Final Project
zmassad
assignmentnew4.docxRunning head: NETWORK AND WORKFLOW 1
NETWORK AND WORKFLOW 8
Network and Workflow for a Data Analytics Company on sports
Student Name Nezar Al Massad
Institution Name Dr. Mark O'Connell
Network and Workflow
In most work organizations a representation of the actual work in terms of duties assigned, organization of staff, timeline required for the work to be done, operations sequence, projects and teams assigned to them are some of the reasons why a workflow is required. Because it represents the real work to be done, a workflow can be defined as a document, a service or a product that directs one from a step to another. It may contain a model or design that is used as a guide with a recurring form. A data analytic company is a company that carries out the process of inspection, cleansing, transforming and modeling data so as to identify, detect or discover insights that can improve performance. As stated by Rishabi (2018) in his article on data analytics product, Blocklysis, the analytics domain is expanding and bringing up new concepts and ideology, meaning that many processes have been automated into algorithms revealing trends and metrics that would otherwise not be easily identified, because of that my company was inspired to use the dataflow diagram to enhance workflow.
A data flow diagram is a diagram that provides a way of data representation,( Robert Klanten and Sven Ehmann 2010) showing the flow of data in an information system majorly, and provides information about the outputs, inputs of entities and the process itself and maps flow of information. Following the structured design, (Ed Yourdon Larry Constatine, 1976), data flow graph. A data flow diagram (DFD), uses symbols such as arrows or dataflow lines, lozenge shapes, rectangles, circles and short text labels to show a simple array of data and the direction to which the data is flowing to or from that is the inputs and outputs. Based on the data flow graph computation models (David and Gerald, 1978) the ideology of the design concept occurred majorly in the software field and the lucid chart implemented it and was applied in business analysis more than other fields.
My company, being a data analytic company has also implemented the lucid chart to show the flow of information from our customers. Like any other good data flow diagram, my company’s is easy to comprehend and obvious to anyone, and it is perfect for review with every other stakeholder in the company with no technical experience.
My company is an online sales company, dealing with supply of products at affordable prices to consumers wherever they are. The consumers first have to log in to the website with login details they have been registered with. After the log in, they are given access to all the products of their choosing, from cosmetics, to kitchen wear, to office equipment, all in different sizes, shapes, colors and prices. Then they select an item of their choosing, and make a purchase. The payments are done through mobile banking transaction, deposited to our account and delivery is done within twenty four hours after the purchase is made depending on the location of our consumers. The workflow diagram, shows the flow from our consumers to our database systems for new and current customers.
Designing a DFD for my company includes having the correct processes which it operates on, thus different levels. Like the workflow diagram, the DFD shows the flow of information within the databases in the system. Using Salesforce as one of the external data sources for payments made, orders made by consumers, received from producers and the total count of products with their descriptions. Other data sources we use are MS access and MS excel. The next diagram shows the data flow diagram of my company.
( New Customer ) ( Process new customer information )Workflow Diagram
( No ) ( Yes ) ( Customer login )
( Payment Confirmation ) ( Payment Received ) ( Process Order ) ( Item shipped to customer ) ( Payment Not Received ) ( End ) ( Place Order Into the system ) ( Place order into system ) ( Current Customer )
From the workflow above, there are different shapes representing different processes. The rectangle shape represents an external source or system that is like a human factor that interacts with my system processes. This entity which intakes inputs or outputs is an interface for data collection. The customer and login information are the processes done by the customers. They key in their details, that is username and password that had been given to them on the first encounter with the online site. When a customer is new to the site, new information about them is added to the system when they add their details, create a username and a password that only they can access. Once that is done, a customer is free to place an order of their choice, then make a payment. After the payment is made, our accountants receive a notification of the payment, then the order is processed and the deliveries made to the nearest towns our customers are situated at. This ensures that the company has a close contact with customers virtually, thus we are able to know their grievances, likes, dislikes and what they would like for us to improve in the future. They also have opportunities to select products of their liking and also suggest other products they require.
( Model ) ( Reports )Dataflow Diagram
( Salesforce (dataset) )
( Model Creation ) ( Model Validation ) ( Data Augmentation and partitioning ) ( Data Parts ) ( Aggregation ) ( Clean Data ) ( Data Cleaning )
From the dataflow diagram, the shapes describe the entities and relationships between the entities. This takes place in the system and does not involve an outward process. Once the products are processed, ordered and delivered, information about them is stored in Salesforce. Salesforce gives a detailed information about the products and their specifications, what they can or cannot do. The producers also send invoices of the products to Salesforce creating a need for data aggregation or sorting. Before data is sort, it has to be cleaned first so as to make the end process of analysis and model making easy. The cleaning part involves removing duplicates, that could include products whose descriptions have been repeated more than once or product names. Also, cleaning involves deleting of missing variables from a dataset, manually adding information that had not been captured by the systems before. Once data has been cleaned, the clean data is used to give reports before analysis, and the data is stored for future reference, after the data is aggregated. After data is augmented, the analysis process begins and the data is segmented. The data managers send the clean and augmented data to the data analysts. The data management system begins here. Data management falls under the rubric of project management. Most researchers are unprepared for data management, since it tends to be underemphasized in training programs. A data analytical project is not unlike running a business project with one crucial difference, the project has a fixed life span. This difference will affect many aspects of its management. Some areas of management that are affected are hiring, firing, evaluation, organization, productivity, morale, communication, ethics, budget, and project termination. Although the production of a data management challenges, if the proposal is approved and funds allocated, the accomplishments of the project are dependent more upon its management than any other factor.
The purpose of the data management system is to ensure high quality data, that is, to ensure that the variability in the data derives from the data collection process, and accurate, appropriate, and defensible analysis and interpretation of the data. Once the data analysis is done the model is made in form of graphs, boxplots, pie charts and many others. There are many graphical packages available that provide the ability to plot, view, and to an extent analyze data. Graphical representations of data are extremely useful throughout the examination of the data. Statisticians are often familiar with these techniques for examining the data, describing data, and evaluating statistical tests (e.g. plots of residuals). The visual impact of a graph is informative and will increase the understanding of the data and limit the surprises that may occur.
These flow diagrams help in showing the processes of the programs taking place in the company, and helps in planning and stocking of future products, determining which ones are mostly purchased and identifying new market gaps for other products. Thus, the DFDs are a very efficient way of algorithmic and system running, because they help in growing business and identifying things that cannot be noticed without them. Thus the application of dataflow and workflow diagrams improves the working environment, adjusts the process of buying and selling without having to meet the buyer or the customer.
References
Edward, Y., & Constatine L.L,(1979). Structured Design, Published by Yourdon Press
Behrouz, F., (2017).Data Communication and Networking, Published by McGraw Hill Education
Robert, .K, & Sven,E., (2010). DataFlow2;Visualizing information in graphic design, Published by Gestalten
