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

1. Reporting & Data
Visualization Contest 2009
Industry Defined Problem
InRev || Aarohan 2k9 || NIT Durgapur
K Kirubakaran

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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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