25343 Business Analytics Assignment

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Across
  1. 4. Point where total cost equals total revenue
  2. 5. Mathematical method to maximize or minimize objectives
  3. 6. R package for data visualization
  4. 9. Creative concepts generated during brainstorming
  5. 11. Preliminary balance of ledger accounts
  6. 14. Snapshot of assets, liabilities, and equity
  7. 15. Collaborative effort to achieve goals
  8. 19. Driving force behind individual performance
  9. 21. Drawing conclusions from sample data
  10. 24. Graph showing frequency distribution of data
  11. 26. Designing with user needs at the center
  12. 27. Satisfaction derived from consuming goods or services
  13. 29. Likelihood of outcomes in uncertain situations
  14. 31. Imitating real-world processes to assess outcomes
  15. 34. Structures for buying and selling goods
  16. 35. Visual summary of data spread and outliers
  17. 36. Strategic choices informed by data analysis
  18. 38. Early model used to test and refine solutions
  19. 39. Modeling relationships between variables
Down
  1. 1. Predicting future trends based on data
  2. 2. Managing transitions within organizations
  3. 3. Structuring problems to guide solution paths
  4. 7. Recommending actions based on predictive insights
  5. 8. Movement of money in and out of a business
  6. 10. Field combining statistics and computing to extract insights
  7. 11. Flowchart-like structure for decision-making
  8. 12. Summarizing historical data to identify patterns
  9. 13. Shared values and norms within an organization
  10. 16. Record of financial transactions in accounting
  11. 17. Disagreement requiring resolution in teams
  12. 18. Repeating cycles to improve solutions
  13. 20. Guiding and influencing team members
  14. 22. Responsiveness of demand or supply to changes
  15. 23. Data-driven decision-making process
  16. 25. Programming language used for statistical computing
  17. 28. Financial gain from business operations
  18. 30. Analyzing expenses to determine value
  19. 32. Understanding user needs and emotions
  20. 33. Forecasting future outcomes using data models
  21. 37. Removing errors and inconsistencies from data