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Data Processing in Running for Glory (RfG)

DataProcessing in Running for Glory (RfG)

DataProcessing in Running for Glory (RfG)

Thispaper explains the data processing steps that will be put in placefor the one-site running centric fitness store in Seattle, WA. Thestore under focus is Running for Glory. Even though the store hasremained true to its course, it has not kept abreast with theadvances in technology. This implies that the store has no muchinformation about its customers. With the technology in place forRfG, it cannot analyze the trends in customer demographics it cannotdevelop strategic plans for expansion or even take part in someserious discourse with the suppliers regarding the viability ofsourcing new products or even eliminating the existing products.

DataProcessing Steps

Dataprocessing refers to the conversion of raw data to information thathas meaning through a given process. During the process, there ismanipulation of data to produce results that help to solve a problemor even improve an existing situation(Alexandrov et al., 2014).

ElectronicData Processing

Giventhat there is a need for advances in technology, RfGs will adopt theelectronic data processing form. Through the method, computers willfacilitate processing of requirements. The computers will be in aposition to handle a large database of the demographic data as wellas data processing. The processing cycle will involve datacollection, preparation, input, processing, output, and storage(Alexandrovet al., 2014).

Inthe collection, the different data regarding the populationdemographics will be collected. The collection will be done asaccurate as possible to ensure that data collected is of highquality. Data will then be prepared. The process involvedmanipulation of data into a form that is appropriate for furtheranalysis and processing. Before processing, the data has to bechecked for accuracy(Kreinovich et al., 2013).The other process will entail the input of the data. Inputting thedata will entail verification of the data or conversion into a formthat can be read. Computers and the components will help inappropriate entry of data. The process has to follow a formal andstrict syntax when breaking down the complex data.

Thenext stage is processing of the data where it is subjected todifferent means and methods of manipulation. During this process,instructions that are specific to the needs of RfG are executed. Thecomputer processing of data will ensure that there is the fastexecution of data within a short time.

Thecycle proceeds to output and interpretation phase where informationprocessed is transmitted to the user. The output is presented indifferent forms and this case it will be the report for RfG. Theoutput produced will be one that can be interpreted. The report fromthis process will entail customer demographics and strategic plansfor expansion. The last process is storage, where the reportsgenerated, will be stored for future use. Storage will ensure thatdata can easily be accessed and retrieved when need arises(Kreinovichet al., 2013).

WhyUse the Electronic Data Processing?

Thereare several benefits of using the electronic data processing methods.Some of the methods include the speed, efficiency of the system,reduction in labor when operating the system, accuracy in the methodand reduction in the costs(Cugola &amp Margara, 2012).The retrieval of information can be done so fast, and management ofthe process happens in an easy way without any delay.

Eachof the steps of data processing is critical and skipping one of thesteps only means that the data processing procedure will be tamperedwith. The relevance of each step is innate in their functions.

Integrityof Data

First,I will ensure that data is coded appropriately. The data values alsohave to be standardized according to the data type of the data model.I will ensure that the features of the data are all correct. In thedatabase, I will ensure data integrity through authentication of dataand checking of error as well as validation of the routines. I willalso format the cells or columns appropriately to ensure that therequired format is only accepted. Numeric cells should not acceptalphabetic data(Hao Zhong &amp Yu, 2011).


Comparedto the manual systems, the electronic systems are expensive. Thesystem is also regulated and guided by ethical concerns hencemanipulation or tailor making some of the software to fit particularneeds may be cumbersome.

Inconclusion, the RfG should consider adopting the electronic dataprocessing if it is to remain relevant and competitive at the sametime. The system will present the RfG with the best opportunity toexpand and keep pace with technological advancements.


Alexandrov,A., Bergmann, R., Ewen, S., Freytag, J. C., Hueske, F., Heise, A.,… &amp Naumann, F. (2014). The Stratosphere platform for big dataanalytics.&nbspTheVLDB Journal,&nbsp23(6),939-964.

Cugola,G., &amp Margara, A. (2012). Processing flows of information: Fromdata stream to complex event processing.&nbspACMComputing Surveys (CSUR),&nbsp44(3),15.

Hao,Z., Zhong, S., &amp Yu, N. (2011). A privacy-preserving remote dataintegrity checking protocol with data dynamics and publicverifiability.&nbspIEEEtransactions on Knowledge and Data Engineering,&nbsp23(9),1432-1437.

Kreinovich,V., Lakeyev, A. V., Rohn, J., &amp Kahl, P. T. (2013).&nbspComputationalcomplexity and feasibility of data processing and intervalcomputations&nbsp(Vol.10). Springer Science &amp Business Media.