RReporting & eporting & DData ata

VVisualization isualization CContest 2009ontest 2009

Industry Defined Problem

InRev || Aarohan 2k9 || NIT Durgapur

K Kirubakaran

id97767168 pdfMachine by Broadgun Software - a great PDF writer! - a great PDF creator! - http://www.pdfmachine.com http://www.broadgun.com

ObjectivesObjectives

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

Consumer Expenditure SurveyConsumer 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

Mapping files visMapping files vis--àà--vis series file vis series file

CX_SERIES

SERIES_ID

ITEM_CODE

TABLE_CODE

BEG_YEAR

END_YEAR COLUMN_CODE

DEFINES

CX_ITEM

ITEM_CODE

ITEM_TEXT

CX_COLUMN

CHARAC

TERIZES

COLUMN_CODE

TABLE_CODE

COLUMN_TEXT

CX_TABLE

CONTAINS

TABLE_TEXT

TABLE_CODE

CX_ECX_E--R diagramR diagram

CX_DATAFILE CX_SERIES

COMPRISES

SERIES_ID

VALUE

SERIES_ID

YEAR

ID

TABLE_CODE

BEG_YEAR

END_YEAR

ITEM_CODE

COLUMN_CODE

TechnologyTechnology

MS Excel (Pivot tables, charts, statistical

analysis)

Oracle 10g Express Edition (Database

handling)

Oracle Application Builder (Prototype

design)

MS Word (Report)

MS Powerpoint (Presentation)

AlgorithmAlgorithm

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

Algorithm Algorithm contdcontd��

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

DemographicsDemographics

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

Fourth 20 percent income quintile

Highest 20 percent income quintile

Lowest 20 percent income quintile

Second 20 percent income quintile

Third 20 percent income quintile

1984

1988

1992

1996

2000

2004

2007

Total no. of persons-

(No of CU in 1000s)

*(No of persons in

CU)

Quintiles of income

before taxes

Shylock calling�Shylock calling�

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

1984 1988 1992 1996 2000 2004 2007

Mortgage interest and charges - All Consumer Units

Mortgage interest and charges - Fourth 20 percent income quintile

Mortgage interest and charges - Highest 20 percent income quintile

Mortgage interest and charges - Lowest 20 percent income quintile

Mortgage interest and charges - Second 20 percent income quintile

Mortgage interest and charges - Third 20 percent income quintile

Mortgage interest and charges

Quintiles of income before taxes

Mortgage Mountain piled up Mortgage Mountain piled up

-7000 -6000 -5000 -4000 -3000 -2000 -1000 0

1984

1988

1992

1996

2000

2004

2007

Mortgage principal paid, owned property -Third 20 percent income quintile

Mortgage principal paid, owned property - Second 20 percent income quintile

Mortgage principal paid, owned property - Lowest 20 percent income quintile

Mortgage principal paid, owned property - Highest 20 percent income quintile

Mortgage principal paid, owned property - Fourth 20 percent income quintile

Mortgage principal paid, owned

property

Quintiles of income before taxes

Asset bomb tickingAsset bomb ticking

-5000

0

5000

10000

15000

20000

25000

30000

35000

1984 1988 1992 1996 2000 2004 2007

Fourth 20 percent income quintile

Highest 20 percent income quintile

Lowest 20 percent income quintile

Second 20 percent income quintile

Third 20 percent income quintile

Net Change in Total Assets

Quintiles of income before

taxes

AssetAsset--liability chemistry!liability chemistry!

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

1984 1988 1992 1996 2000 2004 2007

Net change in total assets

Net change in total liabilities

All Consumer Units

Living the silly high lifeLiving the silly high life

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

1991 1994 1997 2000 2004 2007

Highest 20 percent income quintile

Lowest 20 percent income quintile

-25000

-20000

-15000

-10000

-5000

0

5000

10000

1991 1994 1997 2000 2004 2007

Highest 20 percent income quintile

Lowest 20 percent income quintile

Net Change in

total liablities

Net Change in

total assets and

liablities

Caveman�s prideCaveman�s pride

0

1000

2000

3000

4000

5000

6000

7000

8000

1984 1987 1990 1993 1996 1999 2002 2005 2007

Other lodging

Owned dwellings

Rented dwellings

All Consumer

Units

Desperate caveman�s prideDesperate caveman�s pride

0 5 10 15 20 25 30 35 40 45 50

1984

1988

1992

1996

2000

2004

2007

Percent Renter

Percent Homeowner without mortgage

Percent Homeowner with mortgage

All Consumer Units

Housemouse�sHousemouse�s woeswoes

0

5000

10000

15000

20000

25000

Consumer units of two or more

persons, no earners

CUs of two or more persons, one

earner

CUs of two or more persons, three or more

earners

CUs of two or more persons, two

earners

Single Consumers, no earner

Single Consumers, one earner

1984

1988

1992

1996

2000

2004

2007

Housing

Number of earners

Incoming Vs. IndulgingIncoming Vs. Indulging

0

10000

20000

30000

40000

50000

60000

70000

1984 1987 1990 1993 1996 1999 2002 2005 2007

Money income before taxes

Total average annual expenditures

All Consumer Units

Dwelling Vs. IncomingDwelling Vs. Incoming

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

1984 1987 1990 1993 1996 1999 2002 2005 2007

Estimated market value of owned home

Money income before taxes

All Consumer Units

Financial Planning, the need of the Financial Planning, the need of the

hour hour

All Consumer Units

0

500

1000

1500

2000

2500

3000

3500

4000

4500

1984 1987 1990 1993 1996 1999 2002 2005 2007

Est. monthly rental value of owned home

Interest, dividends, rent income, property income

Mortgage interest and charges

Property taxes

InspirationInspiration

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