1. What is Linux?
Linux is, in simplest terms, an operating system. It is the software on a computer that enables applications and the computer operator to access the devices on the computer to perform desired functions. The operating system (OS) relays instructions from an application to, for instance, the computer’s processor. The processor performs the instructed task, then sends the results back to the application via the operating system.
But something sets Linux apart from these operating systems. The Linux operating system represented a $25 billion ecosystem in 2008. Since its inception in 1991, Linux has grown to become a force in computing, powering everything from the New York Stock Exchange to mobile phones to supercomputers to consumer devices.
As an open operating system, Linux is developed collaboratively, meaning no one company is solely responsible for its development or ongoing support. Companies participating in the Linux economy share research and development costs with their partners and competitors. This spreading of development burden amongst individuals and companies has resulted in a large and efficient ecosystem and unheralded software innovation.
Over 1,000 developers, from at least 100 different companies, contribute to every kernel release. In the past two years alone, over 3,200 developers from 200 companies have contributed to the kernel–which is just one small piece of a Linux distribution.
This article will explore the various components of the Linux operating system, how they are created and work together, the communities of Linux, and Linux’s incredible impact on the IT ecosystem.
- Where is Linux?
One of the most noted properties of Linux is where it can be used. Windows and OS X are predominantly found on personal computing devices such as desktop and laptop computers. Other operating systems, such as Symbian, are found on small devices such as phones and PDAs, while mainframes and supercomputers found in major academic and corporate labs use specialized operating systems such as AS/400 and the Cray OS.
Linux, which began its existence as a server OS and Has become useful as a desktop OS, can also be used on all of these devices. ‚ÄúFrom wristwatches to supercomputers,‚Äù is the popular description of Linux’ capabilities.
An abbreviated list of some of the popular electronic devices Linux is used on today includes:
These are just the most recent examples of Linux-based devices available to consumers worldwide. This actual number of items that use Linux numbers in the thousands. The Linux Foundation is building a centralized database that will list all currently offered Linux-based products, as well as archive those devices that pioneered Linux-based electronics.
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- COMPOUND INTEREST
M = P( 1 + i )n
M is the final amount including the principal.
P is the principal amount.
i is the rate of interest per year.
n is the number of years invested.
Applying the Formula
Let’s say that I have $1000.00 to invest for 3 years at rate of 5% compound interest.
M = 1000 (1 + 0.05)3 = $1157.62.
You can see that my $1000.00 is worth $1157.62.
Area and Perimeter of a Triangle, Rectangle, Parallelogram, Trapezoid and Circle
Surface Area and Perimeter of a Triangle
FUNCTIONAL DEPENDENCY OF THE DATA
Functional dependency of data means that the attribute within a given entity are fully dependent on the entire primary key of the entity-no more, no less.
The implication is that each attribute has a one-to-one relationship with its primary key. For each instance of a primary key, there is one set of applicable values; for each attribute, there is only one primary key that properly gives it its identity.
For example, in the customer entity, names, DOB all belong to the primary key of CustomerID.
If the columns with each table contain attributes with proper functional dependency, then the simplest way to make a change to any column is to rely on the functional dependency.
Each change will be applied to one attribute in one place.
If customer changes name, then the customer row and change the name.
If the new customer address is used as the mailing address, go to address role and change it there-one place. Functional dependency is not irrelevant in analytical models.
When you define a level, you define a relationship between the level key attributes and the other attributes in the level (default attribute and related attributes). The relationship indicates that the level key attributes can be used together to determine the other attributes in the level. DB2 Data Warehouse Edition documents the relationship between the level’s attributes by defining functional dependencies between the attributes. The relationships, defined by functional dependencies, can be used to perform intelligent optimization of your data.
If a functional dependency exists between a level key attribute and the level’s related attributes, the Optimization Advisor wizard can include the level key attribute without the related attributes in the summary table. Queries that are interested in the level’s related attributes can still be routed to the summary table because the DB2 optimizer joins the summary table with the dimension table when the query is issued to create the final result set.
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DATA WAREHOUSE OPTIONS
There are many ways to develop data warehouse as there are organization and number of key factors that need to be considered:
- SCOPE OF THE DATA WAREHOUSE
- DATA REDUNDANCY
- TYPE OF END – USER
i. SCOPE OF THE DATA WAREHOUSE
The scope of a data warehouse may be as broad as all the informational data for the entire enterprise from the beginning of time, or it may be as narrow as a personal data warehouse for a single manager for a single year. There is nothing that makes one of these more of a data warehouse than another.
ii. DATA REDUNDANCY
There are essentially three levels of data redundancy that enterprises should think about when considering their data warehouse options:
a) “virtual” or “point – to point” data warehouses
b) Central data warehouses
c) Distributed data warehouses
A) “VIRTUAL” OR “POINT TO POINT” DATA WAREHOUSES
A virtual or point to point data warehousing strategy means that end users are allowed to get at operational databases directly, using whatever tools are enabled to the “ data access network” this approach provides the ultimate in flexibility as well as the minimum amount of redundant data must be loaded and maintained.
B) CENTRAL DATA WAREHOUSES
A central data warehouses may contain records for any specific period of time and usually, contains information from multiple operational systems.
Central data warehouse are real. The data stored here is accessible from one place and must be loaded and maintained on a regular basis. Normally, data warehouses are built around advanced RDBMs or some form of multidimensional informational database server.
C) DISTRIBUTED DATA WAREHOUSES
Distributed Data warehouses are those in which certain components are distributed across a number of different physical databases.
iii. TYPE OF END – USER
There are different ways to organize a data warehouse, it is also important to note that there is an increasingly wide range of end – users too. They can broadly be categorized into three;
Executives and managers
Power users (business and financial analysts, engineers)
Support users (clerical, administrative)
Each of these has its own set of requirements for data, access, flexibility and ease of use.
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What is the difference between OLAP and OLTP?
Data Warehouse (OLAP)
|Involves historical processing of information.||Involves day to day processing.|
|OLAP systems are used by knowledge workers such as executive, manager and analyst.||OLTP systems are used by clerk, DBA, or database professionals.|
|Used to analysis the business.||Used to run the business.|
|Focuses on Information out.||focuses on Data in.|
|Based on Star Schema, Snowflake Schema and Fact Constellation Schema.||Based on Entity Relationship Model.|
|Focuses on Information out.||Application oriented.|
|Contains historical data.||Contains current data.|
|Provides summarized and consolidated data.||Provides primitive and highly detailed data.|
|Provides summarized and multidimensional view of data.||Provides detailed and flat relational view of data.|
|The number or users are in Hundreds.||The number of users is in thousands.|
|Number of records accessed is in millions.||Number of records accessed is in tens.|
|database size is from 100GB to TB||Database size is from 100 MB to GB.|
|Highly flexible.||Provides high performance.|