Pooja Nahar, Dr. Sanjay KumarIJSRE Volume 05 Issue 06 June 2017 Page 6674 Volume||5||Issue||06||June-2017||Pages-6674-6681||ISSN(e):2321-7545 Website: http://ijsae.in Index Copernicus Value- 56.65 DOI: http://dx.doi.org/10.18535/ijsre/v5i06.22
Simulating a Web based DSS for Power Supply Organization using Data Warehousing
Authors
Pooja Nahar1 , Dr. Sanjay Kumar2 1
Ph.D. Scholar (Computer Science) Jaipur National University Jaipur, Rajasthan 2
Associate Professor Jaipur National University Jaipur, Rajasthan Email: [email protected], [email protected] ABSTRACT-:
Organizations also depend on computerized decision support systems for making routine and strategic decisions. Implementing Decision Support System is a complicated process and public sectors also have very complex system, because they are not profit driven organization. Some political goals are influenced by decision making processes which are conditioned by available information and knowledge. The more information and knowledge are available about the problem, less the risk involved in it. Data warehouses contain information ranging from measurements of performance to competitive intelligence. This paper provides a model of web based DSS for Power Supply organization, to manage large amount of data and fast and efficient extraction of information from the database using Data Warehouse. It also includes implementation process, benefits and problems with Data Warehousing.
Keywords-: Decision Support System, Data Mining, Data Warehouse, ETL (Extraction, Transformation and Loading)
INTRODUCTION-:
The importance of computer based information systems is recognized and innumerable systems have been computerized to improve efficiency in accounting and operational activities. That is applicable for private sectors as well as public sectors. Now-a-days public sectors also have to face tough market competition, where the customer finds the higher satisfaction with better services. Including, these services, an organization also depends on computerized decision support systems for making routine and strategic decisions. That is why; DSS has flourished in many public and private organizations. With the advent of the personal computer, computer-based assistance for all functions of the business becomes widespread in a number of corporations. For implementation there is no difference between private and public sectors, but in making use of DSS, public sector is irregular, because of many reasons. Decision making can be a complicated process. Although there is a room for effective DSS exploitation in the public sector, but their usage is very low. The public sector is a very complex system, which can be described by the services that organization deliver to citizens. Public sectors are not profit driven. Profit maximization is not their primary goal, but it does not mean that these are not concerned with financial matters [1]. They also have to fight for funding, power and cost saving. Public sectors have to operate in a political environment. Public sectors organizations have to meet objectives with service delivery like productivity, efficiency and quality of service.
Pooja Nahar, Dr. Sanjay KumarIJSRE Volume 05 Issue 06 June 2017 Page 6675 conditioned by available information and knowledge. Knowledge is essential to support decision making activities and to deliver better services. The information-gathering is the basic need of decision making. Every decision involves a certain amount of risk. Some internal and external factors influence the decision making process. All the decisions influenced by information and knowledge available. The more information and knowledge are available about the problem, less the risk involved in it. Storing of data in a centralized system has a basic goal to provide decision makers sound information and knowledge with the right building blocks. Data warehouses contain information ranging from measurements of performance to competitive intelligence. Properly designed and implemented Data warehouse, drastically reduce the time required in decision making, by using its tools. Online Analytical Processing (OLAP), Data Visualization and Data Mining are the tools, are used to achieve that.
FRAMEWORK OF THE APPLICATION-:
Three main issues, which provide guidelines in developing relevant DSS and in identifying new ways of making efficient process of decision making through computer. These are- 1) Conceptual DSS focus, in which the nature of individual and organizational decision making process will be addressed. 2) Methodological DSS focus, in which integration of existing computer based tools and techniques with human decision making will be focused. 3) Application oriented DSS focus, in which the real organizational needs will be focused [2].
This is a web based application described in the previous paper for the case company. It basically addressed three areas- 1) It supports and encourages human decision making processes, 2) Integrated DSS into the organizational context and 3) Identifying new application domains. This framework would support decision makers and civil servants to identify the benefits of the DSS applications and to evaluate ICT based services on the aspect of cost savings, knowledge, improved decision making processes and data and information integration. World Wide Web technologies have rapidly transformed the process of design, developing and implementing all types of DSS. Web technologies provide new means of delivering decision support services. Web base DSS is a computerized system that delivers decision support information to the managers using web browser like Netscape Navigator or Internet Explorer. This works like Client-Server application, where server will be hosting the DSS application and user’s computer behaves like client. It works by using TCP/IP protocol. This application could be accessible by anyone through Internet connection. It works in a networked environment where team based working or group working would be possible. This facility allow people to avoid geographical problems, like manager could check the reports or manage the regular working by sitting at home too and this will enable the remote and platform independent access of DSS. While there is a significant promise in having web base decision support system, but there are some important challenges like-technological, behavioral, social and economic. To reach the goals of the organization, they should face the challenges and resolve them at time. As the case company is a public organization and serves to the civil for the requisition of their basic need of electricity. Each and every person should fulfill his/her basic requirement of the electricity on time and without any problem. This DSS would have a big amount of data because of its large customers list. To manage and analyzed large data, this DSS would be integrated with Data warehouse techniques. DW techniques help the organization to make advanced DSS. By using OLAP tool this DSS could be supported by multidimensional database and analyzed by different aspects. Data Visualization is another tool, which will help to visualize data in graphical manner, so that it would be easy to understand by the novice users.
DATA WAREHOUSING-:
Pooja Nahar, Dr. Sanjay KumarIJSRE Volume 05 Issue 06 June 2017 Page 6676 demands, speed of delivery, technology inputs, government regulation, etc. are the factors those affect any application of the DSS [3]. The outcome of public services depends not only on inputs and outputs, but also on institutional, behavioral and regulatory issues. Public sectors should introduce innovations, i.e. technological innovations and innovations are mainly driven by the need to improve governance and service performance including efficiency and effectiveness of service delivery.
Therefore, we proposed a web based model for the case company, to use this as DSS in their internal working and as well as for their external working i.e. to communicate with their customers for their product which is providing an electricity connection. This adoption could provide effective results. In the conventional model, we could find that user could be interacting with Data Base Management System (DBMS) and the defined and recommended functions through user interface. Through DBMS user could store and extract data or information according to the requirement. These could be done through queries. As the case company has the large amount of data related to customers and as it is increasing day by day. So it will be difficult to cumbersome and time consuming for human to make analyses. As well as it will take more time to execute queries on all the records and data extraction could be a complex process. Company could be overcrowded with complicated data and they could get useful information by using DW, this data could be appropriate for various analyses. So by storing data in a centralized manner, could provide sound information and knowledge. Data Warehouse is the driver of data driven DSS. DW systems allow the manipulation of data provide additional functionality. DW collects and combines information in a sharing environment and provides integrated view. Conventional query driven approach has many problems like delay in query processing, complex filtering and integration, inefficient and potentially expensive for frequent queries etc. That’s why this approach has not been caught in big industries. Whereas we manage all the data in the warehouse, so that integrated information could get and direct query and analysis would be possible. DW uses metadata to extract information from different sources. It provides high query processing including fast complex queries result [4]. For implementing DW, for our case company, we fetch all important data from OLTP system. It includes sub-sets of data which have all interesting data related to analysis. Data analysis does not need all the data but only important data for a specific time period.
Figure-1 General Architecture of Data Warehousing
Different Sources Data Warehouse
Clients/Customers
Pooja Nahar, Dr. Sanjay KumarIJSRE Volume 05 Issue 06 June 2017 Page 6677 Data-driven decision support systems, like DWs can extract information from more than one database/source. DWs provide a single view of information for whole the organization. DWs provide the required information to the decision makers, so that they could make effective decisions [5].
Case company is a public sector organization and it is service oriented. Its main objective is to provide better service to the citizens, so that even every poor citizen could fulfill his/her basic requirement of electricity. Citizens do not pay their dues in time; hence the company is facing monetary shortfalls. Case company is not in a good monetary shape. Since implementing Data Warehousing is very expensive step; in this situation of lack of funds, managing finance for Data Warehousing by case company is very difficult. Already public organizations are facing tough competition in market. In order to overcome all above mentioned issues, organization needs to take efficient and effective decisions for their well being.
DW obtains the data from a number of different data base systems which can be based on RDBMS. Then the data are converted into a suitable form for data warehouse. This process is called Extraction, Transformation and Loading (ETL). In addition to the main database, there would be another database which store data about data, i.e. Metadata. Then the Web based software system will be used to generate reports. A survey, questionnaire etc. is made by visiting the staff and customers of the case company, some findings are summarized here-
1. Users could not find proper reports, which they want to retrieve.
2. The user interface of current system is not very friendly; users find difficulty in accessing information.
3. Data related to different areas are scattered / distributed, they are not maintained centrally.
4. Information related to different areas could not be retrieved. In other words consolidated reports with different areas could not be seen.
5. No proper training was provided to the employees. Employees are not computer literate, so they need training.
6. No reports related to employees and customers were there.
Proposed Web based data driven DSS, could provide a better way to managing data, operate and analyzing data. The main purpose of this model is to provide a better system for timely, accurate, consistent information delivery to the decision makers of the case company. This paper has been prepared in order to extend the usage of current system in decision making. This web based data driven DSS would provide many benefits to the decision makers-
1. Reduction of cost and time of query processing.
2. Effective and efficient decision making for the organization. 3. Improving reporting and approvals of the employees.
4. Consolidated reports could be generated to achieve more comprehensive information. 5. Integration of different data sources could be possible.
Pooja Nahar, Dr. Sanjay KumarIJSRE Volume 05 Issue 06 June 2017 Page 6678
Figure – 2 JVVNL_Data Warehousing Architecture
IMPLEMENTATION OF THE APPLICATION-:
Implementation step is the most important step for any software application, because at that time the developer or researcher could find the problems and the level of acceptance of his application. A successful implementation requires support from top level management and evaluation and assessment should be done at the time of implementation [3]. The impact of the application could be justified. Implementation needs proper infrastructure for the application and all the top, middle and low level management should be ready to find the benefits from this DSS. As we discussed the framework of the application in section 2, this web based DSS for the case company, was developed from the point of view of ease of use, usage, adaptability and cost to operate.
User interface is a vehicle for both the end user and the manager for finding results. GUI provides an understanding of the system to the end user. Even if the model is very good and its results are correct, this would not be followed if it is not understood. Without understanding a system could be accepted or rejected because of not reason. User involvement throughout the development and implementation phases, improves user’s satisfaction level. DSS implementation phase is closely connected with DSS development phase, which is a critical phase of user acceptance. Project can lead to the rejection by users due to lack of support, training and overall involvement throughout the development process. However, the quality and the reliability of the system are important, but the most crucial part of DSS is GUI. Systems with user interfaces that are cumbersome or require special ability are rarely acceptable generally [6].
Implementation is a never ending phase. It is collaboration between users and their developers. The success of the implementation is not measured by the merits of the DSS but rather by the users of the DSS. System flexibility, user willingness to change and user participation are the basic three factors, on which success of DSS implementation is based. Before finally submitting to the users, all functional groups had to agree upon design, accountabilities, resource allocation, training, etc [7]. Implementation is an important stage in the life cycle of the Information System’s development. This phase begins when all the informatics applications
Transactional Databases
Utility Database
Inventory Database
Employee Database
Data Staging Area
Data Warehouse
ETL ETL ETL
Data Marts
Employee Data Mart
Customer Data Mart
Store Data Mart
Pooja Nahar, Dr. Sanjay KumarIJSRE Volume 05 Issue 06 June 2017 Page 6679 of the system had been tested and results allow assembling them. Then implementation finalizes the design activity and helps in achieving the effectiveness in reality [8]. The case company - “Electricity Distribution Company” is more or less similar like a retailer of electricity product. In regarding the large volume of data, data should be mined for business insight. Use of data to manage, operate and evaluate in a better way, can be done by utilizing DSS. DWs are effective system for the decision makers [5]. Fig -2, shows the DW architecture of JVVNL, which is the case company. DW obtains data from these 3 transactional databases used as source, which are Utility database, Employee database and Inventory database. Utility database includes the tables related to new connection, dis-connection, re-connection, name change, weight change etc. It includes all applications which customers can use to apply for different facilities. So all the data related to customers, connections, due connections, payments, due payments etc. could be extract from this database. Employee database includes all the data related to employees, their work status etc. Different reports related to employees could be generated by this database like their retirement time, their pay scale, increments, appraisals etc. Inventory database holds store data items, their issue transactions, return transactions, total items issued etc. DW could support to generate consolidated reports. The data from these sources are stored in an area which is called Staging Area of DW. This is used for data processing during the extract, transform and load (ETL) process. This area is transient in nature, i.e. all contents are being erased following successful completion of an ETL process. There is another database to store metadata. This database contains data about data, i.e. data description of source database. The information is stored in different databases, data is collected and then consolidated reports could be produced. ETL activities are performed and data load into the staging area and then data loaded for reports generation according to metadata or fact tables.
RESULT-:
Data Warehouse is a central storage facility which can collect information from many sources, integrates it, manages it and delivers it to many clients, for effective storage and retrieval. It supports mangers by providing important information for making decisions. When the data warehouse application is implemented in the case company, users will be very curious to get reports according to their requirements. The system design has been carried out with ease of use being one of the highest criteria in the design of the software. It has an extremely user-friendly Graphic User Interface (GUI).
Data is extracted and copied onto special dedicated computers and then it can be validated, reformatted, reorganized, summarized and restructured from other sources. The resulting data warehouse is used for report generation, analysis, and presentation. Some of the results are observed and shown below-
Fig.3 shows the employees detail, in which number of employees of a particular label is shown. This could be an output from employee mart. It includes information regarding number of employees of each department.
Figure-3 Shows no. of employees
1 15
10
10
15 8 25
5 3 15
10
Employees detail
Admin
JENs
AENs
Pooja Nahar, Dr. Sanjay KumarIJSRE Volume 05 Issue 06 June 2017 Page 6680 Fig.4 shows the total no. of applications came in a specific month or duration for different utilities in case company. It helps the managers to find quickly that how many applications came for any request in any particular month or duration. This report would be generated from customer mart.
Figure 4 Shows number of applications
Fig.5 shows the number of pending applications report for any specific month or duration. This is also from customer mart. By this type of report manager could be helped in taking decisions that why the applications were not proceed and who is the responsible person.
Figure- 5 Shows Pending Applications
PROBLEMS IN IMPLEMENTATION OF DATA WAREHOUSE-:
As DWs are a important tool for making efficient decisions in data driven DSS environment, but there are many problems associated with it; some employees related, some customers related and may be some organization related. Building data warehouses is a difficult task. Initially, at the time of development it found to be costly, time consuming, and resource intensive. Over the years, it shows its importance to all the concerned and related people. This is especially true that development and deployment of DW should be with the help of experts. It needs expertise and tactics for developing complex DWs. DWs requires business skill, technology skills, and program management skills in building and using it, as this a complex task [8]. Employees are not sound in their computer knowledge, so they need proper training and assistance to use DWs. To find better, accurate and consistent results data need to be entered properly in the database [9].
CONCLUSION-:
This paper describes the need of Decision Support System in public organization. It includes the framework of the application proposed and defines the process of simulating a web based DSS using data warehouse. It shows the general architecture of Data Warehousing and architecture of the case company using Data Warehousing. It also describes the benefits and the problems of data warehousing implementation. It
0 100 200 300 400 500 600
No. of Applications
Count
0 50 100
No. of Pending
Applications
Pooja Nahar, Dr. Sanjay KumarIJSRE Volume 05 Issue 06 June 2017 Page 6681 explains why the projects in public sectors tend to fail and what the importance of GUI in implementation is. We also identify some results which could be seen and understood easily by the users.
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