VIETNAM NATIONAL UNIVERSITY HO CHI MINH CITY UNIVERSITY OF INFORMATION TECHNOLOGY ADVANCED PROGRAM IN INFORMATION SYSTEMS CAP HUU ANH DUC- 17521295 BUILDING AN AUTOMATED WORKFLOW TOOL FOR BUSINESS DATA ANALYSIS IN RETAIL BACHELOR OF ENGINEERING IN INFORMATION SYSTEMS THESIS ADVISORS PH. DO TRONG HOP PH. TRAN VAN THANH HO CHI MINH CITY, 2024 ACKNOWLEDGEMENTS To complete this thesis, I would like to thank the teachers of the Department of Information Systems, University of Information Technology - Vietnam National University, Ho Chi Minh City for creating opportunities to study, practice and accumulate. Accumulate knowledge and skills to carry out the thesis. I would like to express my sincere gratitude to my advisors, Mr. Do Trong Hop and Mr. Tran Van Thanh, for their guidance and support throughout this research process. The teachers’ expertise, knowledge and patience are invaluable to me. Due to my limited knowledge and lack of practical experience, it is difficult to avoid shortcomings in the thesis content. I look forward to receiving comments and further teaching from you teachers. Finally, I would like to wish you good health and much success in your work. TABLE OF CONTENTS CHAPTER 1.-- ng ng krh 2 1.- Ăn HH HH HH HH 2 1. Objectives Of DTOJ€C(. LG SH TH ng HH ng 3 CHAPTER 2. Functional reQUIT€INTIES. cv HH ng rệt 5 2.ccSĂ kg nghiệt 5 2. Non-functional reQUIT€Tm€TIẨS. ANALYSIS AND DESIGN. Use-case Diagram.ccc SH HH key 7 3. Use-case specification and Activity điaøram. -- -«--«c+s<<sx+se+sers 13 “2. Get data ITSIBlI(. Ăn TH HH TH ng HH 18 3. Gà HH HH kg tr 29 3. Ăn TH TH HH HH Hy 37 3.- -- «+ HT ng rờ 48 as Fs MNS) 22 108 | . Get data InsIBl(.- Ăn HH TT HH TH ng HH Hy 49 3.- SH HT TH nh TH HH 50 3. Ăn HH TH TH HH ng 33 3. SH TH HH ng rưy 54 3. cv TH TH HH 55 3. Ăn HT HH TH HH HH, 55 2m". Entity Relationship Diagram (ERD) .-- 55 Sc St siseereeererere 56 CHAPTER 4.- HH HH HH gi, 57 4. Ăn TH HH Hư 57 “MA(( 2005. User interface develOpImehn[. Back-System develOpT€TI. Workflow US€ CAS€. HH TH HH HH ng Hệ 60 4.- SĂ LH HH HH ng kt 63 4. Workflow management page . Job manag€Im€in(.- --- 5 + + SH HH gi 64 CHAPTER 5. G9 HT HH HH ky 65 2. Ăn TH HH HH HH rờ 65 2. OTI€TẨA{IOTS. SG nTHgnHTHg hH nh grờ 66 I3 ›95)8I51 4501011175777. G7 LIST OF FIGURES Figure 3.- Ăn 1H TH HH HH ng 7 Figure 3. Detail use-case: Manage WOTkfÏOW.- -- Ăn HH re, 8 Figure 3. Detail use-case: Manage JOb. Detai use-case: Manage aCCOUITI. Signin activity 1aØTAI.G- G1 91v HH HH 15 Figure 3. Get data insight activity điaØTAm.- -- c vn g ere 17 Figure 3. Create workflow activity 1aØTATN.c cv re 20 Figure 3. Update workflow activity 1aðTATN. Run workflow activity đ1aØTAT. G1 HH ng rrt 26 Figure 3. Delete workflow activity đ1aØTa.- - c Scc + *kseeeereeeeeesre 28 Figure 3. Create account activity đ1aðTA1T. Update account activity (Ï1aðTA1T1. Delete account activity 1aØTATm. Schedule job activity đ1aØTa1m. Execute job activity d1aØTAIm.- c3 kg re43 Figure 3. Cancel job activity đ1aØTATm. Delete job activity đ1aðTAI. - óc 13kg nh Hy47 Figure 3. Signin sequence đ1aØTa1m.- -- -- << + 13 E11 1 1 vn trên48 Figure 3. Get data insight sequence điaØTa1m. Manage workflow sequence điaøTam. Create workflow sequence đ1aðTA1m. Update workflow sequence diagram. Delete workflow sequence điaðTa1m. Run workflow sequence (đÏ1aØT41m. Manage job sequence diagram . Manage account sequence d1aðTaTm.‹- s5 ss<sss+*sksseeeeeeseeers 54 Figure 3. Workflow state điaðTaIm.- 5 5 SH HH HH tiệt 55 Figure 3. Job state (1aØTATT.- - - - <1 TH HH nh 55 Figure 3. Directed Acyclic Oraphh. -- ---- -- + +1 vn ng ng trên 56 Figure 4. Export report to Dropbox . 5 2 + 31v ng trên 60 Figure 4. Send exported TÊDOYẨ. -- 5 «+ E1 E111 9 93 1 1n ng ng 561 Figure 4. Notify about new DFOdUC. Workflow management Page. cece seeseeseeeeceeeeseeseeeeseeseeaeeaeeneeees 562 Figure 4. Workflow detail page 0. cele cesecsceseceeceeeeeseseseecseesseenaessaeeseeeaes 562 Figure 4. Job management Page.-- - -- 5 + 31111191 vn ng ng nếp 562 LIST OF TABLES Table 3. List Of 4CẨOTS. G0011 ng nh TH Hi 11 Table 3. List Of USG-CAS€. - 2G G1 HH TH HH như 12 Table 3. Signin SD€CIẨICAfIOH.- c3 1E TH TH ngàng Hưng hư 14 Table 3. Get data insight SD€CIÍICAfION. SG 111v ve 17 Table 3. Create workflow SD€CIÍICAfIOT. -- G11 HH ng rg 19 Table 3. Update workflow SD€CIfICAfIOT. -- G1 1 1S HH ng ng 22 Table 3. Run workflow SD€CIẨICAfIOH.- 5 5 5 + vn nh HH g rưệt 25 Table 3. Delete Workflow SD€CIÍICAfIOT. -- S1 1S HH ng rệt 28 Table 3. Create account SD€CIÍICAfIOTI.c- 2c c0 2101193119111 119 11v kg ngư 30 Table 3. Update account SDeCIÍICAtIOTI. Delete account SD€CIÍICafIOTI. Schedule job s€pDCIẨICAfIOII. Execute job SD€CITICAfIOH1. --- 5 5 + 1v ng ng rưệt 42 Table 3. Cancel job sp€CIÍICAfIOII.---- c6 + 11H ng ng ưệt 45 Table 3. Delete Job SpeCIfICatION.--- c5 + 1v HH ng rưệt 46 ABSTRACT Data is an extremely valuable asset for retail stores in today's era of science and technology. Data helps retail stores better understand their customers, products and markets. From there, retail stores can make more informed business decisions, improve operational efficiency and compete in the market. The data management application for retail stores presented in this report is an effective solution to solve problems related to data processing and exploitation, helping retail stores manage data effectively. Introduction In the modern business landscape, data is an extremely valuable asset for retail stores. Data helps retail stores better understand their customers, products and markets. From there, retail stores can make more informed business decisions, improve operational efficiency and compete in the market. The data management application for retail stores presented in this report is an effective solution to help retail stores manage data effectively. This application provides the following functions: e Manage customer data, products, orders, .: The application helps retail stores store and manage all data related to their business activities completely and accurately. e Display data in charts: The application helps retail stores display data in an intuitive, easy-to-understand form. This makes it easier for retail stores to analyze data and make more informed business decisions. e Automate repetitive tasks: The application helps retail stores automate repetitive tasks, saving time and costs. e Customizable and scalable: The app can be customized to meet the specific needs of each retail store. In addition, the application is also scalable to meet the needs of retail stores of different sizes. Data management application for retail stores is an effective solution to help retail stores improve operational efficiency and compete in the market. Research problems Managing data effectively is a challenge for many retail stores. Retail stores often encounter the following problems: e Distributed data: Retail store data is often stored in many different places, such as in CRM, ERP, POS systems, etc. This makes accessing and managing data difficult. becomes difficult and expensive. e Confusing data: Retail store data is often stored in text or spreadsheet format. This makes data analysis difficult and time-consuming. e Lack of effective data analysis tools: Retail stores often lack effective data analysis tools to help them better understand their data. Based on the above issues, specific research issues for data management applications for retail stores include: e Effective data integration methods: How to effectively integrate data from many different sources into a single system? e Visual data display models: How to display data in a visual, easy-to- understand form? e Effective data analytics tools: How can we provide effective data analytics tools that help retail stores better understand their data? Additionally, specific research problems can also be identified based on the specific needs of retail stores. For example, one retail store may need to research how to use data to predict customer needs, while another retail store may need to research how to use data to Optimize your supply chain. Objectives of project In the scope of this project, the application targets two main goals: automation and management. Automation functions help the business data analysis process, save time and effort, improve the efficiency of business data analysis, leading to more informed business decisions. Management functions help retail stores better understand their customers, products and markets. From there, retail stores can make more informed business decisions, improve operational efficiency and compete in the market. Automation function The automation feature is one of the most important features of the system, which is the basis for implementing the system's features. Every automation process must include the following steps: e Schedule with trigger e Start e Execution e End The automation feature must allow users to configure automation process steps, schedule or event-driven automation processes, and track the status of automation Processes. Because business operations will constantly change, automation functions must be able to expand easily, with the ability to integrate additional external systems when necessary. In addition, because application users may not have a good background in technology, the user interface must be minimalist, easy to use, and easy to operate. Statistic function The statistical function must support a variety of chart types to display the most complete information possible to help users get an overview of the data. Non-functional requirements Scalability: The application must be scalable to meet growing user needs, such as the ability to add new features, handle more data. Reliability: Automated processes must be highly reliable, meaning they must operate accurately and without interruption. Performance: The app must have performance that meets user needs, such as fast response time, and the ability to handle large amounts of data. Security: The application must ensure safety and data security such as using encryption measures, user authentication. Usability: The app should be easy to use and learn, such as having a user- friendly interface, supporting online help. Supportability: The application must be well supported such as availability of documentation, phone or email support. Efficiency: Automated processes must be efficient, meaning they must complete tasks quickly and cost-effectively. Customizability: Automation processes must be customizable to meet the specific needs of the organization. User requirements: Non-functional requirements must meet user needs and expectations. Technical factors: Non-functional requirements must be technically feasible and consistent with the application's technology platform. ANALYSIS AND DESIGN 3. Use-case Diagram Manage account Manage workflow i Manage job Administrator Figure 3. General use-case Create workflow «extends ~ Edit workflow “ woes «extend» --~ ., “‘wextend» «extend» Figure 3. Detail use-case: Manage workflow Schedule job «extend TT Cancel job _ «exfefndbs“7“““ˆˆ ee Manage job =. “ae = ““eextends aoe Delete job «extends ` ` = ` * Execute job Figure 3. Detail use-case: Manage job Create account Manage account nesses «extend». Update account Figure 3. Detai use-case: Manage account 10 List of actors Actor Basic roles description Manage the system, have all of permissions in the 1 Administrator system Table 3. List of actors List of use-case Use case name Use case description Authenticate a user and grant them access to the 1 | Sign in system. 2 | Get data insight Explore data insights in the form of charts. Configure a workflow to meet the specific needs 3 | Manage workflow of their business. Define the steps and tasks required to complete a 4 | Create workflow business process. Make changes to a workflow to reflect changes in 5 | Update workflow business requirements or processes. Start a workflow and monitor its progress until it 6 | Run workflow is completed. Remove a workflow from the system or the 7 | Delete workflow database. Manage the lifecycle a job, from creation to 8 | Manage job completion.
Xây Dựng Công Cụ Tự Động Hóa Quy Trình Phân Tích Dữ Liệu Kinh Doanh Trong Ngành Bán Lẻ
Luận văn tốt nghiệp nghiên cứu tốt nghiệp building an automated workflow tool for business data analysis in retail, điều tra thực trạng, phân tích số liệu, đề xuất biện pháp cải
Trường đại học
Vietnam National University Ho Chi Minh CityChuyên ngành
Information SystemsNgười đăng
Ẩn danhThể loại
ThesisPhí lưu trữ
30 PointMục lục chi tiết
THÔNG TIN CHI TIẾT
Tác giả: Cap Huu Anh Duc
Người hướng dẫn: Ph. Do Trong Hop
Trường học: Vietnam National University Ho Chi Minh City
Chuyên ngành: Information Systems
Đề tài: Công Cụ Tự Động Hóa Quy Trình Phân Tích Dữ Liệu Kinh Doanh Trong Ngành Bán Lẻ
Loại tài liệu: Thesis
Năm xuất bản: 2024
Địa điểm: Ho Chi Minh City
Tài liệu có tiêu đề Công Cụ Tự Động Hóa Quy Trình Phân Tích Dữ Liệu Kinh Doanh Trong Ngành Bán Lẻ cung cấp cái nhìn sâu sắc về cách mà tự động hóa có thể cải thiện quy trình phân tích dữ liệu trong ngành bán lẻ. Tài liệu nhấn mạnh tầm quan trọng của việc sử dụng công nghệ để tối ưu hóa quy trình ra quyết định, từ đó giúp các doanh nghiệp nâng cao hiệu quả hoạt động và tăng cường khả năng cạnh tranh.
Độc giả sẽ tìm thấy nhiều lợi ích từ việc áp dụng các công cụ tự động hóa, bao gồm tiết kiệm thời gian, giảm thiểu sai sót và khả năng phân tích dữ liệu lớn một cách nhanh chóng và chính xác. Điều này không chỉ giúp doanh nghiệp nắm bắt xu hướng thị trường mà còn cải thiện trải nghiệm khách hàng.
Để mở rộng thêm kiến thức về chủ đề này, bạn có thể tham khảo tài liệu Nghiên cứu về big data và ứng dụng trong phân tích kinh doanh, nơi cung cấp cái nhìn sâu hơn về cách big data có thể được áp dụng trong phân tích kinh doanh. Ngoài ra, tài liệu Ứng dụng một số thuật toán phân cụm trong phân tích dữ liệu ngân hàng sẽ giúp bạn hiểu rõ hơn về các thuật toán phân tích dữ liệu có thể áp dụng trong lĩnh vực tài chính. Cuối cùng, tài liệu Khai phá dữ liệu dịch vụ bán hàng siêu thị Lotte Mart sẽ mang đến những ứng dụng thực tiễn của khai thác dữ liệu trong ngành bán lẻ.
Những tài liệu này sẽ giúp bạn mở rộng hiểu biết và khám phá thêm nhiều khía cạnh khác nhau của tự động hóa và phân tích dữ liệu trong kinh doanh.
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