1641 Business Intelligence Assignment 2 Pass, Assignments of Computer Science

Download 1641 Business Intelligence Assignment 2 Pass and more Assignments Computer Science in PDF only on Docsity! Higher Nationals in Computing Unit 14: BUSINESS INTELLIGENCE ASSIGNMENT 2 Assessor name: PHAN MINH TAM Learner’s name: NGUYEN MINH DAO ID: GCS210351 Class: GCS1103B Subject code: 1641 Assignment due: Assignment submitted: ASSIGNMENT 2 FRONT SHEET Qualification BTEC Level 5 HND Diploma in Computing Unit number and title Unit 14: Business Intelligence Submission date Date Received 1st submission Re-submission Date Date Received 2nd submission Student Name Nguyen Minh Dao Student ID GCS210351 Class GCS1003B Assessor name Phan Minh Tam Student declaration I certify that the assignment submission is entirely my own work and I fully understand the consequences of plagiarism. I understand that making a false declaration is a form of malpractice. Student’s signature DAO Grading grid P3 P4 P5 P6 M3 M4 D3 D4 Unit Learning Outcomes LO3 Demonstrate the use of business intelligence tools and technologies LO4 Discuss the impact of business intelligence tools and technologies for effective decision-making purposes and the legal/regulatory context in which they are used Assignment Brief (Continued from previous scenario) Your next task is to demonstrate to the board of directors about the ability of applying business intelligence in the company's current business processes. To demonstrate BI, you need to prepare a presentation about BI and related tools & techniques and a demonstration on real company dataset. For the presentation, you need: - Explain general concept of what is BI - Introduction to some tools / techniques for BI and their application in general For the demonstration, you need: - A (some) data set(s) extracted from the company's business processes. Explain the dataset. - Show how you pre-process data for later analysis, explain each step and it purpose - Design dashboards to show your analysis on pre-processed data. Explain clearly purpose of dashboards and charts. Suggestions should be made after analysis During the demonstration, you need collect feed-back and comments from users to review how well your dashboards design meet user or business requirement and what customization needed for future use. Team needs to present their point of view about how business intelligence tools can contribute to effective decision-making as well as the legal issues involved in exploiting user data for business intelligence. You may need to research for specific examples of organizations that use BI tools to enhance or improve their business and evaluate how they can use BI tools for extend their target audience and make them more competitive within the market. To summary, you need to submit a report in PDF includes 4 parts: your presentation, result of demonstration and review of user feedback, point of view on BI contribution and legal issues. Learning Outcomes and Assessment Criteria Pass Merit Distinction LO3 Demonstrate the use of business intelligence tools and technologies D3 Provide a critical review of the design in terms of how it meets a specific user or business requirement and identify what customisation has been integrated into the design. P3 Determine, with examples, what business intelligence is and the tools and techniques associated with it. P4 Design a business intelligence tool, application or interface that can perform a specific task to support problem- solving or decision-making at an advanced level. M3 Customise the design to ensure that it is user friendly and has a functional interface. LO4 Discuss the impact of business intelligence tools and technologies for effective decision-making purposes and the legal/regulatory context in which they are used D4 Evaluate how organisations could use business intelligence to extend their target audience and make them more competitive within the market, taking security legislation into consideration P5 Discuss how business intelligence tools can contribute to effective decision-making. P6 Explore the legal issues involved in the secure exploitation of business intelligence tools M4 Conduct research to identify specific examples of organisations that have used business intelligence tools to enhance or improve operations. Table of Content Unit 14: BUSINESS INTELLIGENCE ASSIGNMENT 2_______________________________________1 ASSIGNMENT 2 BRIEF_____________________________________________________________3 I. Determine, with examples, what business intelligence is and the tools and techniques associated with it (P3).____________________________________________________________8 1. Business Intellience.________________________________________________________8 2. The tools of Business Intelligence (BI tools)______________________________________9 2.1. Tableau_____________________________________________________________9 2.2. Microsoft Power BI____________________________________________________9 2.3. Python____________________________________________________________10 2.3.1. Numpy_______________________________________________________10 2.3.2. Pandas_______________________________________________________11 3. Business Intelligence techniques_____________________________________________11 3.1. Collection techniques_________________________________________________11 3.2. Analysis techniques__________________________________________________11 3.3. Analytic techniques__________________________________________________12 4. Tool BI used______________________________________________________________12 II. Design a business intelligence tool, application or interface that can perform a specific task to support problem-solving or decision-making at an advanced level (P4).____________________14 1. Dataset._________________________________________________________________14 2. Pre-process steps on dataset.________________________________________________15 2.1. Accquire the dataset_________________________________________________15 2.2. Get dataset_________________________________________________________15 2.3. Checking Dataset____________________________________________________16 3. Design dashboard_________________________________________________________16 4. Chart___________________________________________________________________18 4.1. Purpose of chart_____________________________________________________18 4.2. Type of chart in BI___________________________________________________18 4.3. Chart from dataset and evaluate________________________________________19 III. Discuss how business intelligence tools can contribute to effective decision-making(P5).____22 1. Business intelligence tools__________________________________________________22 2. The tools of Business Intelligence (BI tools) 2.1. Tableau Tableau is a data visualization application that allows users to visually study and comprehend data. To gather and analyze data, it may connect to a variety of data sources, including files, relational databases, and Big Data sources. Users may use Tableau to build interactive and shared dashboards that exhibit data trends, variations, and density in graphs and charts. Tableau is a great tool for converting raw data into an intelligible manner. It enables experts at all levels of a company to comprehend data and non-technical people to develop customized dashboards. Figure 2: Tableau 2.2. Microsoft Power BI Microsoft Power BI is a web-based business analytics tool that specializes in data visualization. It enables users to identify patterns in real time and includes new connections that might assist increase campaign success. It can be viewed from practically anywhere because it is web-based. Users may also use the platform to deliver real-time data and dashboards, as well as link their apps. You can visually explore your data with Power BI by using a free-form drag-and-drop canvas, a wide choice of modern data visualizations, and an easy-to-use report writing experience. You may also access your data from anywhere, at any time, thanks to native mobile apps that enable live, interactive access to your critical business data. Figure 3: Power BI 2.3. Python Python is a programming language used in the field of Business Intelligence (BI) to execute data analysis, data processing, and process automation activities in data gathering, processing, and visualization. Business data. Here are the two most important libraries used by Python in business intelligence: 2.3.1. Numpy Numpy is a sophisticated Python package that provides quick and adaptable n- dimensional arrays as well as tools for manipulating them. It may help business intelligence data analysis and processing by offering efficient and powerful tools for numerical computing and data analysis. Numpy's major characteristics that aid in data analysis and processing in business intelligence include: - Array operation: Numpy provides a powerful and fast ndarray object for storing and analyzing numerical data. Numpy arrays enable the direct use of whole data arrays for arithmetic and logical operations including addition, subtraction, multiplication, division, and comparisons without the usage of loops. - Random number generation: It is essential in business intelligence to be able to produce random sample data and random distributions. Numpy includes procedures for generating random integers and random arrays based on preset distributions such as the normal, uniform, and Poisson distributions. - Compatibility with other libraries: Numpy works well with the rest of the Python data science ecosystem, including Pandas, Matplotlib, and scikit-learn. This combination allows you to simply graph data in business intelligence and do complex analytics. 2.3.2. Pandas Pandas is yet another sophisticated Python package that offers high-performance, user-friendly data structures and data analysis capabilities. It is frequently used in combination with Numpy and other Python data science modules. Pandas can help businesses with data analysis and processing by providing efficient and effective tools for data manipulation, cleansing, and visualization. Some of the most important Pandas functionalities for data analysis and processing in business intelligence are: - Data manipulation: Pandas has sophisticated capabilities for modifying and cleaning data, such as filtering columns by specific criteria or conveniently eliminating values. - Data visualization: You can quickly visualize your data with Pandas by utilizing a variety of charting methods and standard chart options such as line charts, bar charts, scatter plots, and histograms. - Data import/export: Pandas makes it simple to import and export data from a variety of sources, including flat files, Excel workbooks, and SQL database tables. - Compatibility with other libraries: Pandas works well with the rest of the Python data science ecosystem, including Numpy, Matplotlib, and scikit-learn. This combination allows you to simply graph data in business intelligence and do complex analytics. 3. Business Intelligence techniques 3.1. Collection techniques Data collection strategies entail acquiring and arranging information from diverse sources. By cleaning, manipulating, and aggregating data, these procedures are used to obtain and prepare it for analysis. This includes approaches like: + Data mining is the process of discovering trends in massive datasets by using databases, statistics, and machine learning. + Data warehousing is the process of storing huge volumes of data in a central location for quick access and analysis. + Extract, transform, and load (ETL): Aggregating structured and unstructured data from numerous sources, converting it, and storing it in a centralized location for convenient analysis. 3.2. Analysis techniques Analysis techniques entail the examination and interpretation of data in order to develop insights and help decision-making. These methods are used to investigate and comprehend data by detecting patterns, correlations, and trends. II. Design a business intelligence tool, application or interface that can perform a specific task to support problem-solving or decision-making at an advanced level (P4). 1. Dataset. Figure 5: Dataset This is a fairly detailed dataset that shows the number of deaths by year, of each sex and different age groups, it also shows data on the death rate per 100,000 of the global countries. ■ The Country Code is to represent the simple code of each country ■ The Country Name absolutely is related to the name of that country ■ The year column displays the year of the death count, divided into ten-year gaps ending in 2010. ■ The age group column records age groups ranging from 0 to over 80 and splits them into several age groups, such as 0-6 years old, 20-24 years old, and so on. ■ Sex group shows the gender of people devide into male, female or both two sex. ■ Number of deaths collumn shows the amount of people death in that country, that year, that sex, or that age group ■ The death rate per 100000 is the representation of death number in 100000 people 2. Pre-process steps on dataset. 2.1. Accquire the dataset Before we get to the data analysis step, it is a must to have a dataset. For a student like me, I have received the dataset from my teacher who guide me in the subject. 2.2. Get dataset Figure 6: get dataset from folder To import a data set to Tableau, you choose the type of file that you want to import on the left of the tool, it will reference to your folder, pick the dataset and it will appear in Tableau. 2.3. Checking Dataset Figure 7: Checking data set The first step before analize a data must be checking whether that dataset is cleaned or not, if it clean (include all the needed information and doesn’t have wrong or null data), you can then continue with analysis step, if it not, you have to check the small square called “Use data interpreter” on the left side above your data files. It will automatically cleaning the data for you. Figure 8: auto cleaning function 3. Design dashboard BI dashboards give a complete real-time picture of an organization's data, allowing decision- makers to swiftly discover patterns and make educated decisions. Dashboards assist businesses in monitoring their progress toward goals and identifying areas for improvement by providing key performance indicators and other relevant information in an easy-to- understand manner. 4.3. Chart from dataset and evaluate Figure 10: The graph shows number of death in each age group Figure 11: The graph shows number of death by sex Figure 12: The graph shows number of death in every decades from 1970 Figure 13: The graph shows number of death by sex in every decades Figure 14: the graph shows the death rate per 100000 in every decades of each country Figure 15: The graph shows death rate per 100000 by sex in every decades of each country ○ Tableau licence is rather pricey. For example: Tableau is used by Salesforce to develop actionable sales and revenue forecasting dashboards. Dashboards assist the sales team in identifying patterns in their pipeline and making data-driven choices. Salesforce is a cloud-based software company that provides customer relationship management (CRM) service and also sells a complementary suite of enterprise applications focused on customer service, marketing automation, analytics, and application development . 1.2. Power BI A Microsoft's Excel Pivot Table and Excel data visualization features give dynamic visualizations and business intelligence capabilities with an interface that is easy enough for end users to construct their own reports and dashboards and quickly get comfortable with. Figure 18: chart power BI Excel integration: Power BI may be linked to any Microsoft Office product, including Excel. The raw data may be put into Excel, where previously observed behind-the-scenes images can be examined. R Script Visualization: Power BI is the only R-compatible tool that uses R's extensive visualization and analytic features for complex data display and analysis, such as forecasting. Natural Language Query: Power BI allows customers to ask natural language inquiries about their data and receive replies in the shape of charts and graphs. Quick Insights: Power BI can produce insights from data automatically by spotting patterns and trends. Data Alerts: Power BI users may set up alerts to get notifications when data changes or fits particular criteria. For examle in JetBlue: JetBlue implemented Power BI to help them analyze data from their customer service interactions. They were able to identify trends and patterns in customer complaints and feedback, which allowed them to improve their customer service experience. IV. Explore the legal issues involved in the secure exploitation of business intelligence tools (P6). 1. Kind of data we collect Because this content was provided by a credible source, it should be widely disseminated for multiple references. This data has been processed in great detail using the legal basis. Because the data will be made publicly available by the poster, our use and collection of data sets on the website does not breach any copyright or other related legal rights. The examination of this data has no consequence on the relevant company's finances, direction, service, and so on because it is supplied for reference purposes only and has no legal implications. 2. How is data collection legal? Data collecting must adhere to legal requirements as well as individual privacy. Here are some broad rules for collecting legal data: ● Consent: Data collecting occurs only with the user's or the person with the right to govern the data's consent. This is especially true for sensitive or personal information. ● Explicit purposes: Data is gathered for defined and legitimate reasons only, and it is not used for other purposes without the user's permission. ● Privacy Compliance: Collected data must be in accordance with individuals' privacy rights, including the protection of personal information and the prevention of illegal use or exploitation of the data. ● Legal compliance: Data collecting must adhere to all relevant laws, including those governing data protection, privacy, and intellectual property rights. ● Data security: Data collected must be kept safe and secure against illegal access, use, or disclosure. ● Data Transfer: When data is sent to a third party, assurances must be provided that the other party complies with data protection and privacy legislation. ● Integrated mitigation: Measures should be implemented to reduce the possible impact on an individual's privacy, such as retaining data only for as long as it is required and destroying it when it is no longer required. 3. How is it Legal for Compaines to Collect Your Data? Terms of Service Agreements 3.1. Terms of Service Agreement When trying to understand how businesses may obtain various types of information on people, it is natural to assume that these firms are doing it illegally. When companies gather and use this information, they are not only working within their legal rights, but also with their clients' clear legal agreement. Companies may lawfully obtain your data extremely easily, often even before customers realize they have agreed. Understanding what Terms of Service (ToS) agreements imply for customer privacy necessitates a closer look at these agreements. The Terms of Service are the long terms that appear when you register for a service. Before creating a new account or using a new program, users are typically prompted to read and then agree the terms and conditions. Because these terms are extensive and riddled with rather odd legal word formulations, most users just click "agree" and continue with account setup. Users may be unaware that by doing so, they have effectively "signed" a contract granting businesses the right to do whatever is described in the terms. The user waives their right to register a complaint if a firm has a section enabling the gathering of consumer purchase history and you click "I agree." The fact that some firms include provisions permitting them the ability to change the ToS without providing customers with prior notice significantly complicates matters. This means that by only "agreeing" to the ToS once, users basically agree to any changes made by the company, even if these changes include more intrusive data collection techniques. 3.2. Example Google: Google reserves the right to use users' search history, usage statistics, and other information to create new services. Google tracks users on other websites via widgets or analytics tools. YouTube: Everything that users upload to YouTube is saved. When videos are just removed off the internet, they are not completely wiped from YouTube's servers. Furthermore, the service has the right to delete user content without warning and to change its terms at any moment. Facebook: Facebook's Terms of Service include clauses that allow Facebook to track users on other websites and automatically share any data users submit on the website with other organizations and services. According to the Terms of Service, users of the Facebook Android app may be surprised to learn that audio and video can be taken at any time without the user's approval.