What is Business Intelligence , Essays (high school) of Artificial Intelligence

Download What is Business Intelligence and more Essays (high school) Artificial Intelligence in PDF only on Docsity! T.M.S.Yasara BTBM0322010484 1 Higher National Diploma in Business Course Tittle Pearson BTEC Level 5 Higher National Diploma in Business Unit Number and Title: Unit 57: Business Intelligence Assignment Title Understanding the importance and application of Business Intelligence. Name of the Learner T.M.S.Yasara Centre Ref. No of The Learner Pearson Regd. No. 6980 Assignment Number 01 Batch No & Semester Batch 03 Semester 04 Issue Date 5th January 2024 Submission Date 23rd January 2024 Re-submission Date Date Received 1st submission Unit Assessor: Ms.Duleesha Manohari Academic Year 2024 Assessor Summative Feedback Grade: Assessor Signature: Date: Resubmission Feedback - Formative Grade: Assessor Signature: Date Internal Verifier’s Comments T.M.S.Yasara BTBM0322010484 2 Signature of the IV Date Student Agreement: Student Signature Date STUDENT ASSESSMENT SUBMISSION AND DECLARATION Student name: T.M.S.Yasara Assessor name: Issue date: Submission date: Submitted on: Programme: PEARSON BTEC Unit: Assignment number and title: Student Declaration 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 signature: BTBM0322010484 Date: 10/01/2024 T.M.S.Yasara BTBM0322010484 5 Task 01 P1 - Examine using examples, the terms ‘Business Process’ and ‘Supporting Processes’.  Many business procedures and supporting procedures are necessary in the health insurance sector to guarantee the insurance company's seamless operation and the delivery of high-quality services to policyholders. Business Processes: 1. Claims processing - The system that handles claims becomes essential to business operations when an insured person asks for compensation for medical costs. This include the insured party submitting documentation to the insurance company, the claim being reviewed, the coverage being confirmed, and the eligible expenses being paid. It is an essential business procedure, for instance, if a policyholder has surgery, submits medical bills, and the insurance company processes and pays for the insured portion of those charges. 2. Underwriting - The practice of assessing insurance applications to ascertain the risk associated with providing coverage to a person or organization is known as underwriting. When determining coverage and premium rates, insurers consider a number of characteristics, including age, lifestyle, medical history, and pre- existing diseases. For example, an insurer looks over a policyholder's medical data and establishes coverage eligibility and premium amounts based on risk assessment. 3. Policyholder Management - Information about policyholders, billing, and customer service are all managed through this method. In order to fulfil this role, one must manage premium payments, handle policy renewals and terminations, keep accurate records, and respond to policyholder inquiries. The customer service personnel of the insurer handle encounter such as when a policyholder needs to update their contact information or has inquiries regarding coverage. Supporting processes 1. IT Infrastructure and Systems - IT systems play a major role in the management of policyholder data, claims processing, billing, and communication T.M.S.Yasara BTBM0322010484 6 within the health insurance sector. Maintaining and updating these systems to make sure they are safe, effective, and able to manage the enormous volume of data related to insurance activities is part of the supporting procedures in this field. 2. Compliance and Regulatory Affairs - It is critical to guarantee adherence to healthcare laws, rules, and industry standards. Regulatory reporting requirements, putting in place the appropriate compliance procedures, keeping an eye on legislative changes, and monitoring and adjusting supporting processes are all part of this field. For example, remaining current with changes in healthcare laws and altering policies and procedures accordingly to meet with new rules. 3. Actuarial and Risk Management - The key supporting procedures in health insurance are actuarial computations and risk management techniques. Actuaries determine premium rates, estimate future liabilities, and evaluate risk using statistical models. To forecast healthcare expenses and guarantee the company's financial stability, they do data analysis. Actuaries might, for instance, use past health data analysis to project future expenses related to a specific disease or course of treatment. M1 - Compare and contrast structured data and unstructured data. Briefly explain structured and unstructured data sources in Health insurance industry (Differentiate between unstructured and semi-structured data in an organization). Structured Data Definition - Using a predetermined schema or model, structured data is formatted and arranged. Relational databases are usually used to store it, and standardized languages like SQL make it simple to query. It is also highly organized. Characteristics  Arranged according to columns and rows.  Ideal for analysis using numbers. T.M.S.Yasara BTBM0322010484 7 Use in Health Insurance  Databases comprising policyholder data, claims data with defined fields (such as procedure codes and diagnostic codes), and tables detailing coverage details are examples of structured data in the health insurance industry. Unstructured Data Definition - Data that is not structured does not follow a set structure and does not have a predetermined data model. Although it can be more adaptable, organizing and analyzing it can be challenging. Characteristics  Not stated in advance.  Suitable for qualitative interpretation and analysis. Use in Health Insurance  Free-form medical notes, communications between healthcare professionals, client feedback, and multimedia materials like medical photos and videos are all considered unstructured data in the context of health insurance. Structured Data Sources in Health Insurance 1. Policyholder Databases - Organised databases that hold data on insured people, such as personal information, coverage options, and payment history. 2. Provider Networks - Databases that organise details such as specialisations, locations, and affiliations of healthcare professionals. Unstructured Data Sources in Health Insurance 1. Medical Records - Medical notes, narrative summaries of patients' ailments, and other unstructured clinical data are examples of unstructured data sources, such as electronic health records (EHRs). T.M.S.Yasara BTBM0322010484 10 Functionality - Gives users the ability to build and run queries, produce reports, and view data visually. 2. ETL (Extract, Transform, Load) Tools Examples - Informatica, Microsoft SQL Server Integration Services (SSIS). Functionality - Makes it easier to load, manipulate, and extract data from source systems into the data warehouse. 3. Dashboards and Scorecards Examples - Tableau, Microsoft Power BI. Functionality - Combines visuals and key performance indicators (KPIs) into a single view to provide rapid insights. 4. Predictive Analytics Examples - SAS Predictive Analytics, IBM Watson Analytics. Functionality - Makes use of machine learning methods and statistical algorithms to predict future patterns and results. P2 & M2 - Compare and contrast a range of information systems and technologies that can be used to support organisations at operational, tactical. (Compare and contrast at least 3 techniques and technologies that support the selected organisations at operational, tactical and strategic levels). Selected Organisation – Sysco Labs IT Firm 1. Operational Level a) Robotic Process Automation (RPA) Description - RPA automates repetitive, rule-based operations with software robots. Pros – o Simplifies repetitive operations, such processing and data entry. o lowers error rates and raises operational effectiveness. Cons – T.M.S.Yasara BTBM0322010484 11 o Restricted to assignments with distinct guidelines and procedures. b) Collaboration Tools (e.g., Slack) Description - Collaboration technologies promote real-time communication and coordination among team members. Pros – o Facilitates better information exchange and communication. o Supports fast decision-making at the operational level. Cons – o Information overload may result from a reliance on digital communication that is excessive. (c) Cloud-Based Enterprise Resource Planning (ERP) System Description - ERP solutions that are hosted in the cloud centralize, optimize, and offer real-time data access. Pros – o Allows collaboration and remote access. o Requires less substantial on-premise infrastructure and is scalable. Cons – o Dependability of access to the internet. 2. Tactical Level 1. Business Intelligence (BI) Analytics Platform (e.g., Tableau) Description - BI solutions assist in data analysis and visualization to produce insights that may be used to make decisions. Pros – o Enables tactical decision-making based on facts. o Facilitates trend analysis and ad hoc reporting. T.M.S.Yasara BTBM0322010484 12 Cons – o For efficient use, trained staff could be needed. 2. Customer Relationship Management (CRM) System (e.g., Salesforce) Description - CRM programs oversee consumer contacts and offer information that helps with tactical choice-making. Pros – o Boosts client happiness and engagement. o Allows for more focused sales and marketing initiatives. Cons – o It could be necessary to make considerable organisational changes in order to implement. 3. Project Management Tools (e.g., Jira) Description - Tools for project management facilitate the planning, monitoring, and cooperation of projects. Pros – o Enhances task organization and collaboration. o Gives tactical decision-makers information into the status of the project. Cons – o Needs team members to provide regular updates and input. 3. Strategic Level (a) Artificial Intelligence (AI) and Machine Learning (ML): Description - In order to find patterns, trends, and make predictions, AI and ML systems examine huge datasets. Pros – T.M.S.Yasara BTBM0322010484 15 customers by customizing its services based on an understanding of their requirements and behaviors. 3) Trend Analysis and Forecasting Reasoning: Key Feature - Predictive Analytics Example - For instance, Sysco Labs can forecast future market demands and technological preferences by examining previous data on technology trends. Making strategic decisions on the creation of new services or improvements to current ones is made possible by this. 4) Operational Efficiency Reasoning: Key Feature - Real-time Reporting Example - As an illustration, Sysco Labs may track operational data, such server performance, code deployment success rates, and system outages, in real- time by utilizing business intelligence tools. Efficient retrieval of this data facilitates timely decision-making to guarantee system dependability and operational effectiveness. 5) Competitive Advantage Reasoning: Key Feature - Competitive Intelligence Example - Sysco Labs can obtain and evaluate information on rivals' technological stacks, market strategies, and customer satisfaction with the aid of business intelligence (BI) procedures. By enabling Sysco Labs to develop and adapt in response to market trends and rival vulnerabilities, this intelligence gives the company a competitive advantage. Task 03 P3 - Determine, with examples, what business intelligence is and the tools and techniques associated with it. Definition of the MS Power BI - The technologies, procedures, and instruments used by businesses to gather, combine, process, evaluate, and display business data in order to facilitate T.M.S.Yasara BTBM0322010484 16 decision-making are collectively referred to as business intelligence, or BI. By transforming unstructured data into insightful and useful knowledge, business intelligence (BI) aims to empower organizations to make strategic and well-informed decisions. BI Tools and Techniques 1. Query and Reporting Tools Examples - Microsoft Power BI, Tableau Functionality - Gives users the ability to build and run queries, produce reports, and view data visually. 2. ETL (Extract, Transform, Load) Tools Examples - Informatica, Microsoft SQL Server Integration Services (SSIS). Functionality - Makes it easier to load, manipulate, and extract data from source systems into the data warehouse. 3. Dashboards and Scorecards Examples - Tableau, Microsoft Power BI. Functionality - Combines visuals and key performance indicators (KPIs) into a single view to provide rapid insights. 4. Predictive Analytics Examples - SAS Predictive Analytics, IBM Watson Analytics. Functionality - Makes use of machine learning methods and statistical algorithms to predict future patterns and results. 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. Sales Dashboard creation https://drive.google.com/file/d/1NSEtfbcFZbE5hxU4VoLPJvpVhoBsdDJ8/view?usp=sharing T.M.S.Yasara BTBM0322010484 17 M3 & D3 - Customise and 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.  According to the data analysis, there are some improvements need to customise the design of the Sales Dashboard. 1. Simplify the design: It appears busy and overpowering as it is now. To make it easier to browse for information, try adding extra whitespace between sections. Another option is to combine similar metrics into smaller tabs or dashboards. 2. Maintain uniform formatting: The dashboard's usage of several fonts, colors, and chart styles can give the impression that it is cluttered and amateurish. Decide on a theme and use it across the dashboard. Users will find it simpler to comprehend and evaluate the data as a result. 3. Incorporate interaction: The dashboard's static state may deter people from using it as much. To enable visitors to go further into the data, provide interactive features like drilldowns, tooltips, and filters. 4. Employ KPI Cards: Emphasize important metrics by incorporating Key Performance Indicator (KPI) cards. For a rapid evaluation of performance, show actual values compared to target values. 5. User Guide: Write a brief user manual or guide explaining each visualisation's function and the proper way to utilize the dashboard. Critically review the design of the Dashboard in terms of how it meets the business requirement of “Amazon Sales”  Factors including real-time updates, data accuracy, security, and privacy should all be considered when assessing a dashboard's suitability for fulfilling business objectives. 1. Real-Time Updates:  Timeliness: Updates in real-time or almost real-time are critical for Amazon sales. To facilitate quick decision-making, make sure the dashboard displays the most recent sales data. 2. Data Accuracy: T.M.S.Yasara BTBM0322010484 20  Ownership Rights: Clearly state who owns the data and make sure that the terms and conditions outlined in data ownership agreements are followed while using BI tools. Legal repercussions could result from the unauthorized use of data. How Keells Super, Arpico and Cargill’s Food city may use BI tools to enhance their operations:  Using Microsoft Power BI tools or Tableau tools organisations can enhance their operations. Such as: 1. Data Integration and Centralization: Businesses frequently combine data from multiple sources, including sales, inventory, and customer information, using business intelligence technologies. A more complete picture of the company is made possible by centralizing this data, which aids in improved decision-making. 2. Inventory Management: For supermarkets, effective inventory management is essential. Stock levels can be optimized, carrying costs can be decreased, and stockouts and overstocks may be avoided with the use of BI tools. Demand may be predicted using predictive analytics, and inventory can be planned appropriately. 3. Supply Chain Optimization: From procurement to distribution, BI solutions support the tracking and analysis of the complete supply chain. Reduced lead times, enhanced vendor control, and cost reductions are all possible with increased supply chain insight. 4. Risk Management: Features for risk management and evaluation may be present in BI tools. They can assist in locating any hazards in the supply chain and operations. Proactive risk mitigation may be made possible by early detection of abnormalities or departures from predicted patterns. D4 - Evaluate how organisations could use business intelligence to extend their target audience and make them more competitive in the market, taking security legislation into consideration.  Tools for business intelligence (BI) are essential for developing marketing plans that work for companies, particularly those in the retail sector. BI tools can be applied to target marketing and market expansion while taking data security and privacy policies into account. Here's how: T.M.S.Yasara BTBM0322010484 21 1. Customer Segmentation: Customer data may be analysed by BI systems to create segments based on preferences, purchasing patterns, demographics, and other pertinent variables. Retailers can increase the efficacy of their targeted efforts by customizing deals and marketing messaging for client segments thanks to this segmentation. 2. Expanding Target Market:  BI technologies have the capacity to reveal information on unexplored markets and customer segments with room for expansion. Retailers can find ways to broaden their target market and attract new client demographics by examining market trends, rival strategies, and consumer preferences. 3. Transparent Data Practices:  Retailers should have transparent data policies, explaining to consumers how their data will be used and giving them the choice to participate or not participate in data-driven marketing campaigns. 4. Predictive Analytics for Targeting:  Predictive analytics-enabled business intelligence (BI) solutions can predict consumer behavior and pinpoint possible high-value clients. To increase client lifetime value, retailers can then specifically target these customers with special offers, loyalty plans, or promotions. Bibliography 1. Roland Mosimann, Patrick Mosimann, and Meg Dussault. The Performance Manager. Cognos, Inc., 2007 2. “Performance Management” presentation, Meg Dussault, October 2009. 3. Cindi Howson. Successful BI Survey: Best Practices in Business Intelligence for Greater Business Impact. BIScorecard, November 2009. 4. Organization of Business Intelligence. Business Applications Research Center, August 2008. Appendices lil More Inet Modeling = View Cptimze —IIelp Format Data Dril G ~ (is e8 Pat |u| scuba Seletin Ps oe S@ Visualizations > Data » = By ica ie d= 2 al EMENEM bh MB bt HFEOOR evAaan — HBIGrry E€SAGR GRROD vue batty Fuliren TE index ‘Sim ofsip-possto. ont stic-sate vx ant simolamwt Da cu Cosseegor Kepuliis QD sed dritioghf8sshare | Rge2of2 +H r na ene Ja Figure 01 — Sales Dashboard T.M.S.Yasara BTBM0322010484 22