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    Data Handling And Business Intelligence

    Introduction to Data Handling

    Data handling is the most important task under which business organize all information and interpret the same for the purpose of extracting valid outcome. Business intelligence is another important aspect under which company shed light upon collecting valid data and drawing valid outcome of the same. It is because collected data are analyzed in the light of aim and objectives of business. Present report is based on case study of Audi dealership data under which Weka software has been applied. It would be effective to apply suitable software and draw valid outcome from the collected information. In addition to this, advantages and disadvantages of Excel for data analysis has also been explained. Moreover, pros and cons and Weka are explained stated clearly to meet research objectives. All these software are required for data analysis as it is important to take appropriate decision regarding selection of suitable strategy to improve business performance.

    As per the collected information, it has been found that sales turnover as well as profitability of business is going down. The main reason behind decrease flow of sales turnover is inappropriate implementation of discounting strategy. Here, the main reason was related to discount on new as well as old product in the same proportion. It affects purchase decision of consumers and accordingly sales turnover of firm get affected (Psenka and et. al., 2015). Owing to this, management of business focuses upon delivering good quality of services to large number of buyers by offering them particular percentage of discount. It can be critically evaluated that same proportion of discount on products offered by Superstore. However, some of the products has very higher prices but discount but margin of profit is very low on the same. It shows that company is selling its product on very higher prices but not generating significant earning in the form of retained profit. It can directly affect flow of production and rate of return of business also get affected (Kumar, 2014). Apart from this, some product are sold at very low price but higher margin is earned on the same. It is showing that less valid impact of discount strategies on varied products. Here, example of deliver truck can be taken which has profitability of .59 but sales generated by the same is 5472. Similarly, another item with 2484 ID number has profitability of .77 whereas sales price of same items is 1810.

    Thus, it can be analyzed that all products which are sold at lower price tend to generate higher margin or rate of return. It can be critically evaluated that Superstore does not have appropriate strategy related to pricing and discount. It is the main reason behind varying margin on different products and services for a business. This shows that management or respective department of Superstore must shed light on discount strategy, price and profit margin for bringing appropriate balance and catering requirement of different parties. In this manner, two factors are discovered such as discount and variation of sales and profitability. It reflects that strategies related to discount and pricing should be changed so as to meet the long a well as short term objectives of Superstore (Lausen, Seidel and Ultsch, 2010). It aids to increase overall rate of return and deliver good quality of services to large number of buyers. Moreover, management should lay emphasis of maintaining difference between margin of profit and sales turnover.

    In addition to this, the main issue is related to identical discount on varied price of products and services. It assists management to change pricing strategies for meeting expectations of stakeholders. Here, product with row ID 103 has value worth 2781 whereas discount on related product was .07. On the contrary, items of row ID 107 has quoted price worth 228 along with discount value of .07. Here, it can be seen that both products has significant difference of price but discount offered on them is exact matched. At this juncture, possible solution can be applied for taking corrective step which tend to determine success operation of business in the marketplace (Işık, Jones and Sidorova, 2013). It can be critically evaluated that all products offered by Superstore are different from each other which must not be discounted on the same percentage as it would decrease overall rate of return in the marketplace. Though, sales value of all products are also difference which cannot be offered on same kind of strategy adopted by corp;oration. It is the main reason behind low rate of return and poor sales turnover of business.

    So, the basic focus can be laid on amendments in discount strategy through which firm can easily recover its cost of production and retain buyers for longer time span. However, some product which has low sales price and even when they are offered at discount then rate of return will be decreased to a great extent. For this purpose, it becomes necessary to modify discount strategy for products with higher price and those with lower price. Apart from this, performance of Superstore can be managed by updating current strategies time to time (Vossen, 2014). It facilitates to allocate all resources on different activities effectively and meet the objectives of business in an effective manner. Therefore, skilled and competent workforce should be assigned to complete the task related to setting appropriate discount strategy.

    Advantages and disadvantage of using excel for data analysis

    Excel is considered as the most important aspect or manual technique to calculate figures related to profit and loss as well as cost of the business. Under this, different kind of data are processed and presented in an effectual manner. By using excel manual calculation can be done easily. Furthermore, advantages of using excel are explained as follows-

    Ease to create data collection tools-There are several tools for creating and collecting data under excel sheet. Here, management of Superstore can cut and paste all information in sheet in order to draw valid outcome (Shmueli, Patel and Bruce, 2016). It is because researcher does not require to learn any new language as excel can be operated with simple and normal aspects. Apart from this, some specific data set make it possible to form the locked fields and restrict entry of new data. It enables companies to analyze collected data in a most effective manner.

    Easy form of charts-Excel is considered as the most effective tool for the purpose of creating charts and presenting valid outcome to reach at the aim of the business. Here, different kind of functions are used such as “IF”, PIVOT table and LOOKUP. These all functions can be used for analysis of collected data and representation of the same for accomplishing set aim and objectives of business (Laverty, 2016).

    Templates can be used to aggregate data-Here, pre-defined data can be copied in excel sheet and then rest of the calculation can be done for the purpose of accomplishing the aim of the business. It would be effective to apply formulas to extract valid outcome so as to analyze the collected data in an effectual manner (Demirkan and Delen, 2013).

    Cons of using excel sheet

    There are several benefits associated with excel sheet but some disadvantage are also there which must be focused by business. Although, cons can be removed by taking corrective steps on right time. At the same time, equal focus can be laid on management side for taking care of below listed aspects. It covers follow listed cons-

    Typical learning curve-Learning curve of excel sheet remain less flexible because it cannot be understood by anybody easily. However, all calculation can be done easily but interpretation of the same need strong knowledge of the same field among individual doing it.

    Calculation error-Normally excel bring-forth valid outcome on the basis of entered data and input. It can be critically evaluated that human error or wrong data entry affect entire output of the data series. However, manual errors can be detected and the same create issue for entire business to a great extent (Katal, Wazid and Goudar, 2013). For example if data of two years are entered wrong then in the same manner overall output of study will be wrong. Thus, manual errors can be controlled and affect the output of study to a great extent.

    Time consuming-Generally data entry task in excel is manual which takes extensive time of researcher. It affect overall procedure of data analysis and completion of data collection procedure. However, delay in data analysis procedure affect overall performance of business to a great extent. For example manual enter data related to sales and profit tend to consume extensive time and accordingly this procedure delay the marketing and other related activities of business (Rausch, Sheta and Ayesh, 2013).

    Cost of entry-The cost of data entry can be either low or no cost alternatives. This tends to have direct impact on cost structure of business. Owing to this, business can focus upon reducing cost of production and applying suitable strategy to increase performance of business in the marketplace.

    Large set of data cannot be managed in excel as it generally contain approximate 3000-4000 rows.


    Audi dealership data

    a.i. J48 algorithms

    Generally specific algorithms is used in order to represent the data and value for taking appropriate decision in context of business. With the help of algorithms overall process is applied for understanding level of individual in order to accomplish the purpose of Audi dealership. It is because collected data are analyzed for drawing valid outcome. Here, J48 algorithms applied for anticipation of reason behind low sales turnover of business. Here, company can shed light upon target variables whereby appropriate outcome can be extracted so as to meet the objectives of business in an effectual manner. Apart from this, decision tree is used to represent the predicted information (Vera-Baquero, Colomo-Palacios and Molloy, 2013). At this juncture, collected data are processed and then analyzed in the light of aim and objectives of company. Moreover, decision tree is prepared in accordance with collected and analyzed data. Here, a person using or applying this particular software will significant updation in existing knowledge.

    It started with 0 as the initial stage under which 810 is divided by 375. Here, possibilities of taking purchase decision as well as frequency of the same is analyzed. Here, it can be interpreted that buyers who purchased Audi car before 2005 will not get benefit of extended warranties as they are initiated later on. Similarly, those with first purchase decision can easily get the advantage of extended warranties. It would be effective for them to get additional benefits out of the new procedures of company. It is showing that results obtained from both options are different and accordingly management of Audi can effectively take decision. It has been found that with the help of one option customer is not getting advantage of latest facilities whereas other option is useful for its potential buyers (Wu and et. al.,2014). It aids to retain them for longer time span and meet their expectations in an effectual manner.

    a.ii. SimpleKmeans

    At this juncture, focus is laid on set of different variables which are responsible behind decreasing sales turnover of Audi. However, the main motive of business is the increase sales turnover and enhance overall profitability in the marketplace. In the same manner, above graph or cluster analysis is reflecting four clusters which are presented through structured process. It can be critically evaluated that above mentioned graph shows larger group of values on right side in comparison to the opposite side. Therefore, both variables are close to each other and all presented valued are correlated to each other. In this manner, final outcome reflects that corporation can easily increase its sales turnover by raising finance for customers. At this juncture, cluster analysis is showing relationship between variables by grouping data together whereby positive changes can be brought in revenue as well as sales turnover.

    Modifying the existing data level

    The current task was related to appropriate management of larger data set for accomplishing specific purpose of researcher. However, business can bring suitable or necessary changes in its internal structure so that accordingly long as well as short term objectives can be accomplished. However, Weka software can be use to handle the situation of managing large data series. At the same time, chances of accuracy also increases for accomplishment of set targets and objectives.

    Advantages and disadvantage of using Weka for data analysis

    Weka is the most popular software among businesses because of its uniqueness and strengths. It facilitates to support different stakeholders in getting information on varied departments of business. However, currently businesses use different new aspects and features of updated tools and technologies for collecting as well as analyzing the information. The popularity of Weka exist because of management of complex data series in a very convenient manner. However, it is superior than excel because it work upon weaknesses of manual mining of data. For example, in using Excel companies face issue for managing large data series. At the same time, chances of manual errors is also higher which can be controlled by using Weka. It does not work in SAS and R language where coding of data become very easy for the purpose of analysis (Demirkan and Delen, 2013). Though, coding is also not complex and decision tree is formed in a successful manner. It relies on automatic calculation through which tough and emergency condition can be tackled effectively. In addition to this, Weka tend to rectify problems faced during data entry and analysis of the same for producing valid outcome.

    Advantages of using Weka

    • It is more better than Excel whereby complex data series can be handled in more effective manner.
    • Weka software input the data related to sales and profit without any kind of manual errors.
    • Selection of data and algorithms procedure are completed automatically for getting output
    • It helps to protect all input or data inserted without any kind of risk of crashing like excel sheet (Psenka and et. al., 2015).
    • Weka maks use of varied statistical tools for extracting valid information related to business
    • Decision tree is formed by working upon set of identical variables at a time.
    • Generally outcome generated by Weka tend to be more accurate with saving of time.
    • Weka is totally worked on the basis of Java programming language for ease of users and full protection of data set.
    • It is considered as portable and independent platform for data mining and handling.
    • It makes use of graphical user interface whereby system can be accessed easily.
    • Weka has large collection of different kind of data mining series.

    Disadvantages of using Weka

    • One must possess sufficient knowledge to use Weka and apply the same in organization context for meeting specific objectives related to data mining
    • Weka generally perform statistical calculation whereas Excel has command on both non-statistical measures as well as statistical one.
    • Some manual errors like wrong programning or wrong input tend to produce less reliable results which misleads decision of business
    • Generally Weka switch the interest of users or business on anther issue rather than focusing upon current solution of firm.

    The collected information reflects that Weka has gained competitive edge over other related tools whereby it becomes easy to handle large data set with application of statistical tools. It can be critically evaluated that company or expert must have experience of Java programming language so as to resolve the solution which is being faced by business. At the same time. management must shed light upon favorable aspects of Weka to resolve potential issues which are being faced by business (Wu and et. al., 2014). It enables them to ensure good working condition and retain buyers for longer time span as effective decisions are taken on the basis of decision tree. Hence, ti can be said that, Weka has edge over excel which generally take extensive time and might be irrelevant at certain point of time. Owing to this, Weka software is used by Superstore and Audi to mine and handle data in a more effective manner. This tends to ensure well being of business in the marketplace.

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    The aforementioned report concludes that application of different types of software facilitate to analyze the collected data related to sales and profit. It would be effective for management to have control on its business activities by taking suitable actions. It can also be concluded that Weka has advantages over other related tools which prove to be effective for the purpose of taking right decision and analyzing the collected data in most effective manner. Apart from this, Microsoft excel might be ineffective at certain point of time due to manual errors.


    • Demirkan, H. and Delen, D., 2013. Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud.Decision Support Systems. 55(1). pp.412-421.
    • Işık, Ö., Jones, M.C. and Sidorova, A., 2013. Business intelligence success: The roles of BI capabilities and decision environments.Information & Management. 50(1). pp.13-23.
    • Katal, A., Wazid, M. and Goudar, R.H., 2013, August. Big data: issues, challenges, tools and good practices. InContemporary Computing (IC3). 2013 Sixth International Conference on(pp. 404-409). IEEE.
    • Rausch, P., Sheta, A.F. and Ayesh, A. eds., 2013.Business intelligence and performance management: theory, systems and industrial applications. Springer Science & Business Media.
    • Shmueli, G., Patel, N.R. and Bruce, P.C., 2016.Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner. John Wiley & Sons.
    • Vera-Baquero, A., Colomo-Palacios, R. and Molloy, O., 2013. Business process analytics using a big data approach.IT Professional. 15(6). pp.29-35.
    • Vossen, G., 2014. Big data as the new enabler in business and other intelligence.Vietnam Journal of Computer Science. 1(1). pp.3-14.
    • Wu, X., Zhu, X., Wu, G.Q. and Ding, W., 2014. Data mining with big data.IEEE transactions on knowledge and data engineering. 26(1). pp.97-107.

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