Table of Contents:
Table of Contents: 1
• Objective of the project: 4
• Implications and limitation. 5
Project Topic outline: 7
Lists of Symbols: 7
1. Introduction including any relevant background information. 8
2. A description of the aim of the project. 10
3. Background research/literature review/requirements analysis. 11
4. Literature Review.. 12
Data Warehousing Definition. 12
Example of Data Warehousing. 14
Relevance of Data Warehouse. 14
Data Warehousing: Process 16
Data Warehouse: Architecture. 17
5. A description of the methods/approach used to implement your project 17
6. Results /Implementation, discuss the outcomes of the method used. 19
7. Analysis and discussion of the project outcomes. 20
8. Conclusions: 21
9. Recommendations: 22
Execution & Results or Analysis & Discussion: 22
Implications & Limitations: 24
Lessons Learned: 25
o Meaningfully synthesize connections among experiences from the project (including life experiences and academic experiences) to deepen understanding of fields of study and to broaden own points of view. 25
o Did the project meet scope, time, and cost goals?. 26
o Were the IT practices used in your project conducted ethically (use the ACS Code of Ethics to respond) 26
o Regarding managing the project, what were the main lessons you learned?. 27
o Describe one example of what went right on this project. 27
o Describe one example of what went wrong on this project. 28
o Outline what will you do differently on the next project based on your experience working on this project? 28
1. Detailed theoretical analyses. 34
2. Tabulated records of results, with reference to instruments or sources as appropriate. 35
• Summary: Write a summary of the report
One of the major advancements involved in information systems is defined as being data warehousing. The key aim regarding this research is to offer a comprehensive as well as systematic research data to elaborate on the key roles regarding data warehouse in the concept of information systems. The information offered in this research paper is on the manner in which data Warehouses can alter an organization as well as the meaning of data warehouse and even information systems with the use of peer reviewed resources on writing and in the presentation of the data. There is an elaboration on the concept of business intelligence which is a famous concept associated with data Warehousing.
The current era is one which is filled with numerous developments especially in the concept of information technology. Data Warehousing has become a common household name in most of the firms that are dealing with IT as well as data analytics. Large corporations are now dealing with high amounts of data which has forced them to look for alternatives on storage and management of data for safety purposes. Business intelligence has helped in the management of data in organizations (Ariyachandra and Watson, 2010). This has been a good way of helping these organizations to attain efficiency and feasibility in the data management. The following research final paper focuses on understanding the concept of data warehouse by elaborating on the key features associated with data warehousing and the role it plays in information systems with a key focus on business intelligence.
• Purpose/Motivation or Problem Statement: research questions, relevance & context of the project
Data warehousing is considered to be extensively utilized in information technology systems as well as business intelligence which is also a key part regarding information systems. The content regarding this project is to discuss the concept of data warehousing as well as its significance on information systems with a key focus on business intelligence.
• Objective of the project:
The identified project objectives are considered to be measurable because of the enhanced business agility as well as performance outcomes. The objectives in this research paper accommodate specific as well as measurable, achievable and time bound aspects on the actual time along with the integrated Platform with a key aim of offering support to the information systems in the identified business strategic IT initiatives as well as measurable on the manner in which big data issues are easily manageable through the concept of data warehousing on information systems as well as business intelligence. The following are key objectives associated with the project:
· Supporting decision making within the given information system as well as the business intelligence platforms. Data warehousing as well as information systems are usually utilized collaboratively to help in the creation of specific insights into the given business operations and this offers robust arguments in supporting business decisions (Köksal and Ticonderoga, 2019).
· The accomplishment of the identification regarding the contribution to the identified data warehousing in the concept of information systems accommodating the business intelligence as well as in the improvement of business agility.
· Management of the highlighting of the manner in which the modern data warehousing contribution has effectively accommodated basic and essential features like real time as well as integrated platforms to help in the supporting of the information system in the identified business strategic IT kind of initiatives.
· Achievement of the illustration of the manner in which data warehousing as a key process for the electronic data collection as well as accommodating the trove historical information for the key analysis as well as decision making in the given big data era happens to help in the management of essential data in the company operation systems (Reddy & Suneetha, 2021).
• Design/Methodology/Approach: Explain the methods used for the data collection in your project (this includes literature; and other analyses your project requires)
Design Methodology is associated with stressing the utility of brainstorming to help in the encouragement of innovative ideas as well as collaborative thinking to work via each of the proposed idea as well as in arriving at the most appropriate solution. The following project uses external sources, specifically the secondary data sources that is literature reviews and other published sources to attain the information which is needed in the achievement of the project objectives (Yao & Chakraborti,2021).
• Results/Findings: Briefly outline the results of your systematic search; the consistent themes, any gaps if appropriate (one or two sentences).
In the current years, the identified database community has been associated with witnessing the emergence regarding a current form of technology which is called data warehousing. With the many and key developments in information systems and in data management, data warehousing is a key emerging concept that needs to be understood comprehensively so as to understand the benefits and the future of data warehousing in not only the large corporations but also in the small businesses.
• Implications and limitation.
The project is highly vital in enhancing the knowledge and skills of students in this field and other related fields. Nonetheless, it will also help in offering information along with knowledge needed by firms to understand how data warehousing operates and the benefits it brings about to the information systems of such companies and businesses. Notably, the identified project is one which is Limited to seeking the key role regarding the concept of data warehousing on the information systems as well as in the accommodation of the business intelligence concept and enhancement of the aspect of business agility. This project is highly feasible in the accommodation of the key concepts regarding business intelligence as well as data warehousing on the manner in which information systems are usually attainable. However, it is vital to note the notable and evident limitations that are present in the given project (Voronkova et al., 2017).
First and foremost, there is the key need to effectively evaluate the manner in which emergency technologies, accommodation of the actual time as well as integrated data warehousing has an impact on the future regarding data warehousing as well as applications in information systems and business intelligence. Accommodation of data mining as well as data warehousing and even business intelligence in the identified information system the given project is considered to be highly feasible due to the fact that there is a basic kind of framework to attain project goals. Therefore, it is vital to note that the given project will effectively operate within the given praxis regarding data warehousing concepts to enhance business intelligence as a key IY strategy in firms.
• Conclusion of abstract: final assessment of the overall evidence and how it helped you to finish this project (one or two sentences).
A data warehouse is considered as being a global repository which is associated with the storage of the pre processed kind of queries on data which is associated with residing in a variety, probably heterogeneous as well as operational or even legacy kinds of sources. The identified information that is usually stored on the given data warehouse can be efficiently as well as easily accessed for enhanced decision making. The current research has been associated with causing current forms of developments in all the given aspects associated with data warehousing, however it is vital to note that there are numerous kinds of issues which need to be handled in the most appropriate manner for enhancing the efficiency of data warehousing. In the following research, there is a discussion of data warehousing as a concept in in depth for increased knowledge and understanding of the concept and the key role it plays in information systems (Ariyachandra and Watson, 2010).
Project Topic outline:
Include the original project topic outline that you chose for your project. This is helpful for the second marking understanding what your project is about. Prepare a final report that concisely details the work completed during your project. (Use your project plan)
Data warehousing is highly utilized in the concept of business intelligence which is identified as being a part of the information systems. The identified content regarding this project will help in the discussion of the data warehousing concept as well as the key concepts associated with it and the key significance of data warehousing in relation to information systems with a key focus on business intelligence. The given project will highly focus on what data warehousing as a concept it is as well as the issues and the significance associated with data warehousing and the kind of industries that have benefited from the use of data warehousing in the information systems. The key reasons as to why data warehousing are usually created is very vital to understand in this project. The project will highly elaborate on the examples of industries that are using data warehousing with a key focus on the key reasons as well as the benefits on the same (Raza et al., 2020).
Lists of Symbols:
Your final report mush includes – Tables; Figures; Abbreviations; Charts; Graphs, Pie Charts.
Data Warehouse Architecture
Characteristic of Data Warehouse
Analysis of Data Warehouse
Australian Computer Society Code of Ethics
The actual report consists of sections arranged to suit the individual needs of each project, and should include the following:
1. Introduction including any relevant background information.
Write an exceptional introduction that grabs interest of reader and states topic clearly. Write an excellent description of research question, problem (including statement of purpose and relevance). The scope should include context, boundaries and assumptions.
The concept of technology is one that is associated with being a leading factor in the world and thus the management of data efficiently along with effectively plays a key role in any company’s activities. Most of the IT departments in companies utilized excel function for the key budgeting strategy but that is associated with coming with numerous issues such as the issue of flexibility and complexities in the preparation of the budget strategy, issues in the identified consolidation regarding the specified budget and in most of the cases the deployment of the budget associated plans. The current era is one that is highly technological and this has added another layer of complexities in the IT industries and the related industries who rely on IT activities and processes.
To effectively solve these issues, it is important to note that data warehousing is associated with playing a key role in any information systems sector for any firm. Such as centralized kind of data warehouse ought to be highly capable in the management of all the financial expenses, whether this is planned earlier in time or it came about unplanned and promptly. In the key aim and attempt to facilitate the evaluation of the manner in which the strategic business IT kind of initiatives like the data warehouse as well as support on the information systems within a given business organization, it is vital to note that there is an essential need for the accommodation of data warehouse as a form of a data repository as well as data warehousing as an entire kind of process which is associated with the facilitating of the use of data gathering formed to offer support to decision making within the given business intelligence kinds of platforms.
Data warehousing is considered as being the vast collection regarding business data, which is associated with helping firms in the making of effective along with efficient business decision. To help in the revelation of business intelligence an appropriate decision making support kind of system is needed which is essential in facilitating the transition of data. The identified concept regarding data warehousing is one which was effectively introduced in the year 1980. Data usually comes from distinct kinds of sources which usually range from the internal applications well as the external applications. Data from the distinct kinds of sources is one that is usually extracted in the effective format as well as is then effectively imported to an effective kind of format which is regraded as being highly supportive in regard to the increment of business intelligence.
There is an identified scope as well as are substantial benefits and advantages that are usually added to the given data warehouse which is associated with helping to make effective and highly efficient presentation regarding data. To attain highly essential data from the distinct sources, it is vital to note that there is the need to utilize analytical kinds of tools as well as data warehousing helps in the storage of data with effective quality as well as integrity. The faster decision is associated with helping to attain higher level of productivity as well as increment in revenue which is considered to be probable with the utility of the concept of data warehousing.
2. A description of the aim of the project.
The key aim of the project is finding out the key role regarding data warehousing on the concept of information systems as well as the accommodation of business intelligence. Essentially, information technology developments is usually associated with being geared towards enhanced applications in the business organizations to help in offering higher level of efficiency and effectiveness as well as agility in the business process, higher level of profitability and even continuation at a cost efficient kind of Platform. In the same manner, the given project usually is associated with the identification of the technologies like data warehousing kinds of projects in information technology kinds of systems as well as resonating with the basic IY projects on the enhancement of business performance effectively as well as cost efficiently.
At the personal level, the given project is essential in offering the basic and essential relevance with the ambition as well as the key need to effectively apply information technologies to help in the improvement of the businesses in the actual world situation as well as in the accommodation of the business intelligence concepts. Moreover, accommodation of a detailed along with a comprehensive literature in the concept of data warehousing would help in enhancing human knowledge as well as comprehensive understanding regarding data warehousing on the information systems as well as business intelligence. Therefore, the given project is highly vital in the accommodation of general as well as personal relevance towards enhanced performance on the business enterprises.
3. Background research/literature review/requirements analysis. This should be based on the work you completed in the interim report and the heading used needs to reflect the project type undertaken.
Management of big data as well as information within the given business organization is associated with having proven to be an issue as well as a key challenge with the increment as well as the development on the information technology adaptation by the given business firms, unavailing the key need for an identified business strategy as well as IT initiative to help in the solving of such kind of issues. In an aim to help in the finding of the most appropriate solutions to such kinds of issues within the business organization, the key objective regarding this given project is considered to be seeking the key roles regarding data warehousing on the information systems as well as in the accommodation of the business Intelligence concept.
In this given project, there is the laid out plan to operate on researching on the issues as well as significance regarding data warehousing, from the research on what data warehousing is, through offering relevant examples associated with data warehousing as well as to the key reasons as to why they are used , to the key reasons as why organizations and businesses do not depend on databases and why they use warehousing for assistance. Through the effective completion of this project, it will help on offering knowledge as well as understanding needed in offering in depth as well as comprehensive research on the key roles regarding data warehousing on the concept of information systems.
4. Literature Review.
Choose a variety of information sources appropriate to the scope and discipline of the research question. Select sources after considering the importance (to the researched topic) of all criteria used (such as relevance to the research question, currency, authority, audience, and bias or point of view). Synthesize in-depth information from relevant sources representing various points of view/approaches.
Data Warehousing Definition
Data warehouse is Considered as being a repository regarding enterprise or even the business databases which offers a comprehensive picture regarding the current as well as the historical operations associated with a firm. Since it is associated with offering a coherent as well as a comprehensive kind of picture associated with the business conditions at a specific time, it is usually utilized for the effective as well as efficient decision making kind of process. It is associated with entailing the advancement of systems which usually assists in the extraction regarding the given data in a manner that is highly flexible. Data mining is associated with the description of the process associated with the designing of the manner in which the given data which is usually stored so as to help in the improvement of the reporting as well as the analysis process.
Data warehousing professionals are associated with putting into consideration that the various kinds of stores regarding data are usually linked as well as associated to one another conceptually and even physically. The data of any business is often considered to be stored across a variety of databases. However, it is essential to note that to be highly capable to analyse the widest range regarding data, each of the given databases is associated with being linked in some manner. This is used to mean that the given data which is within them requires a key way of being associated to other essential data as well as that the identified physical databases themselves usually have a link so their given data can be looked at collaboratively for the purpose of reporting (De Mul et al., 2012).
Fig 1: Data Warehouse
It is essential to note that a variety of the data stores are usually integrated by the identified Data Warehouses as well as this information is often utilized but the key leaders as well as managers for enhancing improved decision making. Data warehousing kinds of environments is associated with the inclusion of extraction regarding the regional databases that is the Transformation as well as Loading and the Online Analytical Processing. As any business grows and expands globally, the identified parameters as well as the complexities entailed in the analysis process as well as decision making usually become highly complex (Özcan & Peker, 2021).
Data access portion which is considered to be available in the key form regarding products is Considered as being the most visible part regarding a data warehouse project. Data Warehousing process is associated with the transformation regarding data from the original format to the dimensional data store which is associated with the consumption of a higher level percentage regarding effort as well as time and even expenses. Since the identified implementation regarding the data Warehousing is considered as being costly as well as essential, there are numerous data extraction as well as data cleaning tools and even load and fresh utilities that are usually available for the same. It is vital to understand that one of the most essential features regarding the data warehouse is data integration.
Example of Data Warehousing
Facebook is considered as being a great example of data Warehousing since it is associated with doing that on its daily operations. Facebook is a famous social media Company which is associated with the gathering of AI data like friends as well as likes and groups among others. All these kind of data that is gathered by the company are usually stored into a single kind of central repository. Although the company of Facebook is involved in the storage of all these kind of information into separate forms of databases, usually they store the most essential as well as vital information into a single central aggregated kind of databases. This is due to numerous reasons such as making sure that individuals perceive the most essential ads which are highly likely to click on or even friends that they suggest are usually the most vital to an individual (Drake, 2021).
Relevance of Data Warehouse
Data warehouse is considered to be a subject oriented as well as time variant, integrated and even non volatile gathering of data. Data cleansing as well as data integration and even Online Analytical Processing are all considered as being part of the data Warehousing technology. It is associated with offering a whole as well as consistent data store from the numerous sources which can be effectively understood as well as utilized in the business applications. Some of the given application areas entail the integration of the data across the entire firm as well as quick and efficient decisions on the current and even historical data, management and the control of Businesses among others (Liu et al., 2021).
Data Warehousing is considered to be an highly essential business intelligence tool which allows firms to be efficient and feasible in different ways. First and foremost it is associated with facilitating high level consistency. Data Warehouses are usually effectively programmed to effectively apply a uniform format to all the gathered data. This is associated with making it easier for the corporate decision makers to efficiently as well as effectively analyse as well as share the data insights with their given colleagues globally. The standardizing of data from the distinct sources is also associated with the reduction of the risk regarding error in the interpretation as well as in the enhancement of overall accuracy (Neamah, 2021).
Moreover, it is associated with enhancing the business decisions. The successful business leaders usually are involved in the development of the data driven technique as well as rarely come up with decisions without in any way consulting the given facts. Data Warehousing is associated with the improvement of the speed as well as the efficiency regarding the accessing of the distinct kinds of data sets as well as it makes it easier and more efficient for the corporate decision makers to derive effective insights that will help in guiding the identified business as well as the marketing techniques that usually are involved in setting them apart from their identified competitors.
Nonetheless, it is associated with improvement of their identified bottom line. The data warehouse kind of platform usually allow the business leaders to efficiently as well as effectively access their historical Activities of the firm. It also helps in the evaluation of the initiatives which have been highly efficient or even not efficient in the previous times. This is associated with allowing the executives and the leaders to perceive where they can effectively adjust their identified strategy to facilitate the decrement of costs along with the maximizing of the level of efficiency and in the increment of sales to help in the improvement of their identified bottom line (Friedrichs, 2021).
Data Warehousing is also associated with the delivery of improved business intelligence. Through having effective access to information from a variety of sources from a single kind of platform, decision makers will no longer be required to be dependent on the limited data or even their instincts. Moreover, it is vital to note that the data warehouse can effortlessly and effectively be applied to any kind of business process such as the market segmentation as well as IT management and so forth. It also helps in saving time (Gladić & Petrovački, 2021). A data warehouse is associated with the standardizing as well as the preservation and even the storage of data from the distinct sources, helping in the identified consolidation and even in the integration regarding all the given data. Since the critical data is considered to be available to the users, it is associated with allowing them to come up with highly informed decisions on the key aspects (Sylvestre et al., 2018).
It is also associated with improving data quality along with consistency. A data warehouse is associated with the conversion of data from numerous sources into a consistent kind of format. Since the given data from across the entire organization is considered to be standardized, each kind of department will be involved in the production of outcomes which are consistent. This is associated with causing more accuracy of data which will help in decision making. Furthermore, it is associated with the streamlining of the flow regarding information via a network that connects all the related as well as the non related parties (Chang et al., 2021).
Data Warehousing: Process
Data warehousing is defined as being the key process regarding the centralizing or even the aggregation of data from Numerous sources into a single common kind of repository. Data warehousing is associated with taking place prior to data mining taking place. Data warehousing is associated with involving a strict engineering kind of phase whereby no any form of business users are entailed. In the data warehousing, data stored in the distinct databases are usually combined into a single comprehensive as well as efficiently understood and accessible database. This is usually considered to be available to the business professionals or even the managers who are associated with the utility of the data for the purpose of data mining and in the creation of forecasts. Data is usually fed from numerous disparate sources into the given data warehouse which is usually again converted as well as reformatted, summarised and utilized for the managerial decision making purposes (Arora & Gosain, 2021).
Data Warehouse: Architecture
Data warehouse architecture is usually on the basis of a variety of Business processes related with any business. Some other kinds of considerations while going for the identified architecture associated with a data warehouse entails data modelling as well as enough security, metadata management, extent regarding query requirements and the use of full technology. Metadata is considered as being the type of data which is usually stored either as a form of unstructured or even in the semi structured manner (Alkraiji, 2021). These kind of summary data are usually highly essential in the given data warehouse. For instance, simple kinds of data warehouse query can be utilized in the retrieval of the sales made in the month of January. Data Warehousing type of architecture can be revealed with the given materialized view in the famous Oracle 9i as depicted below.
Fig 2: Data Warehouse Architecture
5. A description of the methods/approach used to implement your project (including justification of the choices made where appropriate). All elements of the methodology or theoretical framework should be skilfully developed. Appropriate methodology or theoretical frameworks may be synthesised from across disciplines or from relevant sub disciplines.
Methods as well as approaches used in the implementation of a project are key to any project and need to be understood in the best way possible for enhanced efficiency and effectiveness. The following project used external sources and to be precise the secondary data sources. When the data is usually gathered from outside an organization, it is usually referred to as external sources of data. Secondary data is used to define the second hand information. It is usually considered to be not originally gathered as well as it is instead attained from the already published or even the unpublished sources. The following project used published Secondary data for enhanced efficiency as well as feasibility of the information offered. There was the use of numerous published sources inclusive of journals as well as the periodicals that are published by various kinds of governments globally (Hemler et al., 2021).
There are numerous precautions which were undertaken in the use of the secondary data to ensure efficiency in the whole research process. First and foremost, there was the confirmation on the reliability of the agency to help in having reliable published data. Moreover there was the suitability regarding the given aim associated with enquiry whereby there was the investigation of the data prior to its use to ensure that the given data is highly suitable for the key aim regarding the present enquiry and this was done via the investigation of the nature along with objectives and even time regarding the collection (Hasselbring, 2000).
There was the consideration of the adequacy as well as the accuracy levels to avoid impact regarding bias. It is vital to utilize adequate data to avoid any kind of biased as well as prejudices causing inappropriate conclusions (Baran, 2021). There is also the method regrading the collection of the data utilized. For this consideration, there was the ascertaining as to the kind of method to use in the collection of the data for enhanced efficiency and feasibility. In overall this helped in attaining updated and feasible data for use in the whole process (Seneviratne et al., 2018).
6. Results /Implementation, discuss the outcomes of the method used. For this project report, it is expected that some tabular data that shows the results of your project activities/methodological approach will be included.
Figure 3: Characteristics of Data Warehouse
Data warehouse is Considered as being a repository regarding enterprise or even the business databases which offers a comprehensive picture regarding the current as well as the historical operations associated with a firm (Dahaoui et al., 2021). Since it is associated with offering a coherent as well as a comprehensive kind of picture associated with the business conditions at a specific time, it is usually utilized for the effective as well as efficient decision making kind of process. It is associated with entailing the advancement of systems which usually assists in the extraction regarding the given data in a manner that is highly flexible. Data mining is associated with the description of the process associated with the designing of the manner in which the given data which is usually stored so as to help in the improvement of the reporting as well as the analysis process (Madurapperuma et al., 2018).
Figure 4: Analysis of Data warehouse
7. Analysis and discussion of the project outcomes. From the work you have completed, extract the important issues from the information you have accumulated and choose suitable information (must use diagrams, images, graphs etc.), to aid the comprehension of the text. Explain the significance of the project outcomes in relation to other relevant published work.
A data warehouse usually is associated with maintaining the copy of information from the given source of transaction systems. This kind of architectural complexity is associated with offering the opportunity to effectively integrate data from Numerous sources into a single form of database as well as the data model. More level of congregation regarding data to the single databases so a single kind of query engine can be utilized in the presentation of data in an identified ODS. It also offers the opportunity to mitigate the issue regarding the given database isolation level lock kind of contention in the identified transaction processing systems that is caused by the key attempts to operate lathe as well as long running analysis kind of queries in the transaction processing kinds of databases. It also helps in the maintenance of data history even in the cases whereby the source kind of transaction systems do not (Kortüm et al., 2017).
8. Conclusions: A critical statement of what has been achieved or demonstrated with this project, based on the analysis and discussion of the results. The conclusion should sum up the main points of the report and should clearly relate to the objectives of your report.
Data mining as well as the data warehouse Technologies are associated with having a bright future in the various business applications as it is associated with helping in the generation of the current probabilities by the automated prediction regarding trends as well as behaviours involved in the large database. Data mining techniques usually assist in the automatic discovery of the unknown patterns such as the identification of the anomalous data that is involved in the highlighting of the key errors which are usually generated during the time of data entry (Golfarelli et al., 2004).
It is important to note that data warehouse as well as data mining technologies have become a big hit with a variety of industries such as sales as well as marketing , financial institutions and much more. These technologies are considered to have numerous benefits in the varying fields. The immense data volumes as well as highly complex knowledge discovery procedures related with the business firms usually make the given data warehouse with its identified OLAP as well as data mining tools to be a highly essential technology which supports decision making and overall success in the firm (Berndt et al., 2001).
9. Recommendations: A statement of further work or action you consider to be necessary, e.g. during the investigation/project it may have become apparent that it would be desirable to carry the study beyond the planned objective or that some problems encountered should be explored in greater depth than was possible or necessary in the current project.
For the efficiency and the feasibility of the future work on the role of data Warehousing on information systems, it is vital for the subject to be studied and explored in in-depth as this will help in having comprehensive understanding of these key roles and being able to apply the same in industries (Bouadi et al., 2017).
Execution & Results or Analysis & Discussion:
Organize and synthesize evidence excellently to reveal insightful patterns, differences, or similarities related to focus.
Data warehouse is considered to be a subject oriented as well as time variant, integrated and even non volatile gathering of data. Data cleansing as well as data integration and even Online Analytical Processing are all considered as being part of the data Warehousing technology. It is associated with offering a whole as well as consistent data store from the numerous sources which can be effectively understood as well as utilized in the business applications. Some of the given application areas entail the integration of the data across the entire firm as well as quick and efficient decisions on the current and even historical data, management and the control of Businesses among others (Dobbs et al., 2002).
Propose one or more solutions/ hypotheses that indicate a deep comprehension of the problem. Solution/ hypotheses should be sensitive to contextual factors as well as all of the following: ethical, logical, and cultural dimensions of the problem.
For the efficiency and the feasibility of the future work on the role of data Warehousing on information systems, it is vital for the subject to be studied and explored in in-depth as this will help in having comprehensive understanding of these key roles and being able to apply the same in industries (Zhou et al., 2011).
Evaluation of solutions should be deep and elegant (for example, should contain thorough and insightful explanation) and includes, deeply and thoroughly, all of the following: considers history of problem, reviews logic/ reasoning, examines feasibility of solution, and weighs impacts of solution.
The solutions to achieving this is by having more in depth and comprehensive research on data Warehousing as well as its significance when it comes to information systems. This will help in avoiding issues of unlimited data on the Concept which limits its application in the different IT companies (Inmon, 1996).
Implement the solution in a manner that addresses thoroughly and deeply multiple contextual factors of the problem.
The solution can be effectively Implemented via the use of professionals as well as experts who will help in the analysis of the issue and the gap and come up with effective solutions on the same via the use of comprehensive research (Jeble et al., 2017).
Review results relative to the problem defined with thorough, specific considerations of need for further work.
It also offers the opportunity to enhance data quality. This is achieved via the provision of consistent types of codes and even descriptions , fixing bad data. There is also the presentation of the information of the organization in a more consistent manner. It also offers a single common kind of data model for all the given data regarding interest of the organization despite the source of the data. This is essential in the organiztaion as well as disambiguation of the repetitive data forms. This is also key in enhancing the making of the decision support kinds of queries easier to write. The project work offers information on how all these benefits are achieved which is key for firms and individuals that are willing to venture into data warehousing and this is also an extension of the other published works. Extensive research is needed on data warehousing on specific companies in the IT industry (Issa, 2002).
Implications & Limitations:
Insightfully discuss in detail relevant and supported limitations and implications.
The project is highly vital in enhancing the knowledge and skills of students in this field and other related fields. Nonetheless, it will also help in offering information along with knowledge needed by firms to understand how data warehousing operates and the benefits it brings about to the information systems of such companies and businesses. Notably, the identified project is one which is Limited to seeking the key role regarding the concept of data warehousing on the information systems as well as in the accommodation of the business intelligence concept and enhancement of the aspect of business agility (Al-Debei, 2011). This project is highly feasible in the accommodation of the key concepts regarding business intelligence as well as data warehousing on the manner in which information systems are usually attainable. However, it is vital to note the notable and evident limitations that are present in the given project.
First and foremost, there is the key need to effectively evaluate the manner in which emergency technologies, accommodation of the actual time as well as integrated data warehousing has an impact on the future regarding data warehousing as well as applications in information systems and business intelligence. Accommodation of data mining as well as data warehousing and even business intelligence in the identified information system the given project is considered to be highly feasible due to the fact that there is a basic kind of framework to attain project goals. Therefore, it is vital to note that the given project will effectively operate within the given praxis regarding data warehousing concepts to enhance business intelligence as a key IT strategy in firms (Alhyasat & Al-Dalahmeh, 2013).
This section enables students to step back from the project and more objectively analyse what they have learned from the project.
o Meaningfully synthesize connections among experiences from the project (including life experiences and academic experiences) to deepen understanding of fields of study and to broaden own points of view. Make explicit references to previous learning and applies in an innovative (new and creative) way that knowledge and those skills to demonstrate comprehension and performance in novel situations. Envision a future self (and possibly makes plans that build on past experiences) that have occurred across multiple and diverse contexts.
The project has helped me in understanding different and essential lessons on data warehousing. A data warehouse is a key process used in the collection as well as in the management of data from a variety of sources to offer essential business insights. A data warehouse is usually utilized to link as well as in the analysis of business data from heterogeneous types of sources. The identified data warehouse is considered as being the core regarding the BI system which is usually built for the process of data analysis along with Reporting. I also learnt that it is a blend regarding Technologies as well as components which help in aiding the strategic utility of data. It is defined as being the electronic storage regarding a large amount regarding information by a given business which is formulated for query as well as analysis rather than the transaction processing (Gupta et al., 2015).
The project also helped me to understand who needs the data warehouse. The data warehouse is usually required for all kinds of users such as the decision makers who are dependent on the huge amount of data. It is also required by the users who usually customize as well as are involved in the complex processes to attain information from various data sources. It is also essential to be utilized by the individuals who want simple technology to effectively access the given data. It is also vital for the individuals who desire a systematic kind of approach for the making of decisions. Data warehouse is considered as being a first step if an individual wants to effectively discover the hidden patterns regarding the data flows as well as groupings (Fernández-Manzano et al., 2016).
Another key lesson attained from the project is the purpose and usage of the data warehouse. There are numerous sectors whereby data warehouse is utilized. First and foremost, there is the airline which uses the data warehouse for operation purposes such as the crew assignment as well as promotions and so forth. The banking sector uses data warehouse to facilitate the management of the identified resources available on the desk effectively. The healthcare industry uses data warehouse to facilitate the strategizing and in the prediction of outcomes in different services (Harris, 2013).
This section should also address the following issues:
o Did the project meet scope, time, and cost goals?
The project did meet the scope as well as time and the cost goals. This was facilitated by the effective planning and the management of all schedules related with the project. All the instructions were also followed to the latter and this avoided any extra costs that come with inappropriate planning.
o Were the IT practices used in your project conducted ethically (use the ACS Code of Ethics to respond)
The ACS code of ethics is essential and it helped in the completion of this project by outlining the ethical principles which govern decisions as well as behaviour at a firm. It was used in offering a general outline on the manner in which professionalism and integrity ought to be used for projects. This helped in enhancing ethical standards of the IT project (McDermid, 2011).
o Regarding managing the project, what were the main lessons you learned?
In regard to the management of the project, there are some key lessons which I learnt. I learnt that not all the projects are smooth and each time changes are made to a project it disrupts the workflow and thus the need to have knowledge on effective completion of the project and in meeting the deadlines. An individual may also experience numerous issues which can in the end impede the identified progress regarding the project as well as cause failure. This is the key reason as to why it is vital to fight for the viability regarding their identified projects.
I also learnt that it is alright if an individual does not know everything. Most of the project managers usually feel that they need to be perfection. However, the experienced individuals in project management will tell people that having knowledge on what one does not know is vital to being am effective project manager. I also learnt that it is vital to not overestimate ones capabilities and end up with the wrong decisions. This is to mean that insights as well as inputs is key for one to be effective in any project (Shahid et al., 2021).
Moreover, I got to learn that it is vital to avoid depending on tools for any critical work. Project managers are usually judging a variety of responsibilities in a simultaneous way. As an outcome, some of the project managers end up depending on distinct project management tools so as to make their lives easier. The use of the latest and most current project management tools is a key way to help in saving time and in the successful completion of task. This helped me in achievement of efficiency as well as feasibility in the entire project management and completion.
o Describe one example of what went right on this project.
An example of what went right in this project was my planning in terms of time. I was able to come up with an efficient time schedule. This helped me in meeting the deadline and in planning my time for each section. Time management is crucial in any project for successful completion of the tasks ahead.
o Describe one example of what went wrong on this project.
An example of went wrong in the project was the setting of goals. This is because despite having formulated SMART goals and objectives, I overestimated my capabilities in project management which led to unmet expectations in the project.
o Outline what will you do differently on the next project based on your experience working on this project?
What I will do differently in the next project is in regard to setting of goals. I will consult my supervisors as well as friends on the same on having effective goal setting. It will help in balancing everything and in the successful completion of tasks.
Alhyasat, E. B., & Al-Dalahmeh, M. (2013). Data warehouse success and strategic oriented business intelligence: a theoretical framework. arXiv preprint arXiv:1307.7328.
Alkraiji, A. I. (2021). Top Management’s Role in Promoting Decision Support Systems Efficiency: An Exploratory Study in Government Sector in Saudi Arabia. In Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering (pp. 1409-1429). IGI Global.
Berndt, D. J., Fisher, J. W., Hevner, A. R., & Studnicki, J. (2001). Healthcare data warehousing and quality assurance. Computer, 34(12), 56-65.
Gupta, A., Agarwal, D., Tan, D., Kulesza, J., Pathak, R., Stefani, S., & Srinivasan, V. (2015, May). Amazon redshift and the case for simpler data warehouses. In Proceedings of the 2015 ACM SIGMOD international conference on management of data (pp. 1917-1923).
Harris, D. (2013). Why Apple, eBay, and Walmart have some of the biggest data warehouses you’ve ever seen. Gigaom. URL: https://gigaom. com/2013/03/27/why-apple-ebay-and-walmart-have-some-of-the-biggest-data-warehouses-youve-ever-seen.
In McDermid, D. (2011). Ethics in ICT: An Australian perspective
Jeble, S., Kumari, S., & Patil, Y. (2017). Role of big data in decision making. Operations and Supply Chain Management: An International Journal, 11(1), 36-44.
Fernández-Manzano, E. P., Neira, E., & Clares-Gavilán, J. (2016). Data management in audiovisual business: Netflix as a case study. El profesional de la información (EPI), 25(4), 568-576.
Dobbs, T., Stone, M., & Abbott, J. (2002). UK data warehousing and business intelligence implementation. Qualitative Market Research: An International Journal.
Golfarelli, M., Rizzi, S., & Cella, I. (2004, November). Beyond data warehousing: what’s next in business intelligence? In Proceedings of the 7th ACM international workshop on Data warehousing and OLAP (pp. 1-6).
Zhou, H., Yang, D., & Xu, Y. (2011). An ETL strategy for real-time data warehouse. In Practical applications of intelligent systems (pp. 329-336). Springer, Berlin, Heidelberg
Inmon, W. H. (1996). The data warehouse and data mining. Communications of the ACM, 39(11), 49-51.
Hasselbring, W. (2000). Information system integration. Communications of the ACM, 43(6), 32-38.
Issa, C. M. (2002). Data warehouse applications in modern day business.
Al-Debei, M. M. (2011). Data warehouse as a backbone for business intelligence: Issues and challenges. European Journal of Economics, Finance and Administrative Sciences, 33(1), 153-166.
J. Stuller, “Inconsistencies in data warehousing,” Proceedings 1999 International Symposium on Database Applications in Non-Traditional Environments (DANTE’99) (Cat. No.PR00496), 1999, pp. 43-50, doi: 10.1109/DANTE.1999.844940.
Bouadi, T., Cordier, M.O., Moreau, P., Quiniou, R., Salmon-Monviola, J. and Gascuel-Odoux, C., 2017. A data warehouse to explore multidimensional simulated data from a spatially distributed agro-hydrological model to improve catchment nitrogen management. Environmental modelling & software, 97, pp.229-242.
Kortüm, K.U., Müller, M., Kern, C., Babenko, A., Mayer, W.J., Kampik, A., Kreutzer, T.C., Priglinger, S. and Hirneiss, C., 2017. Using electronic health records to build an ophthalmologic data warehouse and visualize patients’ data. American journal of ophthalmology, 178, pp.84-93.
Madurapperuma, S., Ebert, L. and Kuruppuarachchi, D., 2018. In-house development & implementation of ‘corebrain’warehouse management system: a case study. In Proceedings of the 2nd International Conference in Technology Management, iNCOTeM (pp. 67-72).
Seneviratne, M.G., Seto, T., Blayney, D.W., Brooks, J.D. and Hernandez-Boussard, T., 2018. Architecture and implementation of a clinical research data warehouse for prostate cancer. eGEMs, 6(1).
Ariyachandra, T. and Watson, H., 2010. Key organizational factors in data warehouse architecture selection. Decision support systems, 49(2), pp.200-212.
Raza, B., Aslam, A., Sher, A., Malik, A.K. and Faheem, M., 2020. Autonomic performance prediction framework for data warehouse queries using lazy learning approach. Applied Soft Computing, 91, p.106216.
Sylvestre, E., Bouzillé, G., Chazard, E., His-Mahier, C., Riou, C. and Cuggia, M., 2018. Combining information from a clinical data warehouse and a pharmaceutical database to generate a framework to detect comorbidities in electronic health records. BMC medical informatics and decision making, 18(1), pp.1-8.
Köksal, Ö. and Tekinerdogan, B., 2019. Architecture design approach for IoT-based farm management information systems. Precision Agriculture, 20(5), pp.926-958.
Voronkova, O.V., KUROCHKINA, A.A., FIROVA, I.P. and BIKEZINA, T.V., 2017. Implementation of an information management system for industrial enterprise resource planning. Revista Espacios, 38(49).
De Mul, M., Alons, P., Van der Velde, P., Konings, I., Bakker, J. and Hazelzet, J., 2012. Development of a clinical data warehouse from an intensive care clinical information system. Computer methods and programs in biomedicine, 105(1), pp.22-30.
Arora, A., & Gosain, A. (2021). Intrusion detection system for data warehouse with second level authentication. International Journal of Information Technology, 13(3), 877-887.
Chang, C. H., Hsu, T. C., Chu, W. C. C., Hung, C. L., & Chiu, P. F. (2021). A Smart Service Warehousing Platform Supporting Big Data Deep Learning Modeling Analysis. Journal of Internet Technology, 22(2), 483-489.
Dahaoui, F. Z., Demraoui, L., Louhdi, M. R. C., & Behja, H. (2021). Toward Data Warehouse Modeling in the Context of Big Data. In Advances on Smart and Soft Computing (pp. 235-245). Springer, Singapore.
Drake, T. A. (2021). “We Have All the Data in One Place”: Examining Principals’ Use of a Data Warehouse During an Academic School Year. NASSP Bulletin, 105(2), 84-110.
Friedrichs, M. (2021). BioDWH2: an automated graph-based data warehouse and mapping tool. Journal of integrative bioinformatics.
Gladić, D., & Petrovački, J. (2021, March). Using a Data Warehouse System to Monitor and Analyze Student Achievement in Teaching Process: Student paper. In 2021 20th International Symposium INFOTEH-JAHORINA (INFOTEH) (pp. 1-6). IEEE.
Liu, Q., Feng, G., Tayi, G. K., & Tian, J. (2021). Managing data quality of the data warehouse: A chance-constrained programming Approach. Information Systems Frontiers, 23(2), 375-389.
Neamah, A. F. (2021, March). Adoption of Data Warehouse in University Management: Wasit University Case Study. In Journal of Physics: Conference Series (Vol. 1860, No. 1, p. 012027). IOP Publishing.
Özcan, M., & Peker, S. (2021). Designing a Data Warehouse for Earthquake Risk Assessment of Buildings: A Case Study for Healthcare Facilities. Sakarya University Journal of Computer and Information Sciences, 4(1), 156-165.
Reddy, G. S., & Suneetha, C. (2021). A Data Warehouse System for University Administration with UML Schema and Relational Decisive Approach. In Data Engineering and Communication Technology (pp. 543-559). Springer, Singapore.
Shahid, A., Nguyen, T. A. N., & Kechadi, M. (2021). Big Data Warehouse for Healthcare-Sensitive Data Applications. Sensors, 21(7), 2353.
Yao, Y., & Chakraborti, S. (2021). Phase I monitoring of individual normal data: Design and implementation. Quality Engineering, 33(3), 443-456.
Hemler, E. C., Korte, M. L., Lankoande, B., Millogo, O., Assefa, N., Chukwu, A., … & Fawzi, W. W. (2021). Design and field methods of the ARISE Network COVID-19 rapid monitoring survey. The American Journal of Tropical Medicine and Hygiene, 105(2), 310.
Baran, M. L. (2021). Mixed Methods Research Design. In Research Anthology on Innovative Research Methodologies and Utilization Across Multiple Disciplines (pp. 312-333). IGI Global.
1. Detailed theoretical analyses.
It is essential to note that a variety of the data stores are usually integrated by the identified Data Warehouses as well as this information is often utilized but the key leaders as well as managers for enhancing improved decision making. Data warehousing kinds of environments is associated with the inclusion of extraction regarding the regional databases that is the Transformation as well as Loading and the Online Analytical Processing. As any business grows and expands globally, the identified parameters as well as the complexities entailed in the analysis process as well as decision making usually become highly complex.
2. Tabulated records of results, with reference to instruments or sources as appropriate.