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The American University in Cairo
Department of Computer Science
CSCI 453: Advanced Database Systems
Research Paper
On-Line Analytical Processing
Submitted to:
Dr. Awad Khalil
By:
Ahmed Naguib
Ibrahim El Mallawany
Yasser EL-Hifnawi900-99-3410
909-80-1112
900-99-2202
Due date:
Sunday November 28th, 2004
Business Intelligence
How you gather, manage, and use information will determine whether you win or lose.
Bill Gates
The primary key in the decision making process is the amount of data collected and how well this data is interpreted. Nowadays, Managers arent satisfied by getting direct answers to their direct questions, Instead due to the market growth and increase of clients their questions became more complicated. Questions are like How much profit from selling our products at our different centers per month. A complicated question like this isnt as simple to be answered directly; it needs analysis to three fields in order to obtain an answer.
The Decision making processes
Identify information about the problem
Analyze the problem
Collect and evaluate the information, and define alternative solutions.
The decision making process exists in the different levels of an organization. The speed and the simplicity of gathering data and the ability to convert this data into information is the main element in the decision process. Thats why the term Business Intelligence has evolved.
Business Intelligence
As mentioned Earlier, business Intelligence is concerned with gathering the data and converting this data into information, so as to use a better decision. The better the data is gathered and how well it is interpreted as information is one of the most important elements in a successful business.
Elements of Business Intelligence
There are three main Components in Business Intelligence
Data Warehouse: it is a collection of data to support the management decisions making. It revolves around the major subjects of the business to support the management.
OLAP: is used to generate complex queries of multidimensional collection of data from the data warehouse.
Data Mining: consists of various techniques that explore and bring complex relationships in very large sets.
In the next figure the relation between the three components are represented.
SHAPE \* MERGEFORMAT
Figure (1) Shows the Connection between Elements of business Intelligence.
[ HYPERLINK "http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt" http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt]
On-Line Analytical Processing
What is OLAP?
Online Analytical Processing (OLAP) applications and tools are those that are designed to ask complex queries of large multidimensional collections of data. Due to that OLAP is accompanied with data warehousing.
The Need for OLAP:
The key driver of OLAP is the multidimensional nature of the business problem. These problems are characterized by retrieving a very large number of records that can reach gigabytes and terabytes and summarizing this data into a form information that can by used by business analysts.
One of the limitations that SQL has, it cannot represent these complex problems. A query will be translated in to several SQL statements. These SQL statements will involve multiple joints, intermediate tables, sorting, aggregations and a huge temporary memory to store these tables. These procedures required needs a lot of computation which will require a long time in computing. The second limitation of SQL is its inability to use mathematical models in these SQL statements. If an analyst, could create these complex statements using SQL statements, still there will be a large number of computation and huge memory needed. There fore the use of OLAP is preferable to solve this kind of problem.
The Multidimensional data Model
As have been stated before, Business questions arent as simple as before. The questions become more complex and multi dimensional. Lets take the question proposed before as our example. The question is as follows, how much profit from selling our products at our different centers per month. In order to look at this question we can imagine a 3 dimensional cube.
SHAPE \* MERGEFORMAT
Figure (2) The Multi Dimensional Cube.
[ HYPERLINK "http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt" http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt]
In this cube we can observe, that each side of the cube represents one of the elements of the question. The x-axis represents the tome, the y-axis represents the products and the z-axis represents different centers. The cells of in the cube represents the number of product sold or can represent the price of the items.
It can be observed that as the size of the dimension increase, the size of the cube will also increase exponentially. The time response of the cube depends on the size of the cube. Thats why pre-aggregation is valuable because the dimensions of the cube can be hierarchal. For example time can be divided into half years, quarters, months and days. Predefining such hierarchal relations allows for smooth drilling down and pre-aggregation (Reference 3).
[ HYPERLINK "http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt" http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt]
Figure (3) Describes The Drilling down and Drilling up operations..
This Figure also gives a different understanding to the drilling down operations. The relations defined must not be directly related, they related directly, what counts is defining the relations.
The size of the cube can be controlled by handling the sparse data. Not necessarily, that all the data in the cube must have a meaning. In marketing databases 95 % of the cells are empty or contain Zero. Also, in handling involves handling duplicate data of the cells. Lets assume that the cost of the product is one value for all markets the company is dealing with, therefore it is not necessary to have a cube with a multiple data item.
Dimensional Hierarchy, sparse management and pre-aggregation are the main tools that speed up the execution of multi dimensional queries and reduce the size of the database.
OLAP Guidelines:
Dr. E.F. Codd the father of the relational model, created a list of rules to deal with the OLAP systems. Users should priorities these rules according to their needs to match their business requirements (reference 3). These rules are:
Multidimensional conceptual view: The OLAP should provide an appropriate multidimensional Business model that suits the Business problems and Requirements.
Transparency: The OLAP tool should provide transparency to the input data for the users.
Accessibility: The OLAP tool should only access the data required only to the analysis needed.
Consistent reporting performance: The Size of the database should not affect in any way the performance.
Client/server architecture: The OLAP tool should use the client server architecture to ensure better performance and flexibility.
Generic dimensionality: Data entered should be equivalent to the structure and operation requirements.
Dynamic sparse matrix handling: The OLAP too should be able to manage the sparse matrix and so maintain the level of performance.
Multi-user support: The OLAP should allow several users working concurrently to work together.
Unrestricted cross-dimensional operations: The OLAP tool should be able to perform operations across the dimensions of the cube.
Intuitive data manipulation. Consolidation path re-orientation, drilling down across columns or rows, zooming out, and other manipulation inherent in the consolidation path outlines should be accomplished via direct action upon the cells of the analytical model, and should neither require the use of a menu nor multiple trips across the user interface.(Reference 4)
Flexible reporting: It is the ability of the tool to present the rows and column in a manner suitable to be analyzed.
Unlimited dimensions and aggregation levels: This depends on the kind of Business, where multiple dimensions and defining hierarchies can be made.
In addition to these guidelines an OLAP system should also support:
Comprehensive database management tools: This gives the database management to control distributed Businesses
The ability to drill down to detail source record level: Which requires that The OLAP tool should allow smooth transitions in the multidimensional database.
Incremental database refresh: The OLAP tool should provide partial refresh.
Structured Query Language (SQL interface): the OLAP system should be able to integrate effectively in the surrounding enterprise environment.
Categorization of OLAP Tools
OLAP tools are designed to manipulate and control multi-dimensional databases and help the sophisticated user to analyze the data using clear multidimensional complex views. Their typical applications include product performance and profitability, effectiveness of a sales program or a marketing campaign, sales forecasting, and capacity planning (reference 3).
MOLAP
SHAPE \* MERGEFORMAT
[ HYPERLINK "http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt" http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt]
Figure (4) Describes The Relation of the MOLAP with the server and end user.
ROLAP
SHAPE \* MERGEFORMAT
[ HYPERLINK "http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt" http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt]
Figure (5) describes The Relation of the ROLAP with the server and end user.
OLAP Tools and the internet:
The mainly comprehensive premises in computing have been the internet and data warehousing thus the integration of these two giant technologies is a necessity. The advantages of using the Web for access are inevitable.(Reference 3) These advantages are:
The internet provides connectivity between countries acting as a free resource.
The web eases administrative tasks of managing scattered locations.
The Web allows users to store and manage data and applications on servers that can be managed, maintained and updated centrally.
These reasons indicate the importance of the Web in data storage and manipulation. The Web-enabled data access has many significant features, such as:
The first
The second
The emerging third
HTML publishing
Helper applications
Plug-ins
Server-centric components
Java and active-x applications
Products for OLAP
HYPERLINK "http://en.wikipedia.org/wiki/Microsoft" \o "Microsoft" Microsoft Analysis Services (previously called OLAP Services, part of HYPERLINK "http://en.wikipedia.org/wiki/Microsoft_SQL_Server" \o "Microsoft SQL Server" SQL Server), HYPERLINK "http://en.wikipedia.org/wiki/International_Business_Machines" \o "International Business Machines" IBM's HYPERLINK "http://en.wikipedia.org/wiki/DB2" \o "DB2" DB2 OLAP Server, HYPERLINK "http://en.wikipedia.org/wiki/SAP_%28company%29" \o "SAP (company)" SAP BW and products from HYPERLINK "http://en.wikipedia.org/wiki/Brio" \o "Brio" Brio, BusinessObjects, Cognos, MicroStrategy and others.
Companies using OLAP
MIS AG Overview
MIS AG is the leading European provider of business intelligence solutions and services, providing development, implementation, and service of systems for budgeting, reporting, consolidation, and analysis. MIS AG products include industry and platform independent software for efficient corporate controlling.
Poet Overview
W i t h F a s t O b j e c t s "!, G e r m a n P o e t S o f t w a r e G m b H ( P o e t ) p r o v i d e s d e v e l o p e r s w i t h a f l e x i b l e O b j e c t - o r i e n t e d D a t a b a s e M a n a g e m e n t S y s t e m ( O D B M S ) s o l u t i o n o p t i m i z e d f o r m a n a g i n g c o m p l e x i t y i n h i g h - p e r f o r m a n c e a p p l i c a t i o n s u s i n g J a v a t e c h n o l o g y , C + + a n d . N E T .
C o nclusion
The growth of the organizations every day, and the insistence of these organizations on clear, flexible and good information, the use of OLAP is necessary. Competition between these organizations became mainly in the process of collection of data, its interpretation and taking right decisions based on this information. The OLAP provided managers to plan for the organizations and set strategic goals to be achieved. Also, OLAP can help in tactical goals, because OLAP can also be used in all the levels of the organization, not only the management. Nowadays the measurement of the companys ability is measured by the quality, efficiency and effectiveness of OLAP capability. (Reference 1, 3)
References
1. HYPERLINK "http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt" http://www.computing.surrey.ac.uk/courses/cs263/Lec14DataMining.ppt
2. HYPERLINK "http://www.dwreview.com/OLAP/OLAP_Comparison.html" \t "_blank" http://www.dwreview.com/OLAP/OLAP_Comparison.html
3. HYPERLINK "http://lib.aucegypt.edu/search/aBerson%2C+Alex./aberson+alex/-2,-1,0,B/browse" Berson, Alex, Data warehousing, data mining, and OLAP / Alex Berson, Stephen J. Smith., New York : McGraw-Hill, 1997.
4.http://www.essbase.com/resource_library/white_papers/providing_olap_to_user_analysts_3.cfm
HYPERLINK "http://www.simba.com/Customers/casestudy_poet.htm" http://www.simba.com/Customers/casestudy_poet.htm
HYPERLINK "http://www.simba.com/Customers/casestudy_mis.htm" http://www.simba.com/Customers/casestudy_mis.htm
HYPERLINK "http://en.wikipedia.org/wiki/OLAP" http://en.wikipedia.org/wiki/OLAP
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