disk drive installed already. Floppy disks are getting rare now, because of high data corruption rate, slow data transfer(read/write), and very small data storage capacity of only up to 1.44 Megabyteswhich is one of the biggest disadvantage of it. Anyways, It could still be a good option to make the backup of your small documents like a Microsoft Word document or some low-resolution images, etc.


Do You Know
 You may wonder that some businesses and industries still regularly use floppy disk drives. Personally I had seen someone installing Windows 3.x using four floppy disks for embroidery machines.

2. Hard Disks or HDD:

A Hard disk consists of one or more circular disks of aluminum or other metal alloy coated with magnetic material on both sides. It’s a mass storage device capable tostore large amount of data for long time-period with higher data transfer rate(read / write data). That’s why an HDD is the most common part of any system. A hard disk is commonly a Fixed disk since they can be found inside of a CPU casing, but lacks in capability of moving data from one to another place. 

Note: We use portable hard drives (or External HDD) which allows to move large amount of data anywhere stored inside of an external HDD.
One of the greatest speed factor of hard disk is instead of reading the stored data inside a hard disk from the beginning it directly reaches to the exact location where data is actually stored (i.e direct access device). A hard disk can be used to store OS files, applications, files and folders etc. We'll discuss about hard disk speed factors to help you to buying good quality hard drives.


3. Optical Storage Media:

i) CD ROM (CD-R and CD-RW) 
CD ROM is an abbreviation of Compact Disk Read Only Memory also a common storage device. As we said above hard disk drives read/writes data at much faster rate than a floppy disk, then why we still need a CD ROM, and the simple answer is a CD can store up to 700 MB of data in it and allows to move CD data from one place to another with ease and portability. On the other hand, floppy disk can store up to 1.44 MB which is not just enough today. It's also very cheap to buy a CD and software development companies are selling their softwares in CDs. You can get a complete version of of their softwares within single CD. 

Let's give you an example, in past when CDs were not available Microsoft Office had supplied with 32 floppy disks, But thanks to the invention of optical storage media and CD ROMs now this software is available in one CD or DVD for latest versions. You can install softwares from CDs more quickly than a floppy disk drive due to better data transfer rate of CD ROMs.


 CD-R: Used for read-only data, allows one-time data recording on the disk.  It’s an abbreviation of Compact Disk Recordable. 
CD-RW or CD Burner: Used for reading / writing / erasing of data to a CD more than once. CD-RW is an abbreviation of Compact Disk Re-writable. You need a classified CD-RW disk not just a CD-R disk for recording/erasing data multiple times. Remember that, a CD-R disk can only be used to record data once. Many people forget this when when buying compact disks for the same purpose.
ii) DVD ROM (DVD-R and DVD-RW)
A DVD drive can store much more data than a CD can. An average DVD can store up to 4 GB of data however the latest dual-layered DVDs are capable to store up to 8 GB of data. The main purpose of DVD drives to store movies, games or any other stuff beyond the capacity of a CD. You need a DVD ROM to to read these disks. Like CDs DVD drives also come in two types: DVD-R, DVD-RW / DVD Burner; one for just reading the disk and other for data reading and writing both.

4. Flash Memory / Pen Drives:

A USB Flash drive is a portable or removable data storage device that allows you tomove data anywhere and  give immediate access to the data (because of plug and play support). They’re compact in size not bigger than a human finger can easily slide into your pockets and capable to store data anywhere from 256 MB to 512 GB.
It’s a better way to transport your data whenever you want and wherever you want . These devices are considered as backup devices and are also known as thumb drive / pen drive / Keychain drive and solid state drive (SSD the technology used in camera and smart phones and other devices – unlike HDD it stores data in integrated circuits & chips without movements of parts). USB flash drives are cheaper than a floppy disk as compare to data storage space they offer.

 

5. Magnetic Tapes / Tape Drives

Tape drives have been using for decades regarded as the most popularly used storage device ever. These devices store data using tape or cartridge coated with magnetic material provide low-cost data storage than any other disk drive can offer. These storage devices specifically used as a backup data storage. Magnetic tapes are very slow at data transfer due to sequential read/write mechanism.


Thanks for reading this article, If you want any addition/correction or suggestion to this article. Please feel free to share your thoughts in comments.

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Database

9:03 pm Unknown 0 Comments

Entity

  • An entity is simply a person, place, event or thing for which we want to collect data.
    • Example: student, course, teacher, enrollment, band, singer (has to be single!)
  • An Entity in an ERD is slightly different, we are referring to all of the objects as a whole collection.
    • For example if we had a student entity, we are talking about all the students together not just a single one.
  • An entity is represented by a rectangle containing its name.
  • things a clear identity of  its own.
  • something that exists separate from other things and has a clear identity of it own.
  • each entity must have at least one primary key.

entity

Attribute

  • Attributes are the characteristics of an entity, they are the actual pieces of data that will be in the database.
    • Example of student attribute: student number, first name, last name, date of birth and nationality and so on.
  • In ERD, attributes are represented by oval and are connected to an enity with a line, Each oval contains the name of the attribute it represents.
  • Each attribute should be connected to only one entity.

attributes 


multi-valued attribute: 

An attribute that holds multiple values for a single entity
Example: A person may have more than one email address.

derived attribute:

an attribute that represents a value that is calculated from the value of another attribute within the same entity.
Example: A person's age. This is calculated from date of birth and the current date.

composite attribute:

An attribute composed of multiple values each with an independent existence but together provides one information. 
Example: Address. This can be subdivided into street, suburb, state and postcode.





Relationship 

  • Entities in the ERD are related to each other. Some are joined together to show that there is some sort of relationship between the entities.
    • Example: The teacher and student entity have a relationship that can be labelled as "teacher teaches student"
  • Relationships are represented by a diamond shaped symbol with a word in the shape to describe the relationship.
  • Lines are used to connect the entities and relationships to one another.

Relationship Types: 

  • The relationship type or degree refers to the number of entities involved in the relationship.
  • There are 3 basic relationship associations:
    • Unary relationship : The entity is related to itself
    • Binary relationship: Two entities are rlated to each other
    • Ternary relationship : three entities are related to each other
    • There are higher ones but they are very uncommon. 
  • The most common one is the Binary relationship.

Connectivity 

  • This describes how many objects of one entity is related to how many objects in the other entity in the relationship.
  • There are three types of relationship connectivity:
    • One to One (1 to 1) : each object in the first entity is related to one other object in the other entity.
    • One to Many (1 to M) : one object in the first entity is related to many objects of the other entity. this can also be Many to One, depending which entity is drawn on which side.
    • Many to Many(M to N): many objects of the first entity is related to many objects in the other entity.

Participation 

  • This describes whether in a relationship if one or both of entities are required for the other to exist.
  • There will be some cases that one entity can exist even without the other enrity.
    • Example: in a relationship between teachers and classes, the class has a total participation in the relationship. Every instance of the class requires a teacher.
  • Total participation is drawn with a double line.
http://yukidatabase.blogspot.com/2012/08/entity-entity-is-simply-person-place.html

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What is Frequency Polygon - Statistics

8:54 am Unknown 0 Comments

Frequency polygons are a graphical device for understanding the shapes of distributions. They serve the same purpose as histograms, but are especially helpful for comparing sets of data. Frequency polygons are also a good choice for displaying cumulative frequency distributions.
To create a frequency polygon, start just as for histograms, by choosing aclass interval. Then draw an X-axis representing the values of the scores in your data. Mark the middle of each class interval with a tick mark, and label it with the middle value represented by the class. Draw the Y-axis to indicate the frequency of each class. Place a point in the middle of each class interval at the height corresponding to its frequency. Finally, connect the points. You should include one class interval below the lowest value in your data and one above the highest value. The graph will then touch the X-axis on both sides.
A frequency polygon for 642 psychology test scores shown in Figure 1 was constructed from the frequency table shown in Table 1.
Table 1. Frequency Distribution of Psychology Test Scores.
Lower LimitUpper LimitCountCumulative Count
29.539.500
39.549.533
49.559.51013
59.569.55366
69.579.5107173
79.589.5147320
89.599.5130450
99.5109.578528
109.5119.559587
119.5129.536623
129.5139.511634
139.5149.56640
149.5159.51641
159.5169.51642
169.5179.50642
The first label on the X-axis is 35. This represents an interval extending from 29.5 to 39.5. Since the lowest test score is 46, this interval has a frequency of 0. The point labeled 45 represents the interval from 39.5 to 49.5. There are three scores in this interval. There are 147 scores in the interval that surrounds 85.
You can easily discern the shape of the distribution from Figure 1. Most of the scores are between 65 and 115. It is clear that the distribution is not symmetric inasmuch as good scores (to the right) trail off more gradually than poor scores (to the left). In the terminology of Chapter 3 (where we will study shapes of distributions more systematically), the distribution is skewed.
frequency polygon
Figure 1. Frequency polygon for the psychology test scores.
A cumulative frequency polygon for the same test scores is shown in Figure 2. The graph is the same as before except that the Y value for each point is the number of students in the corresponding class interval plus all numbers in lower intervals. For example, there are no scores in the interval labeled "35," three in the interval "45," and 10 in the interval "55." Therefore, the Y value corresponding to "55" is 13. Since 642 students took the test, the cumulative frequency for the last interval is 642.
cumulative polygon
Figure 2. Cumulative frequency polygon for the psychology test scores.
Frequency polygons are useful for comparing distributions. This is achieved by overlaying the frequency polygons drawn for different data sets. Figure 3 provides an example. The data come from a task in which the goal is to move a computer cursor to a target on the screen as fast as possible. On 20 of the trials, the target was a small rectangle; on the other 20, the target was a large rectangle. Time to reach the target was recorded on each trial. The two distributions (one for each target) are plotted together in Figure 3. The figure shows that, although there is some overlap in times, it generally took longer to move the cursor to the small target than to the large one.
Figure 3. Overlaid frequency polygons.
It is also possible to plot two cumulative frequency distributions in the same graph. This is illustrated in Figure 4 using the same data from the cursor task. The difference in distributions for the two targets is again evident.

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Normalization in Database

8:34 am Unknown 0 Comments

In creating a database, normalization is the process of organizing it into tables in such a way that the results of using the database are always unambiguous and as intended. Normalization may have the effect of duplicating data within the database and often results in the creation of additional tables. (While normalization tends to increase the duplication of data, it does not introduce redundancy, which is unnecessary duplication.) Normalization is typically a refinement process after the initial exercise of identifying the data objects that should be in the database, identifying their relationships, and defining the tables required and the columns within each table.
A simple example of normalizing data might consist of a table showing:
CustomerItem purchasedPurchase price
ThomasShirt$40
MariaTennis shoes$35
EvelynShirt$40
PajaroTrousers$25
If this table is used for the purpose of keeping track of the price of items and you want to delete one of the customers, you will also delete a price. Normalizing the data would mean understanding this and solving the problem by dividing this table into two tables, one with information about each customer and a product they bought and the second about each product and its price. Making additions or deletions to either table would not affect the other.
Normalization degrees of relational database tables have been defined and include:
First normal form (1NF). This is the "basic" level of normalization and generally corresponds to the definition of any database, namely:
  • It contains two-dimensional tables with rows and columns.
  • Each column corresponds to a sub-object or an attribute of the object represented by the entire table.
  • Each row represents a unique instance of that sub-object or attribute and must be different in some way from any other row (that is, no duplicate rows are possible).
  • All entries in any column must be of the same kind. For example, in the column labeled "Customer," only customer names or numbers are permitted.
Second normal form (2NF). At this level of normalization, each column in a table that is not a determiner of the contents of another column must itself be a function of the other columns in the table. For example, in a table with three columns containing customer ID, product sold, and price of the product when sold, the price would be a function of the customer ID (entitled to a discount) and the specific product.
Third normal form (3NF). At the second normal form, modifications are still possible because a change to one row in a table may affect data that refers to this information from another table. For example, using the customer table just cited, removing a row describing a customer purchase (because of a return perhaps) will also remove the fact that the product has a certain price. In the third normal form, these tables would be divided into two tables so that product pricing would be tracked separately.

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