This report discusses the importance of data handling and Excel pre-processing in business intelligence. It explores the various functions of Excel and their relevance to different firms. The report also evaluates common data mining techniques and their applications in real-world business scenarios.
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Data handling and business intelligence
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Contents Contents...........................................................................................................................................2 INTRODUCTION...........................................................................................................................1 PART 1............................................................................................................................................1 1. Detailed examination of the uses that excel pre-processing data possess in the long run scenario for different firms..........................................................................................................1 PART 2............................................................................................................................................4 2.1 By using audidealership.csv that was provided in conjunction with Weka gives a specific example of clustering...................................................................................................................4 2.2 Detailed explanation as well as evaluation of the methods of common data mining that can be used in the business relating with real examples that are prevailing in the market................7 2.3 Detailed analysis and evaluation of Advantages as well as disadvantages of Weka over Microsoft Excel...........................................................................................................................9 CONCLUSION..............................................................................................................................10 REFERENCES..............................................................................................................................11
INTRODUCTION As it is known that data handling is one of the most important as well as crucial aspect in each and every business irrespective of the industry in which it is operating as it is related with the facts and figures of the firm that possess a lot of importance in the current market scenario (Boyles, 2019). In this report there is a brief discussion of various aspects that are related with a firm that is Smile Clinic and a detailed evaluation of various factors that are involves in it so as to do a systematic analysis as well as evaluation of different things that are pretty important from the company’s point of view. Apart from that different types of functions that are performed in Excel are also evaluated in this report according to the needs, requirements, and demand of the business. PART 1 1. Detailed examination of the uses that excel pre-processing data possess in the long run scenario for different firms There are many functions and uses of Microsoft Excel and an organisation can be listed in it for the sake of its clients, managers of the company, owner of the enterprise, collection of data, and constant as well as regular analysis of the functions of the Microsoft Excel. As there are many functions that are included in Microsoft Excel all of them are described below in detail in a systematic manner- Analyzing and storing data-As there are many other ways also to analyze and evaluate data and there are various ways too in which its storage can be done but in Microsoft Excel both can be done in a systematic and accurate manner that helps in detailed evaluation of all the aspects that carriers a lot of value in the industry. There are different tools that can be used in it so that storage of data can be done in a precise manner which would further result in improvement of the value of the firm in the market and thus enabling the company to sustain in the industry for a much longer period of time as compared to its competitors(Fatima and Linnes, 2019). Data recovery- It is one of the most important as well as essential part as in Microsoft Excel there is a tool which helps in recovering the data that is wrongfully deleted and thus adding the value to the operations of the organizations.
Making report-Microsoft Excel is also a very critical as well as crucial tool as it helps in making reports and that too in an effective and efficient manner with the help of different tools and techniques that are available in it. In MS Excel monitoring of the report can also be done in an accurate manner so that chances of any errors can be minimized. Research-Microsoft Excel also helps in doing a detailed research and analysis of all the different aspects of an enterprise so as to improve the productive and performance of that company which will result in improved sales and profitability enabling firm to grow and prosper in the industry in which it is operational. Conditional formatting-In Microsoft Excel there is a way through which firms can do formatting in the data according to the needs and requirements of the organization so that minimization of any type of misrepresentation can be done which proves very beneficial from the company’s point of view. Security-As important data is stored in Microsoft Excel it becomes very much important that the security of it remains the first priority of the organization and MS Excel provides all the security features so that it can be breached in any of the ways that are used by different people(Fernández-Manzano, Neira and Clares-Gavilán, 2016). Evaluating the use of IF function in Microsoft Excel-It consists of a comma that divides it into three pieces that is IF feature or it can be said IF declaration at times due to the function that it does. It provides useful information about income or the revenue that is generated by the firm and also describes the sales as well as expenses aspect in a step by step basis that helps in evaluating it in detail. Also old facts and figures can also be rearranged in a systematic manner with the help of this function in an appropriate way. Uses of the IF Element form-There are various uses of it and all of them are explained in detail below- It helps in shaping a form code. Also cell code can be checked with the help of it so as to analyse that requirements are fulfilled or not.
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If a function reveals the significance of B3, then if the value or the importance of B3 is less than that of B3's variable, thus parameter ofB1 will also mean that the IF parameter is more important than B3 as soon as this function is seen. User that is operating it should obtain the cell of B4 file after pressing the Enter key. To see the impact of it the user have to transfer the handle from D4 to cell D8400. If in an application user needs to learn about the H Lookup and V lookup aspects the firstly they are not supposed to be confused, whether or not the buyer wants it as this is an important skill. User will consider anything in detail if operating is being done with minimal numbers. Hence it would take much longer to locate each and everything in the data for the extension of the search(Kumar, 2018). Lookup Value-It is the base of the row of quest which is the base of the row. Table series-These are a series of table from which the necessary as well as appropriate one has to be chosen. Row index number-In it number is shown as the row sums up and the numbering is done as first row is equal to 1. [Range_ lookup]-As there are two different sets within a same table that is correct and incorrect in it these aspects are included. Detailed examination of the Look up function with the context of the superstore sale in an appropriate manner- With the help of same Microsoft Excel sheet various steps can be taken which are discussed below in detail- Lookup Value-A row or column can take input that is the question and performs results that is answer of that question after analysis all aspects in detail. For time of request, selling, and revenue use of Cell G2, H2 and I2. G3, H3 and I3 can be obtained. Pick the Lookup feature and set the cell H3; using the Lookup key as G3 cell. Table series-Choose from A2 to C8400 (A2:C8400) for the whole set. [Range_ lookup]- Select cell to be purchased, B2 to B8400 (B2:B8400). Graphs and Charts-There are different steps that are involved in it that are discussed below- Step1- Pick a cell so as to prepare a line graph appropriately Step2- Chose a line graph that is required for visibility.
From the above it can be seen that sales and subsequently profits of firm was maximum in 2009 and after that period it had remained almost constant up to an extent. Though there are some years in which the company was in loss which affected its working very badly. PART 2 2.1 By using audidealership.csv that was provided in conjunction with Weka gives a specific example of clustering === Run information === Scheme-weka.clusterers.EM -I 100 -N -1 -X 10 -max -1 -ll-cv 1.0E-6 -ll-iter 1.0E-6 -M 1.0E-6 - K 10 -num-slots 1 -S 100 Relation-audidealership2 Instances-100 Attributes-8 Dealership Showroom Internet Search RS7
A4 TT Financing Purchase Test mode- evaluate on training data === Clustering model (full training set) === EM == Number of clusters selected by cross validation-3 Number of iterations performed-1 Cluster Attribute012 (0.34)(0.4) (0.26) ========================================= Dealership mean0.4816 0.5603 0.5847 std. dev.0.4997 0.4963 0.4928 Showroom mean0.9983 0.51360.368 std. dev.0.0409 0.4998 0.4823 Internet Search mean0.3044 0.4358 0.4306 std. dev.0.4601 0.4959 0.4952
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RS7 mean0.00080.886 0.6673 std. dev.0.0281 0.3178 0.4712 A4 mean0.9105 0.3434 0.4004 std. dev.0.2854 0.47480.49 TT mean0.6736 0.4823 0.3003 std. dev.0.4689 0.4997 0.4584 Financing mean0.5143 0.9489 0.1674 std. dev.0.4998 0.2202 0.3733 Purchase mean0.2751 0.7113 0.0001 std. dev.0.4466 0.4532 0.0084 Time taken to build model (full training data)-0.34 seconds === Model and evaluation on training set === Clustered Instances 034 (34%) 128 (28%) 238 (38%)
Log likelihood--2.19141 Result-From the above screenshot that is pasted it can be seen that Audi is 52 percent and 48 percent that uses base of 10 and thus it exposes the features that are strong points in the company. Though there are many features that are inter related with each other but its customer purchase choice doesn’t affects the variables of the organisation(Moyo and Loock, 2018). 2.2 Detailed explanation as well as evaluation of the methods of common data mining that can be used in the business relating with real examples that are prevailing in the market There are a number of methods that are commonly used as data mining and all of them are described in detail below-
Data mining technique-It is a technique that is old, tried, as well as tested as it gives maximum results and that to in positive aspect to each and every firm that uses it in an appropriate manner. It includes various other factors too like classification analysis, learning of associate rules, detection of anomaly or outlier, analysis of different types of clusters, regression analysis, etc. and thus it carriers a lot of value in the current market situation. There are three major steps that are needed in this technique and all of them are analysed below briefly- Exploration-In this step data is transformed and cleared so as to measure the results in an effective and efficient way(Mumtaz and Ashraf, 2017). Pattern Recognition- This step includes the recognition of the strongest pattern that will help in establishing a good market value and that too in long term. Deployment-This step involves production of appropriate effects so as to determine trends that can be used precisely. Data mining technique-It is one of the most important perspective as application of a correct as well as useful data mining techniques becomes a necessity for each firm that wants to grow and expand in the market and it is also very useful in building long term sustainability. As it is a wider concept and includes many things but majorly involves six most common used techniques by firms that are evaluated below in detail- Statistical Techniques-These are techniques that are involved in data mining method and is regarded as one of the most important aspect as it is related with the statistical data that is regarded as the most essential as well as integral part of each and every organisation that is operating in the market. There are differentissues that are related with it so as to analyse the future prospects which will help the business to grow and these are- What is the trend of data network? For how many occasions it can occur? What are the patterns that possess a lot of value for the company? What is a high-level description of the things that are found in the document? Clustering Techniques-It is a technique in which certain groups are formed according to a similarity and then subsequent clusters are formed so that analysis and evaluation can be done quickly as well as in a systematic manner(Pahl and Voß, 2020). There are various different methods that are involved in it and they are explained below-
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Hierarchical agglomerative methods Grid based methods Model based methods Division methods Density based methods View-It is regarded as one of the best way as it is related with imaging a situation that has a great possibility of happening and after that a detailed study can be done on that which would result in high level of success rate in the market as compared to other competitors that are prevailing in the similar industry. Trend analysis is mainly done in it so as to make necessary arrangements for the future prospects(Riker Jr, 2019). Induction Decision Tree Technique-It is a technique in which a tree like structure is formed and on the basis of it different evaluations are done so that all the aspects can be studied in detailed making it a much better technique as compared to others that only focuses on a single factor. It can be also used as pre-processing as it is closely related with it. NeuralNetwork-Itisatechniquewhichinvolveshumanbeingsandartificial intelligence technology is also used in depth in this factor as well as it involves certain things that are described below- How does nodes are linked in it? What will be the production units and its amount? When the training will complete? Association Rule Technique-It is a technique that involves two aspects that are associated with each other in some or the other aspect and analysis and evaluation of those factors are included in this technique(Stepashko, 2017). 2.3 Detailed analysis and evaluation of Advantages as well as disadvantages of Weka over Microsoft Excel Weka is an open sources code that proves beneficial in evaluating the artificial intelligence technology and also involves gaining of various types of knowledge in it too. It involves a UNIX interface and a GUI Explorer. Advantages and disadvantages of it are explained below in detail-
Advantages of Weka over Microsoft Excel-As it is a compilation of different aspects that are related with advanced technology and also allows submission of pictures and its editing in a quicker as well as better manner which MS Excel lacks. Disadvantages of Weka over Microsoft Excel-Weka involves use of high technology which at times is not feasible for all the firms that are operating in the market while it is very easy to operated Microsoft Excel(Wangoo, 2018). CONCLUSION From the above it can be concluded that Microsoft Excel is of high importance as it helps the business in its operations and that too in a systematic as well as precise manner that proves beneficial for the firm in increasing and improving its market value in the industry in which it operates. Though there are some disadvantages of it too but its advantages outnumber them by a huge margin.
REFERENCES Books and journals Boyles, M., 2019.The Affect and Limitations of Business Intelligence in the Fast-Food Restaurant Industry(Doctoral dissertation, Capella University). Fatima, A. and Linnes, C., 2019. The Current Status of Business Intelligence: A Systematic Literature Review. Fernández-Manzano, E. P., Neira, E. and Clares-Gavilán, J., 2016. Data management in audiovisual business: Netflix as a case study.El profesional de la información (EPI). 25(4). pp.568-576. Kumar, A., 2018. Implementation core Business Intelligence System using modern IT Development Practices (Agile & DevOps).International Journal of Management, IT and Engineering.8(9). pp.444-464. Moyo, M. and Loock, M., 2018, August. Small and Medium-Sized Enterprises’ Understanding of Security Evaluation of Cloud-Based Business Intelligence Systems and Its Challenges. InInternational Information Security Conference(pp. 133-148). Springer, Cham. Mumtaz, I. and Ashraf, A., 2017. A SURVEY BASED RESEARCH FOR BUSINESS INTELLIGENCE INTEGRATION WITH KNOWLEDGE MANAGEMENT.Science International.29(2). pp.351-351. Pahl, J. and Voß, S., 2020. Introduction to the Minitrack on Intelligent Decision Support and Big Data for Logistics and Supply Chain Management. Riker Jr, R. W., 2019.End-User Computing Satisfaction and System Use on Business Intelligence End-User Performance(Doctoral dissertation, Capella University). Stepashko, V., 2017, September. Developments and prospects of GMDH-based inductive modeling. InConference on Computer Science and Information Technologies(pp. 474- 491). Springer, Cham. Wangoo, D. P., 2018, December. Artificial intelligence techniques in software engineering for automated software reuse and design. In2018 4th International Conference on Computing Communication and Automation (ICCCA)(pp. 1-4). IEEE.