Search paper about Offers bank

1. Offers bank DSS
Ghada Saad Al-Ajlan Manal Hamad Al- Saloum
College of Computer & Information Sciences College of Computer & Information Sciences
Al-Imam Muhammad Ibn Saud Islamic University Al-Imam Muhammad Ibn Saud Islamic University
Al-ajlan.ghada@gmail.com jo0ory1111@hotmail.com
Abstract— Offers bank DSS is aims to follow up on customer
behavior to find out their attitudes and offers the most
convenient for them, to improve the performances and renew
always be consistent with the requirements of customers, keeps
them from leaking to other banks and to attract new customers.
Exploitation is optimized for customer data in the bank, can be
classified information accurately able to work queries multiple
order to know the trends of the customers about offers, then
analyze these trends and try to find relationships between these
trends to see offers occasion to intensify, and inappropriate for
its defiance. This can be done by using Microsoft Access which
helps to store a large number of a proper data with the
possibility of linking them and be able to work query appropriate
smoothly. Using the new shape Microsoft Excel 2013 where
contains new features that enable user to access the databases
and extract information for do appropriate analysis that helps to
make the better decisions. One of the most important features
are VBA enabling user to program Excel so that you can
automate a boring report, format a big&ugly chart, clean-up
some messy data .
Keywords— Offers bank DSS , Business Intelligence (BI),
Microsoft Excel 2013, Data warehouse (DW), SAP company
I. INTRODUCTION
Business Intelligence (BI) is the top priority of any
enterprise. It is a much more integrated, highly strategic,
management tool that supports every day decisions on how to
operate the business to better achieve corporate objectives[1].
Know , there are wide range of it as products that offering
solutions depending on what you spend the need . May
company as Oracle, IBN,SAP and Microsoft despite its many
successful applications in different business domains, such as,
E-government, E-business, E-commerce, E-market, E-finance,
and E-learning systems with the corresponding technologies
of web research, web mining, and web-based support systems.
Business intelligence solutions makes enterprise easier to
identify trends and issues, uncover new insights, and fine-tune
operations to meet business goals. BI solutions can be very
comprehensive, or they can focus on specific functions, such
as corporate performance management, spend. analysis, sales
pipeline analysis and sales compensation analysis.
With the tremendous progress in all fields, there are many
challenges and problems ,"Getting better insights out of the
data they already have" as their top technology challenge". BI
solutions can solve this problem by providing a framework
and tools to measure and manage business goals and conduct
―what-if‖ scenarios to evaluate different courses of action. In
very small companies, spreadsheets and other ad hoc tools are
often enough to get the job done. But as companies grow, the
amount of data decision makers need to understand grows:
new products and services, new markets and opportunities,
investments in operations, sales, marketing and other systems
to support growth. As a result, more people have to be part of
the data collection and analysis process, and different people
in the organization (sales, marketing, finance, etc.) need to
look at data in different ways.
There are some important applications that contribute to
the achievement of BI solutions like Microsoft Excel .
Microsoft Excel 2013 today with new features such as Flash
Fill can easily reformat and rearrange your data to gain new
insight and learns and recognizes pattern and auto-completes
the remaining data for user . No formulas or macros required.
It perform complex analyses quickly and summarizes your
data with previews of various pivot-table options, so user can
compare them and select the option that tells your event
better to discover the insights hidden in data. Visualize data
to understand it better else was one of news which can
achieved through recommended Charts that apply best charts
illustrate for data's patterns ,quickly preview chart and graph
options, and then pick the ones that present insights most
clearly. To implement any things quickly ,Excel provides
Quick analysis which can discover and compare different
ways to represent your data visually else with use Chart
Formatting Control allow imagine the freedom to fine-tune the
look and feel of your charts quickly. Microsoft Excel as the
tool of choice to analyse large sets of complex data stored in
databases or in various spreadsheets will be very pleased with
the new data modelling and visualization capabilities in
Microsoft Excel 2013. A number of advanced reporting tools
that were previously available as add-ins for Excel are now
built in to Excel 2013. Now you can create great looking
reports and dashboards by inserting a ―Power View‖ into your
spreadsheet. The Power View takes advantage or Microsoft’s
Silver light technology and online services such as the Bing
mapping service to create more advanced reports. With the
more advanced data modelling capabilities of Microsoft Excel
2013 you can add multiple data sets and define relationships
between data. For every release of Office, Microsoft has
added business intelligence (the ability to turn raw data stored
in the organization into meaningful business insights)
capabilities into Excel[2]. Still, many organizations have

2. required third party tools to fulfil their business intelligence
needs.
Offers bank DSS explain in this paper how can make
offers system as BI solutions in four phases . first phase is
create Database and Star schema by use Microsoft access
2013 . Second phase is fill data after determine Dimensions
and Measures and retrieval it in Microsoft Excel 2013 .Third
phase is create a dashboard in Microsoft Excel 2013 .Finial
phase is analyse and understand past trends and predict by
using Data Mining.
II. literature survey
Demand for Business Intelligence (BI) applications
continues to grow even at a time when demand for most
information technology (IT) products is soft[3].Business
intelligence (BI) is a data-driven DSS that combines data
gathering, data storage, and knowledge management with
analysis to provide input to the decision process. The term
originated in 1989; prior to that many of its characteristics
were part of executive information systems. Business
intelligence emphasizes analysis of large volumes of data
about the firm and its operations. It includes competitive
intelligence (monitoring competitors) as a subset. In
computer-based environments, business intelligence uses a
large database, typically stored in a data warehouse or data
mart, as its source of information and as the basis for
sophisticated analysis. Analyses ranges from simple reporting
to slice-and-dice, drill down, answering ad hoc queries, real-
time analysis, and forecasting. A large number of vendors
provide analysis tools. Perhaps the most useful of these is the
dashboard. Recent developments in BI include business
performance measurement (BPM), business activity
monitoring (BAM), and the expansion of BI from being a staff
tool to being used by people throughout the organization (BI
for the masses). In the long-term, BI techniques and findings
will be imbedded into business processes[4].
Essential components of proactive BI are : real-time data
warehousing , data mining ,automated anomaly and exception
detection , proactive alerting with automatic recipient
determination, ,seamless follow-through workflow, automatic
learning and refinement, ,geographic information systems
(Sidebar 1) ,data visualization (Sidebar 2)[5].
Embracing of BI was synchronization with the birth of new
corporate strategies [6], such as:
 Early user-friendly languages emerged to offer a
bridge between end users and the hostile IT
environment establishing the concept of end-user
computing.
 Centralized centers of competency were created to
provide a means for end users to become productive
quickly. The need to set corporate standards for
analysis tools was one of the most significant
benefits from these centers.
 With the era of client/server systems came the
understanding that keeping data in situ may not be
conducive to analysis; thus, reengineering of data
into BI friendly forms and formats was ideal. The
most commonly accepted form of database was a
relational store that supported SQL. The need to
establish and adhere to standards for all vendors’
SQL became a mantra.
 The Information Warehouse proved that accessing
data in place is not always desirable, but capturing
the metadata about existing information makes
perfect sense. Before user transform current
information, user need to know all about its current
contents and form.
 Data Warehousing projects brought all the pertinent
steps together for taking existing information sources
and creating new, analysis-based data. It also proved
that the tasks related to data transformation could be
incredibly long and costly. The argument as to
whether a warehouse or a mart is more appropriate
continues. The most significant aspect of
warehousing or ―marting‖ is the realization that the
back ends will probably remain and processes to
transform and create new data stores must be
automated.
Solution of business intelligence become available for
decision-makers. To extract information from huge, ever-
growing databases and then turn it into actionable business
intelligence at the time it’s needed, however, puts enormous
strain on traditional data management systems. There are
many offers view of it solutions from different company ,for
example Panorama Software company produced Panorama
Necto which enabled Business Intelligence solution that offers
a new way to connect data, insights, and people in the
organization[7]. It represents a new generation of BI solutions
that enable enterprises to leverage the power of Social
Intelligence to gain insights more quickly, more efficiently,
and with greater relevancy. Sybase company download
Sybase Business Intelligence Software Solutions To help its
customers overcome these problems, Sybase provides
radically innovate enterprise analytics and data warehousing
software tools that give customers with the power and speed
they need to make actionable business intelligence a reality —
even in real time[8] . SAP company launched SAP Crystal
Reports enables user to easily design interactive reports and
connect them to virtually any data source, that allow users can
benefit from on-report sorting and filtering – giving them the
power to execute decisions instantly[9].
In IBM company business intelligence solutions as Cognos
Enterprise provides the following[10]:

3.  Reports equip users with the information they need to
make fact-based decisions.
 Dashboards help users access, interact and
personalize content in a way that supports how they
make decisions.
 Analysis capabilities provide access to information
from multiple angles and perspectives so you can
view and analyze it to make informed decisions.
 Collaboration capabilities include communication
tools and social networking to fuel the exchange of
ideas during the decision-making process.
 Scorecarding capabilities automate the capture,
management and monitoring of business metrics so
you can compare them with your strategic and
operational objectives.
These excellent features and multiple options to select paid
a lot of sectors to insert BI which the most important of these
sectors, the education . BI Listed in the academic field and
become very important course but with absence of a lot of
possibilities teaching it became a very difficult for multiple
aspects, which from Professors specialists aspect , they cannot
teach content and explain the complex and internal processes
in BI. From student aspect ,difficult for them to imagine
operations and does not have a suitable training environment
that contain software to enhance the concept of BI. This leads
to a gap between students and professionals, so the result not
knowing the certainty of the benefits of BI and not recognize
it as a better solution. Might come out students for the labor
market does not have an adequate exercise and therefore
cannot work in this area.
III . offers bank DSS project
In this section of the paper is to clarify the project in details
as the following:
A . Project description
Offers bank DSS are system using business intelligence
(BI) to predicting customers bank behavior and know what
customers want before they do it ,also it develop to record and
monitor the transaction by ( phone, bank branch , online and
ATM) and combine this data with personal customers data to
extract the important information for support the system . The
Offers bank DSS analysis the data and model the customers
behavior to automatically come up with prospective offers just
in right time with connection ways ( mobile, email ,…..) , to
improved the system of bank and maintain of customers.
B. Worth of project
The project well help to improve the performance of offers
system bank by develop the method and process needed to for
reflect a good financial to the bank.
C. Dimensions and measures
At this section we explain the details about offers bank DSS,
the steps which we have worked in it to release good and
useful result to evaluate the system performance.
1) Data warehouse (DW)
The DW Designed to extract , manipulate , representation
and submitted data to analysis and knowledge discovery and
make a suitable decisions of the Bank, this data extract from
deferent data source like databases (see figure 1).
Figure 1: data cube
The data warehouse represent like multidimensional model
in data cube and contain two tables dimension table and fact
table . We use Microsoft access 2013 (my SQL) to represent
DW.
2) Dimensions table of offers bank DSS
There are 4 dimension tables use in DW as the following:
1. Customers table
The table record 200 information customers bank ,
Which contain ( customer_key, customer
_account,first_name, last_name , address, phone,
city, zib_code, own house , own car, family_id
,number _children , material_statue) . Each
customers belong to family that also have account in
bank they gives the same family id .
Also there related table to customer table is named is
Account which contain about information of account
for each customer.
2. Time table
Time was at period 6 month from 1/1/2011 to
30/6/2011 and divided for each day to 2 period at
AM and PM . Which contain ( time_key , day ,month
,year ,time _from ,time_ to)
3. Transaction type table

4. There 17 type of transaction and way to do
operations . Which contain (trans_key , transaction
_method, transaction _type)
4. Offer table
There are 21 offers , offer type and classification and
the description of it .
which contain ( offer_key , offer classification ,
offer_type , offer _description).
3) Fact table of offers bank DSS
The fact table contain all key of dimension tables and the
measure are amount of money that customers use it for each
operation. Fact table record the offers that send to customer
depended in their transaction they do it for 6 month . At figure
( 2 ) we draw the snowflake schema of the system and there
relation between theme.
Figure 2: snowflake schema
IV. Implantation and Result
At this stage we analysis the data in DW and extraction the
knowledge and decisions related to that we use OLAP
operations and queries to represent important information
about system .
A) The queries and charts
There numbers of queries answer and extract important
information from DW to improve the offers DSS. We use
pivot OLAP operation by Excel 2013 to extract information
and represent it in charts. At below the queries and chart
for each one and the result.
 the number of customers that take offers and
compare between month about which offer are
more active. At figure 3 show the result of
number of customers whom send to them the
offers at 5 may and 6 JUN months.
The manger also can choose any month he want
to represent at any offers.
Figure 3: number of customers for each offers at
select month
 the most customer who deposit in bank for select
month to treat him for best services and best offers,
the bank very interest for this type of customers to
keep them customers for their bank . At figure 4
show the result .
Figure 4:amount of deposit for select customer and
select month
 the number of affluent customers ( their amount of
account more or equal to 100,000 RS ) that do not have
credit card , so we try sent to them more of credit card
offers , the bank very interest about affluent customers
because bank will benefit from large amount deposit in
to credit card . At figure 5 show the result .
Figure 5: total number of affluent customers use or not
use credit card
 numbers of family that take offers more than single
customers who do not belong to family id , we

5. result from that the customer keen to register their
family at same bank to obtain of family offers . At
figure 6 show the result
Figure 6: numbers of family and single that take offers
B) Descriptive rule by data mining
to descriptive the rules we need to extract pattern from DW
transactions, first determined the 2 offers that frequently
occur ,then determined the support and confidence for each
relation after that see it can be rule or not , at below figure 7
explain the work .
figure 7:assoccetion rule
C) The rules
 relation between offer personal loan and house
loan. Customers like offer of house loan with low
and fixed finance rate so she or he interest to get
personal loan . it can help bank to improve their
offers about this loans to increasing customers .
 also their relation between the holiday 5 may and 6
JUN month with offers of personal loan at figure 8
explains the rate .
numbers of offers loans send to customers whom
get personal loans at these month it can help bank
to create more offers at holiday months .
Figure 8: number of loan
V . Conclusion
This paper concerned with BI , which seeks to exploit the
huge data in order to provide appropriate solutions for
organizations. By integrated with other applications is
Microsoft Access and Microsoft Excel 2013 work became
more easily, quickly and appeared high quality results. Many
companies introduced BI products to solve various problems.
Nevertheless remained teaching BI faces several difficulties,
including lack of resources, the transfer of expertise for
teachers, lack of good content and practices and not to be
subjected to the appropriate training.
Through the project, we saw how the results emerged and new
directions, so that after the study of the behaviour of
customers in the bank show that there is a relationship
between home loans and the growing popularity of personal
loans. As well as other relationship emerged between the
holidays season and the increase in personal loans . A lot of
relationship appeared as well as there are other hidden,
possible new show after several transaction carried out by the
customer. This helps to improve the Bank offers and choose
the most appropriate time to put it coincided with the
customer's requirements.
Future research work will be focused on providing
recommendations for the use of BI in other areas, especially in
the field of education in order to change the bad image and try
to void the difficulties faced by the teaching BI in academic
sector .

6. REFERENCES
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[7] (2013) The panorama website. [Online]. Available: http://
http://www.panorama.com/
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