ASSIGNMENT 3 FRONT SHEET Qualification BTEC Level 5 HND Diploma in Computing Unit number and title Unit 14: Business Intelligence Submission date 25/04/2023 Date Received 1st submission 25/04/2023 Date Received 2nd submission Re-submission Date Student Name MAIHUUNAM Student ID BS00152 Class PBIT17101 Assessor name DO PHI HUNG Student declaration I certify that the assignment submission is entirely my 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 P5 P6 M4 D4 NAM ❒ Summative Feedback: Grade: ❒ Resubmission Feedback: Assessor Signature: Date: IV Signature: Assessment Brief Student Name/ID Number Unit Number and Title 14: Business Intelligence Academic Year 2018 Unit Tutor Assignment Title Assignment 2: Apply BI tools & techniques and their impact Issue Date Submission Date IV Name & Date Submission Format The submission is in the form of an individual written report. This should be written in a concise, formal business style using single spacing and font size 12. You are required to make use of headings, paragraphs, and subsections as appropriate, and all work must be supported with research and referenced using the Harvard referencing system. Please also provide a bibliography using the Harvard referencing system. Unit Learning Outcomes LO4 Discuss the impact of business intelligence tools and technologies for effective decisionmaking purposes and the legal/regulatory context in which they are used Assignment Brief (Continued from the previous scenario) After the demonstration, each member of the team needs to write an individual report to present his/her point of view about how business intelligence tools can contribute to effective decisionmaking as well as the legal issues involved in exploiting user data for business intelligence. You may need to research specific examples of organizations that use BI tools to enhance or improve their business and evaluate how they can use BI tools to extend their target audience and make them more competitive within the market. Learning Outcomes and Assessment Criteria Pass Merit 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 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 organizations that have used business intelligence tools to enhance or improve operations. Distinction D4 Evaluate how organizations could use business intelligence to extend their target audience and make them more competitive within the market, taking security legislation into consideration Table of Contents Assessment Brief ........................................................................................................................................................... 2 Introduction................................................................................................................................................................... 8 P5 Discuss how business intelligence tools can contribute to effective decision-making. ....................................... 9 1.1. BI Tools and Technology ................................................................................................................................. 9 • Centralized data :............................................................................................................................................... 9 • Self-sufficiency : ................................................................................................................................................. 9 • Make projections: ............................................................................................................................................... 9 Automated reports: ............................................................................................................................................... 9 • Reduces business costs:................................................................................................................................... 10 The following categories of features and functionalities are crucial for business intelligence tools: ................ 10 • Dashboards: ...................................................................................................................................................... 10 • Visualization: .................................................................................................................................................... 10 • Reporting: ......................................................................................................................................................... 10 • Predictive Analytics: ........................................................................................................................................ 10 • Data Mining: ..................................................................................................................................................... 10 • ETL (Extract, Transform, and Load): ................................................................................................................. 11 • OLAP (Online analytical processing): ............................................................................................................. 11 • Drill-Down:........................................................................................................................................................ 11 Some popular BI tools: ........................................................................................................................................ 11 1.2. BI tools can contribute to effective Decision-making .................................................................................. 17 P6 Explore the legal issues involved in the secure exploitation of business intelligence tools. ............................. 18 Legal matters in law: ........................................................................................................................................... 18 Respect for privacy: ............................................................................................................................................. 19 Ownership: .......................................................................................................................................................... 19 Data security:....................................................................................................................................................... 19 III. The example to explain in real world ................................................................................................................. 19 LinkedIn ............................................................................................................................................................... 19 Spambot .............................................................................................................................................................. 19 Netease................................................................................................................................................................ 20 Conclusion ................................................................................................................................................................... 20 References ................................................................................................................................................................... 21 Figure 1 Tableau ................................................................................................................................................................... 13 Figure 2 Tableau visuations ............................................................................................................................................. 14 Figure 3 Power BI ................................................................................................................................................................. 15 Figure 4 Python ..................................................................................................................................................................... 17 Figure 5 Dashboard ............................................................................................................................................................. 18 Introduction In the assignment, the benefits of BI tools like Power BI, Tableau, and Python are discussed. Users may now be aware of how to efficiently gather and analyze data using BI technology. They also understand that BI technologies might be useful in helping them make informed judgments. They are also aware of the legal issues surrounding the secure application of business intelligence technology, such as those about data security and privacy. P5 Discuss how business intelligence tools can contribute to effective decision-making. 1.1. BI Tools and Technology Business intelligence tools gather, handle, and examine copious volumes of organized and unstructured data from both internal and external systems. Documents, photos, emails, movies, diaries, books, postings on social media, files, and more are all examples of possible data sources. The data may be presented in user-friendly ways including reports, dashboards, charts, and graphs using BI tools that locate this information through queries. BI tool advantages include: • Centralized data : Companies get information from a variety of databases, including portals, enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and others. Business intelligence tools are the tools that pool the data together and give specific perspectives (problems, trends, analytics) based on my queries or what I want to know to make sense of it all. • Self-sufficiency : Data is no longer only the property of your company's IT staff. Now, even interns and non-technical employees may access and evaluate the data required for their teams. • Make projections: Employees may make decisions based on solid facts because of the abundance of historical and current data available to them. Users can produce insights based on a product or service's performance history with the help of predictive analytics and forecasting. If a business situation changes, the intelligence tools can detect anomalies automatically, enabling me to respond to interruptions as they happen. Automated reports: Many BI solutions are automated, so you don't have to switch between multiple programs or manually enter data into Excel spreadsheets. If that data is important and I want to use it in a presentation, I may make an interactive dashboard and download any charts or graphs I might want. • Reduces business costs: Because BI technologies are capable of so much, including sales forecasting, consumer behavior analysis, and real-time process monitoring, analyzing, planning, and reporting processes are now far more precise and efficient than they have ever been. The following categories of features and functionalities are crucial for business intelligence tools: • Dashboards: Dashboards are business intelligence (BI) reporting tools that compile and present important metrics on a single screen, allowing users to monitor and quickly assess business performance. • Visualization: Visualization is how facts and information are shown graphically. Data visualization tools offer an easy approach to observing and analyzing trends, outliers, and patterns in data by utilizing visual components like charts, graphs, and maps. • Reporting: Reporting is generally understood to be the method of preparing and analyzing data using a BI tool to discover and communicate actionable insights. • Predictive Analytics: Predictive analytics refers to forecasting the future using historical data, machine learning, and artificial intelligence. A mathematical model that takes into account the main trends and patterns in the data is supplied with this historical data. The model is then used to forecast future events using data as of now. • Data Mining: Data Mining is described as the process of examining data from many sources and distilling it into useful knowledge. In business intelligence, finding correlations or patterns between hundreds of fields in huge databases is the main goal of data mining. • ETL (Extract, Transform, and Load): ETL refers to the procedures used to gather data from various sources, prepare it appropriately for querying, reporting, and analysis, and then put it into a data warehouse or other central data repository. • OLAP (Online analytical processing): The technology that underlies many Business Intelligence (BI) systems is called (). One of the most effective tools for data discovery is OLAP, which has the capacity for endless report reading, intricate analytical computations, and predictive "what if" scenario (budget, forecast) planning. • Drill-Down: is an analytics feature that enables users to quickly switch from a high-level view of data to a more in-depth and granular view inside the same dataset they are examining by clicking on a statistic in a dashboard or report. Some popular BI tools: Tableau By enabling individuals and companies to make the most of their data, Tableau is a visual analytics platform that transforms how we utilize data to solve issues. Data-driven transformation is made possible through Tableau. It is, in essence, a technology that gathers, combines, analyzes, and presents significant information as charts. To grasp the information presented and get insights, they assist you in doing data analysis, data manipulation, and data visualization. In addition to databases, spreadsheets, big data platforms, and cloud services, Tableau can connect to a wide range of data sources. Advantage Multiple data sources are supported, including relational databases, no-SQL databases, multidimensional databases, big data platforms, and file data sources (Excel, CSV, txt, json, pdf, mdb, Tableau). Strong visualization skills for data. Tableau uses cutting-edge visualization technologies to present analytical results in a variety of colors, shapes, and sizes, allowing for rapid data processing. The development team at Tableau is still focusing on creating the popular chart kinds. As a result, Tableau is the best option for showing the data graph. However, it is not possible to employ gauges, 3D graphs, or heat maps. Mobile Support and Responsive Dashboards: Tableau Dashboards include amazing reporting options that let you design dashboards precisely for a certain device, such as a mobile phone or laptop. Tableau makes changes to ensure that the appropriate reports are sent to the appropriate devices by automatically detecting the devices users are using to view reports. Mobile Support and Responsive Dashboards: Tableau Dashboards include amazing reporting options that let you design dashboards precisely for a certain device, such as a mobile phone or laptop. Tableau makes changes to ensure that the appropriate reports are sent to the appropriate devices by automatically detecting the devices users are using to view reports. (Incomplete data, n.d.) • Use other scripting languages in Tableau: Users may integrate Python or R to execute sophisticated table computations without experiencing performance difficulties. Disadvantage Limited BI capabilities: Tableau still needs a few features to be a complete business analytics solution. Large-scale reporting, creating data tables, and static layouts are some examples. Additionally, there are only a few available export and print formats, which is problematic for sharing. Tableau is tough to insert in business architecture plans or adapt. Figure 1 tableau Figure 2 Tableau visuations Power BI Microsoft Power BI is a business intelligence (BI) platform that offers tools for aggregating, analyzing, visualizing, and sharing data with non-technical business users. Its goal is to improve and maximize the data visualization in reports, hence assisting in data analysis and decision-making. Furthermore, Power BI can gather information from hundreds of sources, including websites and databases, and then publish results in a secure, highly secret way. and efficiently and reliably collect company information Advantage Power BI can connect to any Microsoft Office program and integrate with Excel. You may enter raw data into Excel to view pictures that have already been visualized behind the scenes. The only tool in the TOP 5 that supports R, R Script Visualization makes use of R's robust visualization and analytics capabilities for sophisticated data display and analysis, such as forecasting. Strong Interactions: After adding visualizations, interactions between reports may be observed clearly. Users only need to click on a bar in the chart to see how the data will be displayed. Similarly to this, all you need to do to examine the values of the location chart, list, and KPI is choose a place from the map picture. Advanced Measures: Power BI uses the mathematical language DAX. It functions quite similarly to Excel but without the Excel reporting complexity. So, with DAX, you can design your KPIs in Power BI with much easier and quicker access, such as last quarter's sales. Disadvantage Management issues include Power BI's inability to manage group permissions completely and its inability to control how finely users may specify which columns they can see. Multi-level permissions are also not supported by Power BI. For the free version, data handling is poor: A cap on the volume of data that may be handled exists in the free version. If you want to speed up processing after reaching 2GB, you must upgrade to the commercial version. Figure 3 Power BI Python Python is a high-level, object-oriented, interpreted programming language with dynamic semantics used to create software and websites, automate processes, and do data analysis. Both the comprehensive standard library and the Python interpreter are open-source and freely distributable for all popular platforms. Python enables data analysts to execute intricate statistical computations, produce data visualizations, design machine learning algorithms, handle and analyze data, and perform other data-related operations. Aside from object-oriented and structured programming patterns, Python is a multi-paradigm programming language that also fully supports functional and aspect-oriented programming. Python is employed in many different industries and can accomplish a lot as a result. Advantage 1. User-friendly and simple to learn Because its syntax resembles English, the Python programming language is straightforward for everyone to learn and comprehend. This is a language that you may simply learn and pick up. One of the benefits of Python over other programming languages like C, C++, or Java is due to this. In addition, Python uses comparatively fewer lines of code to accomplish the same tasks and operations as other programming languages that use bigger code blocks. From an authority, gain more knowledge about Python. Join our Python classes in Bangalore! 2. When productivity is increased Python's high level of productivity and simplicity allows programmers to concentrate on problemsolving with ease, which is one further advantage of the language. 3. Translation of a Language Python may run the code in its entirety, line by line, as it is an interpreted language. Furthermore, if there is a mistake, it reports the error that happened rather than continuing with the execution. Disadvantage 1. Slow Motion Unfortunately, sometimes having strengths may also mean having shortcomings. Here is one such instance. Although Python is an interpreted language with dynamic typing, this also implies that the code is run line by line, which adds to the language's sluggish performance. Python's dynamic nature, which necessitates some additional effort during execution, is mostly to blame for its slow execution time. This is one of the reasons why Python is not employed when a program's speed is an important consideration. 2. Ineffective Memory Usage Python must make certain compromises to provide developers and programmers with some simplicity. A drawback of this language is that it consumes a lot of memory, which is problematic for creating apps that prioritize memory optimization. 3. Lack of expertise in mobile device programming Instead of utilizing it for client-side or mobile apps, developers often employ Python for server-side development. This is due to Python's low memory efficiency and sluggish processing speed when compared to other programming languages. Figure 4 Python 1.2. BI tools can contribute to effective Decision-making BI tools provide reporting and analytics that, via the use of reports, dashboards, charts, graphs, and visualizations, assist enterprises in informing regular business activities. Without the aid of an IT department, they combine diverse data sources to give quick and precise information. Businesses may combine data sources using BI technologies to get a full picture of what's going on inside the business. Leaders as a result make quicker, data-driven business choices. Figure 5 Dashboard P6 Explore the legal issues involved in the secure exploitation of business intelligence tools. Large volumes of organized and unstructured data are gathered, processed, and analyzed by business intelligence tools from both internal and external sources. Documents, photos, emails, videos, periodicals, books, social media postings, files, and other types of data sources, including consumer personal information, are examples. Due to this, the following issues develop: Legal matters in law: According to the regulations of other nations, companies must get consent and publicly explain their plans before collecting and exploiting consumers' personal information. The company should also have a suitable policy defining the information's intended use, its intended scope, how long it will be retained, etc. When using consumers' personal information, businesses must also maintain the privacy of such information. Respect for privacy: The protection of user privacy is required while gathering, analyzing, and using their data. Anyone who uses this service cares about this critical subject. Users' privacy must be protected by businesses to prevent exploitation or abuse of the data they supply by law enforcement, terrorists, or others. Ownership: Securing ownership is a significant barrier that has recently generated a lot of anxiety all around the world in an era where technology is pervasive and continuously changing. The rights of copyright holders are protected by laws in many nations, yet this problem will still call for stronger laws or regulations. Data security: Businesses that utilize BI tools to gather, process, and use user information must protect such information by the law and ethical standards. Securing consumer data fosters greater customercompany relations, which helps both the business community and society as a whole. III. The example to explain in real world -Some are accidental and may result from hardware or software failures LinkedIn Date: June 2021 Impact: 700 million users In June 2021, data linked with 700 million LinkedIn members were released on a dark website, affecting more than 90% of the company's user base. A hacker known as "God User" employed data scraping techniques to breach the site's (and others) API before releasing the first data collection of around 500 million clients. They then boasted that they were selling the whole 700 million client database. Spambot Date: 2017 Impact: 700 million accounts In August 2017, a spambot leaked passwords and emails due to a misconfiguration. As a result, In August 2017, a spambot leaked passwords and emails due to a misconfiguration. As a result, over 700 million records roughly equivalent to one email address for every man, woman, and child in Europe were leaked. However, this breach of data included lots of repeated and fake accounts. Roughly equivalent to one email address for every man, woman, and child in Europe were leaked. However, this breach of data included lots of repeated and fake accounts. Netease Date: October 2015 Impact: 235 million user accounts NetEase, a supplier of mailbox services through sites such as 163.com and 126.com, purportedly experienced a breach in October 2015 when dark web marketplace seller DoubleFlag sold email addresses and unencrypted passwords for 235 million users. NetEase has maintained that no data breach occurred, and HIBP continues to state: "Whilst there is evidence that the data itself is legitimate (multiple HIBP subscribers confirmed a password they use is in the data), due to the difficulty of emphatically verifying the Chinese breach, it has been flagged as "unverified." Conclusion In this assignment, I get knowledge about BI technologies and tools like Tableau, Python, and Power BI that I can use for real-world projects. I also learn how to use BI tools so that I can help with decision-making that is effective. I also address a few concerns regarding the secure use of business intelligence technologies. References Anon., 2023. bacs. [Online] Available at: https://www.bacs.vn/vi/blog/cong-cu-ho-tro/top-5-business-intelligence-tools-bitools-cho-doanh-nghiep-trong-nam-2020-8769.html [Accessed 12 04 2023]. Anon., 2023. topdev. [Online] Available at: https://topdev.vn/blog/python-la-gi/ [Accessed 12 04 2023].
