An approach for forecast prediction in data analytics field by tableau software

Published Online January 2019 in MECS

• II.    Literature Survey

Tableau presently has the largest customer domain. When businesses organization are focusing for a BI solution, it’s always their first choice. In the below section the paper has described different BI tools that are currently used in the business market for enhancing the business strategy. Sisense is one of the leaders in the market of BI and a winner of the Best Business Intelligence Software Award given by Finances Online [3][4], It was considered as one of the most adopted business, software review platforms. The users of this tool will also enjoy effectively by using the in-chip technology in a database that operates the data much more faste than the existing traditional systems. BIRT project is a flexible, Standalone, and 100% pure Java reporting tool for creating and presenting reports in opposition to data sources varying from typical business relational databases, to XML data sources, to in-memory Java objects. It is originated as a top-level project integrating with the Eclipse Foundation. Similarly icCube is a SaaS end to end BI platform, particularly to be ingrained in to the developed application[5][6]. It amalgamates smoothly with any application due to on-the-fly-authentication and authorization ability. icCube can be treated as a dream for any software developer who wants to present predicated dashboards or a solid web based self service BI solution, to their end-users. It is not Cost effective. Business Optimization Software Domos imports together the customers, the data, and the acumen business users demand to present a detailed view of what’s happening in the organization[7][8]. The Jaspersoft Business Intelligence Suite provides different ways for end customers to initiate interactive analysis. In the case of casual user, this might include simply changing a filter setting on a report to present various slice of data.This tool is generally helpful for data analyst to writing powerful, multi-dimensional expressions. Microsoft also provides Business Intelligence platform comprises of Analysis Services, Integration Services, Master Data Services, Reporting Services, and several client applications used for initiating or operating with analytical data. But this software is not able to make the dashboard attractive like other BI tools. This data is often travelled across various databases in multiple locations with different versions of database software. .Pentaho platform provides an easier way for preparing and blending any data and adds a spectrum of tools to easily analyze, visualize, explore, report and predict[9]. In the above section the paper has discussed some business intelligence tools which are earlier used for the business intelligence and business analysis processes. In the next section the paper has described how tableau is helpful for business intelligence and analysis purpose which plays an important role for decision making processes in the organisation.

• III.    Tool Study

Tableau prepared its mark on the Field of BI by being one of the first companies to permit business customers the ability to achieve equitably arduous data visualization in a very interesting, drag and drop manner. Tableau’s data virtualization is head and shoulders above what traditional BI vendors offer[10]. Tableau occupied its mark on the world of BI by being one of the first companies to give business customers the ability to operate fairly complex data visualization in a very intuitive, drag and drop manner. In this platform visualization and analysis can be done without having proper knowledge in programming domain, The output analyzed results can be shown in an effective manner. In the below section the paper has described the how smoothly the forecasting process can be done by tableau tool by taking a business test case. Tableau clearly and beautifully visualizes your data. Tableau has the functionality to present reports on supreme large sets of data without enormously affecting network performance. someone can easily go from novice to expert level with proper assistance through this tool.

• IV.    Implementation

This section describes how the data is processed in tableau platform and how forecasting can be done with the collected dataset. The data which are collected for processing are from a sample store present in USA which comprises of different attributes or fields , In the below figure describes the excel format of data that is taken for processing in tableau platform. There are multiple ways to import the data set in tableau software, One of the biggest leverage of tableau software is, it allows the user to import the data in portable document format and perform different data analytic operation by utilizing the data. Tableau’s data virtualization is leader and shoulders above what conventional BI vendors offer. Tableau done its mark on the world of BI by being one of the first companies to give business users the propensity to perform fairly complex data visualization in a very visceral drag and drop manner. Tableau assimilates with most data types and provides out of the box integration with a variety of big data platforms, comprising Hadoop. Tableau assimilates with R, the business intelligence statistical language many data scientists use to dive deep into BI for statistical and advanced analytics,

Tableau has a ample amount of partner and consultant base, as well as exhaustive online resources including guides, online training and forums. Plus, the Tableau community is well-known enthusiastic and engaging., Like most BI vendors, Tableau provides different software licensing options. There’s a nonpaid version of Tableau for personal use, but its scope is limited. To download Tableau to your desktop, you’ll pay in the range of $1000 and $2000 per year. Online or hosted access to Tableau costs $500 per person, per year. In the below paragraph the paper has described some cons of tableau server and tool

Hence, lot of organizations will need Tableau server. Based on what companies that have considered Tableau (or have purchased it) tell us, an entry-level server license is about $1000 per user (with a 10-user minimum). If data is in Excel or a CSV file format, you can upload it to Tableau and perform different data analytical operations Tableau occupied its mark on the world of BI by being one of the first companies to give business customers the ability to operate fairly complex data visualization in a very intuitive, drag and drop manner.. But, if you want to interact to a database, a developer skilled in SQL will have to create the SQL query to retrieve the dataset.

With the Tableau server, there is no term of versioning. You build your reports and dashboards through your desktop and then publish them to the server. Once they’re published, there’s no alternate way to retrieve previous versions- once you overwrite there’s no pulling back options is available. , In the below figure [1] describes the excel format of data that is taken for processing in tableau platform.

Fig.1. Original Data source in excel sheet

The below figure [2] describes the process of importing the original data source which is present in excel format to tableau-platform.

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Row ID       Order ID       Order Date          Order Priority          Order Quantity        Sales        Discount        Ship Mode          Profit        Unit Price

1             3 13-10-2010         Low                                  6     26154      0.040000 Regular Air            -213.25          38.94 1

49            293 01-10-2012          High                                    49   10,123.02       0.070000 Delivery Truck           457.81          208.1€

50            293 01-10-2012          High                                    27      244.57       0.010000 Regular Air               46.71            8.65

80            483 10-07-2011          High                                    30    4,965.76       0.080000 Regular Air            1,198.97          195.95

85            515 28-08-2010          Not Specified                            19      394 27       0.080000 Regular Air               30.94           21.7E

86            515 28-08-2010          Not Specified                            21      146.69       0.050000 Regular Air                4.43             6.64

97            613 17-06-2011          High                                    12       93.54       0.030000 Regular Air              -54.04            7.3C

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Fig.2. Importing data set in to tableau framework

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After successfully importing the data in to tableau platform the data is divided in to two parts the numeric data are generally come in to the measure section and rest other data come to the dimension section. This division of data is generally done by the tableau itself. The a division of data in to dimension and measure section which is done by tableau internally, In the below figure[3] and

Figure [4] the paper describes the data that is present on the original data source ,In the original data set profit and sale information about various, categories of products are present up to year 2017 and the paper has forecasted the profit and sale information on the forthcoming quarters of 2018.

Sheet 65

Sum of Profit for each Order Date Quarter broken down by Category and Order Date Year Color shows details about O-der Date Quarter.

Fig.3. Profit Data Retrieve From Tableau Tool

Fig 4.Sales Data retrieve from tableau tool

In the below section the paper has described the estimated profit of different categories of product in forthcoming quarters. In Figure [5] the estimated profit for Furniture Category for forthcoming quarters are calculated ,In similar manner Figure[ 6] provides the estimate calculation of technology category product and Figure [7] represents the estimated calculation Office supplies product category, In tableau the forecast calculation is done on the basis of import data .

FORECAST FOR FURNITURE CATEGORY

Sum of Profit (actual 8 forecast) for each Order Date Quarter broken down by Category and Order Date Year. Color shows details about Forecast indicator. The view is filtered on Category, which keeps Furniture.

Fig.5. Estimated Profit Calculation For Furniture Category

FORECAST FOR OFFICE SUPPLIES

CATEGORY

Sum of Profit (actual 8 forecast) for each Order Date Quarter broken down by Category and Order Date Year. Color shows details about Forecast indicator. The view is filtered on Category, which keeps Office Supplies.

Fig.7. Estimated Profit Calculation For Office Supplies Category

In the below section the paper has described the estimated Sales of different categories of product in forthcoming quarters. In Figure [8] the estimated sale for Furniture Category for forthcoming quarters are calculated ,In similar manner Figure[ 9] provides the estimate sale calculation of technology category product and Figure [10] represents the estimated sale calculation of Office supplies product category, In tableau the forecast calculation is done on the basis of currently available sales data of different quarters. .

FORECAST FORTECHNNOLOGY

CATEGORY

FORECAST FOR FURNITURE CATEGORY

Fig.8. Estimated Sale Calculation For Furniture Category

Fig.6. Estimated Profit Calculation For Technology Category

FORECAST FOR TECH N NOLOGY CATEGORY

Forecast indicator ■ Actual ■ Estimate

Fig.9. Estimated Sale Calculation For Technology Category

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Fig.10. Estimated Sale Calculation For Office Supplies Category

• V.    Conclusion

Due to the increased market competition and increased data management an era has reached that needs more optimization technique to analysis the data. Big data technologies such as HADOOP proposes a framework for processing the data parallel y and after processing the data different visualization tools are used for representing the analyzed result in an effective manner which plays an important for decision making process in different business organizations[11]. Tableau will enhance decision making, add operational awareness, and increase performance throughout the organization[12]. The presented paper describes different tools used for business intelligence field and provides a depth knowledge regarding the tableau tool. Data visualization plays an important role for the business analytics in order to do different operation with data. Tableau analytics is one of the easiest and most powerful analytics tools today’s era[13]. Tableau can assist to assemble sense of different types of data coming in from multiple sources and blend it into one unique platform so that everybody can make sense of it and utilize it[14].The Tableau Dashboard is an important feature of the Tableau Product that lets you allow to create unique data stories, It is constructed from the ground up for people who do not have any technical skills or coding experience for that matter. So anything can be done by anybody without any prior set of skills. This paper has explained the forecast methodologies in tableau framework and practically done the forecast by taking the dataset from business domain. There are many various types of visualization options available in Tableau which enhance the user experience. Also, Tableau is very easy to learn compared to Python, Business Objects and Domo, anyone without having knowledge of coding can easily learn Tableau. Tableau can operate millions of rows of data with ease. Various types of visualization can be initiated with a huge amount of data without impacting the performance of the dashboards. Also, there is an option available in Tableau where the user can make and can “live” to connections to different data sources like SQL etc and can perform multiple data manipulation operation [16] with the live data. Tableau Dashboard has a marvellous reporting feature that allows you to create personalize dashboard specifically for a convinced device such as a mobile phone or laptop. Tableau automatically figure out which device is the user is viewing the report on and do adjustments to ensure that the right report is delivered to the right device.

Tableau has done a great job climb its way to the top of data visualization tools. So, Tableau has spent more than six years as a leader. However, with the increasing interest in data science, artificial intelligence, and machine learning, Tableau may be left behind if it doesn’t innovate quickly. Tableau does not support the aspect of automatic exhilarating of the reports with the help of scheduling. There is no other choice of scheduling in Tableau. Therefore, there is always some manual effort required when users need to update the data in the backend. Tableau is not entirely an open tool. Just like other tools like Power BI, developers can create custom visuals that can be easily imported Tableau. So, any new visuals need to be recreated instead of imported. Tableau’s parameters are constant and always unique value can be preferred using a parameter. Whenever the data gets changed, these parameters need to be updated manually every time.

• VI.    Future Scope

Tableau is strictly a visualization tool. Tableau Desktop only permits you to perform very basic preprocessing, Which includes joining and blending data[17]. Also, you have the competence to change data types. In an ideal world, most data would be exported in perfect tables. However, data cleansing is a necessary step. In most cases, an analyst needs to build a data model with reappearing to format the data. This needs a tool such as Altyrex, Power BI, Python or even Excel to operate data prior to loading[18]. In 2018, introduced their own data preparation tool called Tableau Prep, Different researches are going on for optimizing the execution time and reduce the elapsed time for performing data analytics operation in tableau platform.