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Data reporting and visualization contest' 09

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This ppt was made by me for Industry Defined Problem organized by InRev Systems Pvt Ltd in Aarohan 2k9

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Data reporting and visualization contest' 09

  1. 1. Reporting & Data Visualization Contest 2009 Industry Defined Problem InRev || Aarohan 2k9 || NIT Durgapur K Kirubakaran
  2. 2. Objectives  To understand the structure of the cx.data file  Use any kind of technology to bring it to presentable form  Assumption of perspectives on the data provided  Report with some useful insights of the given data
  3. 3. Consumer Expenditure Survey  Mapping files-Series file-Datafile  Expenditure-Diary & Interview survey  Seasonally Unadjusted data  Income-Expenditure-Characteristics per CU classified by 14 groups  Avg Annual Expenditure- 14 categories
  4. 4. Mapping files vis-à-vis series file vis- ITEM_CODE BEG_YEAR TABLE_CODE TABLE_CODE END_YEAR COLUMN_CODE COLUMN_CODE COLUMN_TEXT SERIES_ID CHARAC CX_SERIES CX_COLUMN TERIZES DEFINES CONTAINS CX_ITEM CX_TABLE ITEM_TEXT TABLE_TEXT ITEM_CODE TABLE_CODE
  5. 5. CX_E- CX_E-R diagram ITEM_CODE BEG_YEAR VALUE YEAR TABLE_CODE END_YEAR COLUMN_CODE SERIES_ID ID SERIES_ID CX_SERIES CX_DATAFILE COMPRISES
  6. 6. Technology  MS Excel (Pivot tables, charts, statistical analysis)  Oracle 10g Express Edition (Database handling)  Oracle Application Builder (Prototype design)  MS Word (Report)  MS Powerpoint (Presentation)
  7. 7. Algorithm 1. Data imported for refinement in Excel Spreadsheet formats 2. Database created by drawing useful relationships among the given tables using Oracle Express 10g Edition technology 3. Additional tables created & data structure understood (for user sorted results) using SQL queries
  8. 8. Algorithm contd… contd… 4. Initial Data Reporting and Analysis using Excel based tools like pivot table and the application developed with Oracle Application Builder 5. Data Visualization using charts and required statistical functions & tools 6. Analytics generation based on perspectives and assumptions made by the team
  9. 9. Demographics 90000 Total no. of persons- (No of CU in 1000s) *(No of persons in 80000 CU) 70000 Quintiles of income before taxes 60000 1984 50000 1988 1992 40000 1996 2000 30000 2004 2007 20000 10000 0 Fourth 20 percent Highest 20 percent Lowest 20 percent Second 20 percent Third 20 percent income quintile income quintile income quintile income quintile income quintile
  10. 10. Shylock calling… 10000 9000 Mortgage interest and charges 8000 Quintiles of income before taxes Mortgage interest and charges - All 7000 Consumer Units Mortgage interest and charges - Fourth 6000 20 percent income quintile Mortgage interest and charges - Highest 5000 20 percent income quintile Mortgage interest and charges - Lowest 20 percent income quintile 4000 Mortgage interest and charges - Second 20 percent income quintile 3000 Mortgage interest and charges - Third 20 percent income quintile 2000 1000 0 1984 1988 1992 1996 2000 2004 2007
  11. 11. Mortgage Mountain piled up 2007 Mortgage principal paid, owned property 2004 Quintiles of income before taxes Mortgage principal paid, owned property - 2000 Third 20 percent income quintile Mortgage principal paid, owned property - Second 20 percent income quintile 1996 Mortgage principal paid, owned property - Lowest 20 percent income quintile Mortgage principal paid, owned property - Highest 20 percent income quintile 1992 Mortgage principal paid, owned property - Fourth 20 percent income quintile 1988 1984 -7000 -6000 -5000 -4000 -3000 -2000 -1000 0
  12. 12. Asset bomb ticking 35000 30000 Net Change in Total Assets 25000 Quintiles of income before taxes 20000 Fourth 20 percent income quintile Highest 20 percent income quintile 15000 Lowest 20 percent income quintile Second 20 percent income quintile Third 20 percent income quintile 10000 5000 0 1984 1988 1992 1996 2000 2004 2007 -5000
  13. 13. Asset- Asset-liability chemistry! 18000 16000 14000 12000 All Consumer Units 10000 Net change in total assets 8000 Net change in total liabilities 6000 4000 2000 0 1984 1988 1992 1996 2000 2004 2007
  14. 14. Living the silly high life 45000 10000 40000 5000 35000 Net Change in Net Change in total assets and 0 total liablities liablities 30000 1991 1994 1997 2000 2004 2007 Highest 20 Highest 20 25000 -5000 percent income percent income quintile quintile 20000 Lowest 20 Lowest 20 percent income percent income -10000 quintile quintile 15000 -15000 10000 5000 -20000 0 1991 1994 1997 2000 2004 2007 -25000
  15. 15. Caveman’s pride 8000 7000 6000 All Consumer 5000 Units Other lodging 4000 Owned dwellings Rented dwellings 3000 2000 1000 0 1984 1987 1990 1993 1996 1999 2002 2005 2007
  16. 16. Desperate caveman’s pride 2007 2004 All Consumer Units 2000 Percent Renter 1996 Percent Homeowner without mortgage Percent Homeowner with mortgage 1992 1988 1984 0 5 10 15 20 25 30 35 40 45 50
  17. 17. Housemouse’s woes 25000 Housing Number of earners 20000 1984 1988 15000 1992 1996 2000 2004 10000 2007 5000 0 Consumer units of CUs of two or CUs of two or CUs of two or Single Consumers, Single Consumers, two or more more persons, one more persons, more persons, two no earner one earner persons, no earners earner three or more earners earners
  18. 18. Incoming Vs. Indulging 70000 60000 50000 All Consumer Units 40000 Money income before taxes Total average annual expenditures 30000 20000 10000 0 1984 1987 1990 1993 1996 1999 2002 2005 2007
  19. 19. Dwelling Vs. Incoming 200000 180000 160000 140000 All Consumer Units 120000 100000 Estimated market value of owned home Money income before taxes 80000 60000 40000 20000 0 1984 1987 1990 1993 1996 1999 2002 2005 2007
  20. 20. Financial Planning, the need of the hour 4500 4000 3500 All Consumer Units 3000 Est. monthly rental value of owned home 2500 Interest, dividends, rent income, property income 2000 Mortgage interest and charges Property taxes 1500 1000 500 0 1984 1987 1990 1993 1996 1999 2002 2005 2007
  21. 21. Inspiration  http://www.f-cube.us/ ----- Data visualization  http://www.bls.gov/ ----- Table creation  http://scoop.in-rev.com/ ------ Data reporting  http://bigpicture.typepad.com/ --- Analytics  http://ttrammohan.blogspot.com – Analytics  http://www.ritholtz.com/ ----- Analytics

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