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Data Science for Business: A Guide to Data Collection, Analysis, and Decision Making, Assignments of Internet and Information Access

Binh Duong University (BDU)Internet and Information Access

A comprehensive overview of data science and its applications in business. It covers key concepts such as data collection, analysis, and decision-making, highlighting the importance of data in improving operational efficiency, increasing revenue, and making informed strategic decisions. The document also explores various tools and technologies used in data science, including python, r, tableau, power bi, and data warehouses, and discusses challenges related to data security and data cleaning. It provides practical examples and case studies to illustrate the real-world applications of data science in business.

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ASSIGNMENT FINAL REPORT
Qualification BTEC Level 5 HND Diploma in Computing
Unit number and title Unit 17: Business Process Support
Submission date 10/08/2024
Date Received 1st
submission
Re-submission Date Date Received 2nd
submission
Student Name Nguyễn Minh Ánh Student ID BH00644
Class SE06203 Assessor name Nguyễn Văn Toàn
Plagiarism
Plagiarism is a particular form of cheating. Plagiarism must be avoided at all costs and students who break the rules, however innocently, may be
penalised. It is your responsibility to ensure that you understand correct referencing practices. As a university level student, you are expected to use
appropriate references throughout and keep carefully detailed notes of all your sources of materials for material you have used in your work,
including any material downloaded from the Internet. Please consult the relevant unit lecturer or your course tutor if you need any further advice.
Student Declaration
I certify that the assignment submission is entirely my own work and I fully understand the consequences of plagiarism. I declare that the work
submitted for assessment has been carried out without assistance other than that which is acceptable according to the rules of the specification. I
certify I have clearly referenced any sources and any artificial intelligence (AI) tools used in the work. I understand that making a false declaration is
a form of malpractice.
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Download Data Science for Business: A Guide to Data Collection, Analysis, and Decision Making and more Assignments Internet and Information Access in PDF only on Docsity!

ASSIGNMENT FINAL REPORT

Qualification BTEC Level 5 HND Diploma in Computing Unit number and title Unit 17: Business Process Support Submission date 10/08/2024 Date Received 1st submission Re-submission Date Date Received 2nd submission Student Name Nguyễn Minh Ánh Student ID BH Class SE06203 Assessor name Nguyễn Văn Toàn

Plagiarism

Plagiarism is a particular form of cheating. Plagiarism must be avoided at all costs and students who break the rules, however innocently, may be penalised. It is your responsibility to ensure that you understand correct referencing practices. As a university level student, you are expected to use appropriate references throughout and keep carefully detailed notes of all your sources of materials for material you have used in your work, including any material downloaded from the Internet. Please consult the relevant unit lecturer or your course tutor if you need any further advice.

Student Declaration

I certify that the assignment submission is entirely my own work and I fully understand the consequences of plagiarism. I declare that the work submitted for assessment has been carried out without assistance other than that which is acceptable according to the rules of the specification. I certify I have clearly referenced any sources and any artificial intelligence (AI) tools used in the work. I understand that making a false declaration is a form of malpractice.

Student’s signature Anh Grading grid P1 P2 P3 P4 P5 P6 P7 M1 M2 M3 M4 D1 D

TABLE OF CONTENTS A. INTRODUCTION....................................................................................................................................... 9 B. BODY...................................................................................................................................................... 10 ASM 1........................................................................................................................................................ 10 LO1 Discuss the use of data and information to support business processes and the value they have for an identified organisation......................................................................................................................... 10 PRESENT.................................................................................................................................................... 10 I. Discussion on how data and information support business processes, including the value they have for organisations........................................................................................................................... 10

  1. What is business data?............................................................................................................... 10
  2. Information in Business.............................................................................................................. 11
  3. The Importance of Data and Information in Business Processes.............................................. 12
  4. Types of data and their role in business.................................................................................... 13
  5. Data and Information Support Business Processes and Deliver Value to the Organization..... 13 II. Discussion of how data is generated and used by organisations to support business processes and the tools for manipulation to form meaningful data..................................................................... 19
  6. Generate data............................................................................................................................. 19
  7. How to use data......................................................................................................................... 20
  8. Tools for data processing?......................................................................................................... 21
  9. What tools did I use in the project?........................................................................................... 25 III. Assess the Value of Data and Information for Individuals and Organizations in Real-World Business Processes................................................................................................................................ 25
  10. Creating Sample Data for the Problem...................................................................................... 26
  11. Apply Power BI and use business results to help leaders make decisions for the business...... 27
  12. Use Power BI tools to create a Dashboard that includes evaluation charts and decision support for managers........................................................................................................................ 34 LO2 Discuss the implications of the use of data and information to support business processes in a real-world scenario................................................................................................................................... 37 REPORT...................................................................................................................................................... 37 I. Discuss the legal and socio-ethical implications of using data and information to support business processes................................................................................................................................ 37

II. Describes common threats to data and how to mitigate them at the individual and

 - 1. Identify the problem.................................................................................................................. - 2. Analyze problems....................................................................................................................... - 3. Proposed solution
  • organizational levels..............................................................................................................................
      1. Common Threats to Data...........................................................................................................
      1. Mitigation Strategies..................................................................................................................
      1. Examples of Effective Mitigation................................................................................................
  • processes............................................................................................................................................... III. Analyze the impact of using data and information to support your real-world business
      1. Analyze the impact of data and information.............................................................................
      1. Assessment on the impact and value of data and information
  • within a defined organization............................................................................................................... IV. Evaluae the broader implications of using data and information to support business processes
      1. Positive implications of using data and information:.................................................................
      1. Negative connotations of using data and information:.............................................................
      1. Consequences of not adequately protecting data:....................................................................
  • processes................................................................................................................................................... LO3 Explore the tools and technologies associated with data science and how it supports business
    • processes and inform decisions.(P5)..................................................................................................... 1) Discuss how tools and technologies associated with data science are used to support business
      • 1.1. Exploration of tools and technologies associated with Data Science:...................................
      • 1.2. Discuss how tools and technologies support to the Business process and Inform decision:
      1. Assess the benefits of using data science to solve problems in real-world scenarios.(M3).........
      • 1.1. Tool and Technology Benefits of the ABC Manufacturing Project.........................................
      • 1.2. Data-Driven Decision Making.................................................................................................
      • 1.3. Improved Efficiency and Productivity.....................................................................................
      • 1.4. Enhanced Customer Understanding and Personalization......................................................
      • 1.5. Competitive Advantage..........................................................................................................
      • 1.6. Risk Mitigation and Fraud Detection......................................................................................
        • 1.7. Improved Forecasting and Planning.......................................................................................
        • 1.8. Innovation and New Opportunities........................................................................................
    • business problems.................................................................................................................................... LO4 Demonstrate the use of data science techniques to make recommendations to support real-world - 1.1. Problems Encountered by ABC Manufacturing When Collecting Data...................................... - 1.2. Data Science Solutions to Support Decision Making.................................................................. - Manufacturing................................................................................................................................... 1.3. Applying Data Science Tools to Solve Problems Encountered When Collecting Data for ABC - 1.4. Components commonly found in the Overall Architecture.................................................
      • (P7) 2) Implement a data science solution to support decision making related to a real-world problem.
        • 2 .1. What is data collection?...........................................................................................................
        • 2.2. Data Cleaning and Preprocessing.............................................................................................
        • 2 .3. Apply data science solutions to support decision making.......................................................
        • 2 .4. Apply model development data science solutions to support decision making......................
      • (M4)..................................................................................................................................................... 3) Make justified recommendations that support decision making related to a real-world problem.
        • 3.1. Analyzing Sales Trends.............................................................................................................
        • 3.2. Customer Segmentation..........................................................................................................
        • 3.3. Forecasting Future Sales..........................................................................................................
        • 3.4. Identifying Key Sales Drivers....................................................................................................
        • 3.5. Detecting Anomalies in Sales Data..........................................................................................
      • identified organisation........................................................................................................................ 4) Evaluate the use of data science techniques against user and business requirements of an
        • 4.1. Evaluation Against User Requirements................................................................................
        • 4.2. Evaluation Against Business Requirements..........................................................................
        • 4.3. Evaluating the Use of Data Science Techniques...................................................................
  • C. CONCLUSION.......................................................................................................................................
  • D. EVALUATE............................................................................................................................................
  • E. REFERENCES........................................................................................................................................
  • Figure 1 Business data.................................................................................................................................. TABLE OF FIGURE
  • Figure 2 Information in business..................................................................................................................
  • Figure 3 Data and Information.....................................................................................................................
  • Figure 4 Desision-Making.............................................................................................................................
  • Figure 5 Customer satisfaction.....................................................................................................................
  • Figure 6 Revenue and profits........................................................................................................................
  • Figure 7 Problem Solving..............................................................................................................................
  • Figure 8 Company process............................................................................................................................
  • Figure 9 Sustainable development...............................................................................................................
  • Figure 10 Efficiency and costs.......................................................................................................................
  • Figure 11 Transparency and compliance......................................................................................................
  • Figure 12 New product.................................................................................................................................
  • Figure 13 Long-term strategies.....................................................................................................................
  • Figure 14 Excel..............................................................................................................................................
  • Figure 15 SQL................................................................................................................................................
  • Figure 16 Power BI........................................................................................................................................
  • Figure 17 Tableau.........................................................................................................................................
  • Figure 18 Identify the problem.....................................................................................................................
  • Figure 19 Analyze problems.........................................................................................................................
  • Figure 20 Common Threats to Data.............................................................................................................
  • Figure 21 Mitigation Strategies....................................................................................................................
  • Figure 22 Analyze the impact.......................................................................................................................
  • Figure 1 Python.............................................................................................................................................
  • Figure 2 R......................................................................................................................................................
  • Figure 3 SQL..................................................................................................................................................
  • Figure 4 Julia.................................................................................................................................................
  • Figure 5 SQL, NoSQL.....................................................................................................................................
  • Figure 6 Data Warehouses...........................................................................................................................
  • Figure 7 Data Lakes.......................................................................................................................................
  • Figure 8 Web Scraping Tools........................................................................................................................
  • Figure 9 ETL Tools.........................................................................................................................................
  • Figure 10 Data Cleaning Tools......................................................................................................................
  • Figure 11 Statistical Analysis.........................................................................................................................
  • Figure 12 Data Visualization.........................................................................................................................
  • Figure 13 Machine Learning Libraries..........................................................................................................
  • Figure 14 AI Platforms..................................................................................................................................
  • Figure 15 Data Governance..........................................................................................................................
  • Figure 16 Data Security Tools.......................................................................................................................
  • Figure 17 Deployment Tools.........................................................................................................................
  • Figure 18 Monitoring Tools..........................................................................................................................
  • Figure 19 Data-Driven Decision Making......................................................................................................
  • Figure 20 Analyzing historical sales data to identify patterns and trends...................................................
  • Figure 21 Analyzing market trends to understand consumer behavior and preferences...........................
  • Figure 22 Analyzing customer feedback to understand preferences and improve products......................
  • Figure 23 Improved Efficiency and Productivity...........................................................................................
  • Figure 24 Proactive maintenance using real-time IoT data to monitor equipment performance..............
  • Figure 25 Real-time energy consumption monitoring for optimizing usage...............................................
  • Figure 26 Real-time route optimization using GPS and IoT data.................................................................
  • Figure 27 Enhanced coordination through real-time data alerts.................................................................
  • Figure 28 Personalizing marketing efforts based on customer purchase history and preferences.............
  • Figure 29 Real-time visibility into supplier data for improved coordination and decision-making.............
  • Figure 30 Real-time shipping status updates to optimize logistics and inventory management................
  • Figure 31 Coordinated supply chain operations through integrated data systems.....................................
  • Figure 32 Monitoring equipment performance to identify potential tampering or malfunctions..............
  • Figure 33 Implementing proactive risk management measures based on data analysis............................
  • Figure 34 Analyzing historical sales data to forecast future demand..........................................................
  • Figure 35 Optimizing inventory management based on demand forecasts and market trends.................
  • Figure 36 Leveraging customer feedback and market data to drive product innovation...........................
  • Figure 37 Identifying new business opportunities through data analysis and market trends....................

B. BODY

ASM 1

LO1 Discuss the use of data and information to support business processes and the value they have for an identified organisation. PRESENT I. Discussion on how data and information support business processes, including the value they have for organisations In the digital age, data and information have become valuable resources for businesses. Using data not only helps improve operational performance but also creates value for businesses. In the modern business environment, data and information have emerged as important assets, central to business operations and strategic planning of organizations. Understanding their importance and how they can be leveraged to support business processes is critical to achieving operational excellence and maintaining a competitive advantage. Before delving into the role and value of data and information in business processes, we need to understand their concepts and roles. Data and information play an extremely important role in supporting business operations and benefiting the organization.

1. What is business data? Business data - A Strategic Asset for Organizational Excellence is a collection of information collected from the daily activities of a business. It includes many different types of data such as transactional data, customer data, marketing data, and data from social media and the web. Each of these types of data plays an important role in supporting business processes and decision making. Figure 1 Business data

Data Example:  Sales data: Number of products sold, revenue earned.  Customer information: Name, contact information, purchase history.  Production statistics: Number of products produced, production time, machine performance.  Financial transactions: Income and expenditure reports, profits.

2. Information in Business Information in business- From Data to Actionable Knowledge represents processed, organized, and contextualized data that transforms raw inputs into actionable knowledge. It bridges the gap between data accumulation and strategic implementation, enabling stakeholders to derive insights, formulate strategies, and drive operational efficiencies. For instance, analyzing sales trends and customer preferences converts raw sales data into actionable insights for devising targeted marketing campaigns or optimizing inventory management. Figure 2 Information in business Information Example:  Sales trends: Analyze sales data over time periods to identify trends.  Customer segmentation: Grouping customers based on purchasing behavior.  Manufacturing performance: Metrics are derived from production data to evaluate operational efficiency.  Financial Summary: Aggregates financial data to show profits and losses.

solutions to meet changing consumer needs, drive innovation cycles, and maintain a competitive advantage.

4. Types of data and their role in business  Transaction data is specific information about a business's sales and purchase transactions. This is a collection of data related to sales, profits, costs, and other business indicators, recorded from POS (Point of Sale), ERP (Enterprise Resource Planning) systems, and other business indicators. financial management platform. Transaction data provides a comprehensive view of an enterprise's daily business operations and is an important basis for evaluating business performance.  Customer data includes detailed information about customers and their shopping behavior. This is important data about personal information, product preferences, purchase history, and feedback from customers about the business's products and services. This data helps businesses better understand their customers, thereby personalizing marketing strategies and improving customer experience.  Marketing data is information about the effectiveness of marketing campaigns that businesses deploy. This includes data on conversion rates, campaign virality metrics, and customer feedback. This data helps businesses evaluate and adjust marketing strategies accurately and effectively.  Data from social media and the web includes information about interactions and responses from customers on social media platforms and websites. This is data related to interactions, comments, reviews, and feedback about a business's products and services on social networks and other online channels. This data provides insight into customer psychology and trends, helping businesses devise appropriate marketing and interaction strategies. 5. Data and Information Support Business Processes and Deliver Value to the Organization On the path towards success and sustainable development, data and information play an extremely important role for every organization, not only as a source of information but also as a strategic and decision support tool. Optimize business processes. These are the benefits that data and information bring to organizations: a. Help businesses make decisions

Figure 4 Desision-Making Data and information provide managers and leaders with an accurate basis for making strategic decisions. By analyzing market trends, customer behavior and performance data, businesses can predict and respond quickly to changes in the business environment. For example, through analysis of customer and transaction data, ABC Manufacturing can adjust production and marketing strategies to match market demand and optimize profits. b. Improve customer satisfaction Figure 5 Customer satisfaction Shopping behavior data, customer feedback and marketing data help businesses better understand customer needs and expectations. By personalizing the purchasing experience and improving customer service, organizations can increase customer satisfaction and loyalty. For example, ABC Manufacturing uses customer data to improve products and services, thereby improving service quality and effectively meeting customer expectations. c. Increase revenue and profits

Figure 8 Company process Data aids in evaluating and improving production, operational and management processes. ABC Manufacturing has used data to monitor and evaluate the effectiveness of internal processes, thereby optimizing and improving product and service quality, while reducing waste and enhancing productivity. f. Promote sustainable development Figure 9 Sustainable development Data and information also play an important role in directing and promoting the sustainable development of the organization. By analyzing trends and customer interactions, ABC Manufacturing has established long-term development goals and built appropriate strategies to meet future market requirements. g. Improve efficiency and save costs

Figure 10 Efficiency and costs Data helps businesses identify wasteful trends and optimize processes to save costs. ABC Manufacturing has applied data analytics to minimize inefficient operations and optimize resource management, thereby improving production efficiency and significantly reducing costs. h. Increase transparency and compliance Figure 11 Transparency and compliance Using data to track and report business activities also helps organizations increase transparency and comply with legal and ethical regulations. ABC Manufacturing has used data analytics tools to ensure that its operations comply with set rules and conditions, thereby enhancing the trust and reputation of customers and the community. i. Develop new products and services

and enable proactive responses to market dynamics. As a result, organizations that exploit the full potential of data and information will be well positioned to thrive in the modern business environment. II. Discussion of how data is generated and used by organisations to support business processes and the tools for manipulation to form meaningful data

1. Generate data Data is a vital resource in business, providing the basis for organizations to better understand their operations, thereby making strategic decisions and optimizing efficiency. The data generation process includes:  Transaction data: - This is detailed information about the company's product or service purchases. This data is collected from POS (Point of Sale) systems or online payment systems. For example, every time a customer purchases a product, the POS system records information such as product, quantity, price, transaction time, and business indicators such as revenue and profit. - Example: A retail store uses a POS system to record each sales transaction. This transaction data not only helps them manage inventory effectively, but also allows them to predict customer shopping trends and adjust sales strategies.  Customer data: - Collected from CRM (Customer Relationship Management) systems and other interactive channels such as websites, social networks, email marketing. This data includes customers' personal information, purchase history, shopping habits, interactions with the company's products and services. - For example: An electronics company collects data from interactive channels such as websites and social networks to better understand customer tastes and needs. This data helps them optimize their marketing strategies and improve customer experience.  Marketing data: - Includes data about the effectiveness of marketing campaigns such as email open rates, ad click rates, social network interactions and customer feedback. This data helps businesses evaluate the effectiveness of marketing campaigns and adjust marketing strategies effectively. - Example: A pharmaceutical company uses data from online advertising campaigns to measure the effectiveness of its marketing campaigns. This data helps them optimize advertising budgets and increase consumer-to-customer conversion rates.

 Data from social media and the web:

  • Includes data about interactions from customers on social networking platforms such as Facebook, Twitter, Instagram and feedback from customers on the company's website. This data provides insights into customer sentiment and trends towards products and services.
  • Example: A fashion company uses data from social media platforms to track and analyze customer feedback about new products. This data helps them better understand customer preferences and adjust sales strategies accordingly. 2. How to use data Data is widely used in business operations to:  Strategic decisions:
  • Data helps managers and business leaders make smart strategic decisions, from new product development and market direction to product distribution and prici
  • Example: An automobile manufacturing company uses market data to evaluate demand and consumer trends. This data helps them decide to develop new car models suitable for the market.  Marketing and customer interaction:
  • Customer data helps personalize the customer experience, from sending marketing emails with relevant content to targeted advertising based on each customer's shopping behavior.
  • Example: A retail company uses customer data to create personalized marketing campaigns, thereby increasing conversion rates and maintaining customer loyalty.  Risk management:
  • Data helps identify and manage risks in business activities, from production risks to financial and distribution risks.
  • For example: An insurance company uses data from CRM systems to assess the risk of each insurance contract and adjust its insurance strategy accordingly.  Monitor and improve performance:
  • Data analysis tools such as Power BI and Google Analytics help businesses monitor and evaluate business performance, thereby improving processes and optimizing costs.