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 NGUYỄN TẤN KHOA Student ID GCD201759 Class GCD1002 Assessor name NGUYEN SI THI 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 Grading grid P3 P4 P5 P6 M3 M4 D3 D4 Summative Feedback: Resubmission Feedback: Grade: Assessor Signature: Date: IV Signature: Page 2 Table of Contents INTRODUTION.7 Chapter 1: Business Intelligence (P3).1 General about BI.1 What is BI?.2 Real examples of how to apply BI on business. Demonstration about BI (P4).1 Introduce and Explain chosen dataset(s).2 Pro-process steps on dataset(s) with Python.3 Design dashboard with PowerBI.1 Stacked bar chart.4 Map and Country selection board.
Point of View (P5 & P6).1 Showing specific examples on your organizations/companies.2 Discuss the legal issues involved in exploiting user data for business intelligence.41 Page 3 Table of Figures Figure 1 Business Intelligence.15 Figure 8 SAP Analytics Cloud.17 Figure 10 MicroStrategy Analytics.20 Figure 13 Import & show dataset.21 Figure 14 Cleansing dataset.21 Figure 15 Explore info().22 Figure 16 Explore tail ().22 Figure 17 Explore describe ().23 Figure 18 Average stats.23 Figure 19 Max stats.24 Figure 20 Min stats.25 Figure 21 Joint plot of the dataset.26 Figure 22 Pair plot of Total Cases, Total Deaths and New Deaths.27 Page 5 Figure 23 Top 10 countries with highest total cases.28 Figure 24 Top 10 countries with highest total deaths.28 Figure 25 Power BI.29 Figure 26 Stacked bar chart.30 Figure 27 Donut chart.31 Figure 28 Area chart.32 Figure 29 Map and Country selection board.34 Figure 31 Dashboard interactivity.35 Figure 32 Visualize data using line graph.36 Page 6 INTRODUTION Business intelligence (BI) is a technology-centric approach aimed at examining data and furnishing valuable insights to executives, supervisors, and staff to support them in enhancing their business choices. Within the BI framework, organizations gather information from both internal and external information technology systems, ready it for examination, execute inquiries on it, and craft data representations, BI dashboards, and reports to present the analytical findings to business users for both operational and strategic decision-making. The primary objective of business intelligence (BI) initiatives is to support businesses in making more informed decisions that can lead to increased revenue, enhanced operational efficiency, and a competitive edge over their peers. BI achieves this by integrating analytics, data management, and reporting technologies with a range of data handling and analysis methods.
The overarching aim of BI is to leverage pertinent data for the betterment of a company's operations. Organizations that effectively implement BI tools and strategies have the potential to convert their accumulated data into valuable insights regarding their operations and strategies. These insights can then be used to make superior business choices that enhance productivity and revenue, resulting in accelerated growth and greater profitability. Chapter 1: Business Intelligence (P3) 1.1 General about BI 1.1 What is BI? In simpler terms, business intelligence (BI) is a technology that helps organizations learn from the past to make better decisions, improve actions, and even predict the future.
BI encompasses skills, methods, technology, or applications that assist in decision-making. It's a set of tools and processes that blend business analytics, data mining, data visualization, data tools, infrastructure, and methods to enable organizations to make decisions based on data. Page 7 Figure 1 Business Intelligence Step Business Intelligence systems are implemented Step 1: Initial data is extracted from the company's database, which may be spread across various diverse systems. Step 2: The data undergoes a cleaning process and is then moved into the data warehouse.
Tables are linked, and data segments are constructed. Step 3: Users have the ability to employ the BI system for various purposes, including asking questions, requesting customized reports, or conducting different forms of analysis.2 Real examples of how to apply BI on business Example 1: Starbucks Thanks to its highly effective loyalty card program and mobile application, Starbucks has access to detailed transaction data from millions of customers. Utilizing this data alongside business intelligence tools, the company predicts customer purchases and sends tailored offers through their app and email. This strategy encourages repeat visits from existing customers, ultimately leading to a boost in revenue.
Example 2: Coca-Cola Coca-Cola leverages its vast social media presence, boasting 35 million Twitter followers and 105 million Facebook fans. Employing AI-driven image recognition technology, the company can identify instances where images of its beverages are shared on the internet. By harnessing the potential of business intelligence (BI), Coca- Cola gains insights into their customer demographics, geographical distribution, and the reasons behind online brand mentions. This valuable information is then utilized to deliver highly personalized advertising to customers, resulting in a fourfold increase in the likelihood of click-through compared to generic advertisements.
Example 3: Netflix The internet entertainment giant, Netflix, possesses a substantial BI edge thanks to its 148 million user base. What is the business intelligence approach of Netflix? The company harnesses data in diverse ways. Take, for example, how it develops and evaluates fresh programming ideas, drawing inspiration from previously aired shows. Netflix also utilizes business intelligence to actively engage users with its content.
The platform excels at promoting tailored content to such an extent that its recommendation algorithm is responsible for more than 80% of all streamed content.2 BI techniques Numerous business intelligence techniques are at a company's disposal to obtain valuable insights for informed decision-making. Let's explore some of the most prevalent BI techniques. OLAP OLAP (Online Analytical Processing) stands as a widely used business intelligence method, particularly effective for tackling multi-dimensional analytical challenges. A key advantage of OLAP is its multi-dimensional framework, enabling users to examine data issues from multiple perspectives.
This capability often leads to the discovery of concealed issues within processes. OLAP finds application in various tasks, including budgeting, CRM data analysis, and financial forecasting. Figure 2 OLAP Reportig The complete sequence of activities encompassing planning, scheduling, performance tracking, sales analysis, reconciliation, and data storage is collectively termed as reporting in the realm of business intelligence. This process serves as a valuable tool for organizations to systematically collect and present data, aiding in managerial activities, planning, and decision-making.
Depending on their needs, business leaders may access reports on a daily, weekly, or monthly basis. Page 10 Figure 3 Reporting Analytis In the realm of Business Intelligence, the term "analytics" refers to the practice of examining data to make informed decisions and uncover patterns. Business analysts and executives rely on analytics as it enables them to gain deeper insights from their data and extract valuable insights. Analytics find application in various facets of business, ranging from marketing to call centers, and they take on diverse forms.
For instance, in call centers, voice analytics is employed to monitor customer sentiment and enhance the quality of responses provided. Page 11 Figure 4 Analytics ETL Extraction-Transformation-Loading (ETL) is a unique business intelligence technique that manages the entire data processing workflow. It retrieves data from various sources, performs necessary transformations, and then feeds it into the business intelligence system. ETL tools are primarily employed as transactional tools for converting data from diverse sources into data warehouses.
ETL also plays a role in modifying the data to align with the specific requirements of the company. In this way, it enhances the data's quality before placing it into its final destinations, such as databases or data warehouses. Page 12 Figure 5 ETL 1.3 BI tools Tableau Tableau is a data visualization tool that empowers data analysts, scientists, statisticians, and various professionals to visually represent data and draw meaningful insights from it. Tableau is renowned for its rapid data processing capabilities, delivering desired visualizations efficiently.
Importantly, it maintains a high level of security, assuring users that any security concerns identified will be promptly addressed. Users can utilize Tableau to prepare, cleanse, and format their data before creating data visualizations that can be shared with other Tableau users. This versatile data visualization software can serve the needs of individual data analysts as well as entire business teams and organizations. Page 13 Figure 6 Tableau Sisense Sisense is a data visualization solution rooted in business intelligence, offering an array of tools to assist data analysts in simplifying intricate data and extracting insights for their organizations and external stakeholders.
Sisense envisions a future where every business is data-centric, and every product has some connection to data. Consequently, it endeavors to furnish business teams and data analysts with a diverse set of data analytics tools to aid in the transformation of their organizations into data-driven entities, aligning with this data-centric future. Sisense offers a remarkably straightforward installation and user experience. Setting it up takes less than a minute, allowing data analysts to swiftly dive into their work and observe results.
Users have the flexibility to export their files into a range of formats, including PowerPoint, Excel, MS Word, PDF, and more, through Sisense. Moreover, should users encounter any difficulties, Sisense offers round-the-clock customer support for assistance. Page 14 Figure 7 Sisense SAP Analytics Cloud SAP Analytics Cloud is a powerful platform that integrates business intelligence and data analytics to aid in the evaluation and visualization of data, enabling you to predict business outcomes effectively. It provides access to cutting-edge modeling tools that can identify potential data errors and categorize various data metrics and dimensions.
Additionally, SAP Analytics Cloud offers Data Smart Transformations, enhancing the quality of visualizations. What sets it apart is its ability to address your questions and concerns regarding data visualization using conversational artificial intelligence and natural language technologies, ensuring that you are completely satisfied with the platform's capabilities. Page 15 Figure 8 SAP Analytics Cloud Qlik QlikView and Qlik Sense are two widely acclaimed business intelligence tools. QlikView is recognized as a guided tool, while Qlik Sense is known as a self-service business intelligence system.
These sophisticated applications offer users the flexibility to analyze data at various stages, from input to processing to output. Notably, QlikView boasts a system memory feature that logs all actions performed during the analysis. It is known for its high level of sophistication and exceptional overall performance. Furthermore, mobile users have access to the same interactive analytical tools, intuitive associative search capabilities, and impressive visualizations that PC users enjoy, making it a versatile and accessible BI system.
Page 16 Figure 9 Qlik MicroStrategy Analytics MicroStrategy Analytics is a United States-based data analytics company that offers a versatile platform for those seeking a customized interface. This platform is particularly well-suited for organizations and individuals who are new to BI systems, as MicroStrategy is renowned for its exceptional customized customer support. On this platform, users can craft personalized dashboards and leverage advanced analytics tools to derive valuable insights from data, making it a powerful resource for data-driven decision-making. Page 17 Figure 10 MicroStrategy Analytics Chapter 2.
Demonstration about BI (P4) 2.1 Introduce and Explain chosen dataset(s) The COVID-19 pandemic, which occurred during 2019-20, is a global health crisis caused by the coronavirus 2, leading to severe acute respiratory illness (SARS-CoV-2). The virus was initially identified in Wuhan, Hubei, China, in December of that year. On March 11, 2020, the World Health Organization officially declared the outbreak as a pandemic. By that date, more than 126,000 cases had been confirmed in over 110 countries and territories, with significant outbreaks occurring in mainland China, Italy, South Korea, and Iran.
The disease had resulted in the unfortunate loss of over 4,600 lives, while around 67,000 individuals had survived. Please note that these figures and details are based on information available up to March 11, 2020, and the situation has evolved since then. Page 18 COVID-19 remains a prominent and urgent global issue, with the entire world grappling with the profound and multifaceted impacts of the disease.