Business Intelligence Lecture Notes PDF - Far Eastern University

Page 1 of 4 FAR EASTERN UNIVERSITY INSTITUTE OF ACCOUNTS, BUSINESS AND FINANCE DEPARTMENT OF ACCOUNTANCY AND INTERNAL AUDITING AUD1207 – INTEGRATED INTERNAL AUDITING REVIEW CO...

Page 1 of 4 FAR EASTERN UNIVERSITY INSTITUTE OF ACCOUNTS, BUSINESS AND FINANCE DEPARTMENT OF ACCOUNTANCY AND INTERNAL AUDITING AUD1207 – INTEGRATED INTERNAL AUDITING REVIEW COURSES SECTION A - BUSINESS ACUMEN BA 04 – BUSINESS INTELLIGENCE MR. CHRISTIAN ANDREI G. UTANES, CPA, CMA, MBA units NOTE TO STUDENTS: These handouts are of property of the reviewer. Unnecessary sharing and uploading of these materials are not allowed. LEARNING OBJECTIVES Upon completion of this chapter, you should be able to 1. Define Business Intelligence 2. Understand the importance of Business Intelligence in business setting 3. Identify the Benefits of Business Intelligence 4. Enumerate and explain the various types of BI tools and software 5. Identify the various data visualization tools LECTURE NOTES BA 04.01 – BUSINESS INTELLIGENCE Business Intelligence (BI) collects and analyzing internal data and external data to provide new insights that were not apparent before. Gathering BI data can lead to new business development opportunities and growth in current business and its absence can lead to business downturns slowly and business declines eventually. Business intelligence (BI) is a process driven by technology that analyzes business data in order to provide information that can be actioned so that executives and managers can make better-informed business decisions. Business intelligence is a broad term that encompasses data mining, process analysis, performance benchmarking, and descriptive analytics. BI parses all the data generated by a business and presents easy-to-digest reports, performance measures, and trends that inform management decisions.  Page 2 of 4 BENEFITS OF BUSINESS INTELLIGENCE TYPES OF BI TOOLS AND SOFTWARES ❖ Spreadsheets: Spreadsheets like Microsoft Excel and Google Docs are some of the most widely used BI tools. ❖ Reporting software: Reporting software is used to report, organize, filter, and display data. ❖ Data visualization software: Data visualization software translates datasets into easy-to- read, visually appealing graphical representations to quickly gain insights. ❖ Data mining tools: Data mining tools "mine" large amounts of data for patterns using things like artificial intelligence, machine learning, and statistics. ❖ Online analytical processing (OLAP): OLAP tools allow users to analyze datasets from a wide variety of angles based on different business perspectives. DATA VISUALIZATION TOOLS A.) Bar Chart is most used for demonstrating a comparison between two or more things. It is a tool that allows a manager to evaluate whether existing resources can handle work demand or whether activities should be postponed.  Page 3 of 4 B.) Gantt Chart is a graphical illustration of a scheduling technique. It highlights activities over the life of a project. It gives a quick picture of a project’s progress in terms of actual timelines and projected timelines. C.) Pie Chart is used to represent a 100% total of two or more items. It shows the portion of one item over the whole. D.) Line Chart is used to represent a trend between two or more items. It shows the movements of two variables across points in time.  Page 4 of 4 MULTIPLE CHOICE QUESTIONS 1. _________________ translates datasets into easy-to-read, visually appealing graphical representations to quickly gain insights. a. Spreadsheet Models b. Reporting software c. Data visualization software d. None of the above 2. ______________ allow users to analyze datasets from a wide variety of angles based on different business perspectives. a. Spreadsheet Models b. Reporting software c. OLAP d. Data Mining Tools 3. _____________ is collecting and analyzing internal data and external data to provide new insights that were not apparent before. a. Business Intelligence b. Data Analytics c. Data Visualization d. Data Mining 4. It is a tool that allows a manager to evaluate whether existing resources can handle work demand or whether activities should be postponed. a. Gantt Chart b. Pie Chart c. Bar Chart d. Line Chart 5. Which of the following statements is/are TRUE? Statement 1: Line Chart is used to represent a trend between two or more items. Statement 2: Gantt Chart is a graphical illustration of a scheduling technique. a. Only Statement 1 is true b. Only Statement 2 is true c. Both Statements are correct d. Both Statements are incorrect GOODLUCK, FEUture CIAs! ---END--- “Many of life’s failures are people who did not realize how close they were to success when they gave up” – THOMAS A. EDISON  Page 1 of 6 FAR EASTERN UNIVERSITY INSTITUTE OF ACCOUNTS, BUSINESS AND FINANCE DEPARTMENT OF ACCOUNTANCY AND INTERNAL AUDITING AUD1207 – INTEGRATED INTERNAL AUDITING REVIEW COURSES SECTION A - BUSINESS ACUMEN BA 03 – DATA ANALYTICS MR. CHRISTIAN ANDREI G. UTANES, CPA, CMA, MBA units NOTE TO STUDENTS: These handouts are of property of the reviewer. Unnecessary sharing and uploading of these materials are not allowed. LEARNING OBJECTIVES Upon completion of this chapter, you should be able to 1. Define and explain Big Data 2. Explain and understand the Data Life Cycle 3. Explain and understand the role of a Data Owner and a Data Steward 4. Identify the Sources of Big Data 5. Enumerate the Characteristics of Big Data 6. Identify the Risks in Big Data 7. Identify the Data Quality Standards 8. Define Data Analytics 9. Enumerate, identify and apply the various types of Data Analytics in day-to-day business environment. LECTURE NOTES BA 03.01 – BIG DATA Big Data means vast amount of data collected from a variety of sources. Big data is subjective, depending on the size and complexity of an organization. DATA LIFE CYCLE Data Life Cycle = Discover + Deploy “Discover” focuses on tasks such as prepare, explore and model “Deploy” on the other hand, it focuses on tasks such as implementation, action and evaluation  Page 2 of 6 A more detailed orientation of data life cycle includes: Data -> Analytics -> Insights -> Results -> Discussions “Data” refers to the collection and generation of data so that it can be processed. “Analytics” means cleansing, normalizing, aggregating, extracting and analyzing data. “Results” means improving decisions, actions and outcomes to realize new benefits. “Decision” means arriving at the appropriate course of action to solve a problem or answer a query Big data does not necessarily mean good data. Good data -> Good outcomes, good results, good decisions Bad data -> Bad outcomes, bad results, bad decisions DATA OWNER AND DATA STEWARD Data Owner is a person or department responsible for safeguarding or securing data with security controls, classifying data and defining data access rules. Data Steward or Data Custodian is a person, or department delegated the responsibility for managing a specific set of data resources. This person defines, specifies and standardizes the data assets of an organization within and across all functional areas. Big Data = Internal + External Data ->>> NEW OPPORTUNITIES Big Data -> Big Decisions Big Data -> New Insights -> New Strategies -> New Decisions -> New Actions Big Data = New Data Asset = New Strategic Asset Big Data -> Assurance Procedures and Consulting Services SOURCES OF BIG DATA A. STRUCTURED DATA Includes internal source documents such as sales order and invoices, purchase requests and orders, operating expenses, production and service records, materials and labor records, etc. B. UNSTRUCTURED DATA Includes external source documents which are commonly found on human languages, audio and video such as public online, search engines, private online and research websites, government agency websites.  Page 3 of 6 CHARACTERISTICS OF BIG DATA 7Vs OF BIG DATA 1. Volume – the amount of big data being created 2. Variety – comes from all forms and formats. This can include data generated within an organization as well as data created from external sources and publicly available data 3. Velocity – means that data is being generated extremely quickly and continuously 4. Veracity – means that data must be verified based on accuracy and content 5. Variability – means that big data is extremely variable and always changing 6. Visualization – means translating vast amounts of data into readily presentable graphics and charts that are easy to understand and are critical to end user satisfaction. 7. Value – means organizations, societies and consumers can benefit from the big data. RISKS IN BIG DATA ▪ Discovering wrong data and bad data leading to wrong and bad decisions ▪ Digging deeper into data, thus creating an “analysis paralysis” situation leading to a situation of being data analytics rich but information poor ▪ Proceeding with invalid data patterns and trends, assuming that they are valid patterns and trends thus wasting resources ▪ Lack of data governance standards leading to poor quality data and information ▪ Lack of data security DATA QUALITY STANDARDS For data to have quality, such data must possess the following characteristics: 1. Relevance 2. Accuracy 3. Credibility 4. Timeliness 5. Accessibility 6. Interpretability 7. Coherence  Page 4 of 6 BA 03.02 – DATA ANALYTICS Data Analytics involve applying quantitative and qualitative tools and techniques to big data to gain new insights and new opportunities. TYPES OF DATA ANALYTICS 1. Predictive Analytics 2. Descriptive Analytics 3. Prescriptive Analytics 4. Cognitive Analytics A.) Predictive Analytics is the process of estimating future outcomes based on the analysis of past data and or current data. They describe what could happen. B.) Descriptive Analytics described what already happened and included content analysis and context analysis. C.) Prescriptive Analytics helps management decide what should happen and thrive on big data. When faced with several potential decisions, prescriptive analytics analyze for the best possible outcome. D.) Cognitive Analytics use Artificial Intelligence (AI) as it applies to day-to-day business transactions. The AI group of technologies such as machine learning and natural language processors can provide clear insights into problems with greater confidence, speed and accuracy.  Page 5 of 6 MULTIPLE CHOICE QUESTIONS 1. In the following items, which of the following comes LAST in the data life cycle? a. Results b. Insights c. Data d. Discussions 2. Who is a data owner? a. is a person or department delegated the responsibility for managing a specific set of data resources. b. is a person or department responsible for safeguarding or securing data with security controls, classifying data and defining data access rules. c. this person defines, specifies and standardizes the data assets of an organization within and across all functional areas. d. None of the above 3. Includes internal source documents such as sales order and invoices, purchase requests and orders, operating expenses, production and service records, materials and labor records, etc. a. Unstructured Data b. Indistinct Data c. Structured Data d. Data formulation 4. This comes from all forms and formats. This can include data generated within an organization as well as data created from external sources and publicly available data a. Volatility b. Vial c. Volume d. Variety 5. Which of the following is NOT a Data Quality Standard? a. Relevance b. Accuracy c. Credibility d. Competency 6. SAMSUNG is analyzing its revenues from 2022 to 2024 and is at the objective of boosting sales for the current period. It used trend analysis and sensitivity analysis in projecting its 2025 revenues. What type of data analytics is illustrated? a. Predictive Analytics b. Prescriptive Analytics c. Descriptive Analytics d. Cognitive Analytics 7. APPLE reported a low employee turnover rate in 2022 to 2024 at an average of 5.1%. The HR manager is happy with the turnout of its policies and procedures, and it is hopeful that it will still improve. What type of data analytics is illustrated? a. Predictive Analytics b. Prescriptive Analytics  Page 6 of 6 c. Descriptive Analytics d. Cognitive Analytics 8. HUAWEI failed to account for its reworks for 2023 which led to $10 Million losses in that year. As a result, HUAWEI replaced its operations manager. What type of data analytics is illustrated? a. Predictive Analytics b. Prescriptive Analytics c. Descriptive Analytics d. Cognitive Analytics 9. VIVO decided to implement Robotics Process Automation (RPA) in the manufacture of its products. This led to efficiency and productivity hence, lowered production costs by 45% in 2024. What type of data analytics is illustrated? a. Predictive Analytics b. Prescriptive Analytics c. Descriptive Analytics d. Cognitive Analytics 10. Which of the following is/are TRUE? Statement 1: When discovering wrong data and bad data leading to wrong and bad decisions Statement 2: Managing big data in an organization is a task of an Internal Auditor a. Only Statement 1 is true b. Only Statement 2 is true c. Both Statements are correct d. Both Statements are incorrect GOODLUCK, FEUture CIAs! ---END--- “Many of life’s failures are people who did not realize how close they were to success when they gave up” – THOMAS A. EDISON