BUSINESS INTELLIGENCE

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BUSINESS INTELLIGENCE FOR DECISION SUPPORT
SYSTEMS P LENIN TECHNICAL DIRECTOR NATIONAL
INFORMATICS CENTRE MINISTRY OF COMMUNICATION
IT NEW DELHI -110 003.

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• Why Now, Not Then?

• DATA AVAILABILITY
• MASSIVE AMOUNT /ELECTRONIC FORM
• WIDESPREAD USE OF APPLN SYSTEMS
• POWERFUL H/W, PARALLEL SYSTEMS
• NEW S/W TECHNOLOGY

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DEMAND FOR DATA

Growing gap
Growth in user demand
IS ability to deliver
Source Gartner Group
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ER MODEL
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WHY BUSINESS INTELLIGENCE SOLUTIONS ?
BI SYSTEMS ? NOT A REPLACEMENT FOR RDBMS/OLTP
? TO COMPLEMENT RDBMS/OLTP SYSTEMS
? FOR PLANNERS AND DECISION MAKERS USE
WHEREVER AND WHENEVER /WEB BASED MINIMUM
DEPENDENCY ON IT PROFESSIONAL EXTRACT IMPLICIT
KNOWLEDGE/PATTERN
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WHY BI/ DATA WAREHOUSE?

• -NEED OF INFORMATICS REQUIREMENT IS DYNAMIC
• -ALSO NEED OF EVERY DEPTT VARIES
• SECRETARY/COMMISSIONER/JT.COMM/DY.COMM.
• -INTEGRATED/SHARED INFORMATION
• DESIGN NOT SUITABLE FOR BUSINESS ANALYSIS
• LIMITED ANALYSIS
• DATA CONTENT CHANGES
• VIEWS BASED ON OBJECTIVES
• REASONING EX. PDS PUNJAB/ORISSA

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WHY BI TECHNOLOGY?
- TO HANDLE DATA FROM MUTI-SOURCE - TO HANDLE
LARGE VOLUME OF DATA - MULTIDIMENSIONAL DRILL
THRU-ANALYSIS - PRESERVE AND USE THE HISTORICAL
DATA - TO EXTRACT HIDDEN KNOWLEDGE/PATTERN - TO
DO AD HOC QUERY
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WHAT BENEFITS YOU GET OUT OF DW?

• EASIER FOR END USERS TO NAVIGATE,
• UNDERSTAND AND QUERY
• ENABLE QUERIES THAT CUT ACROSS
• DIFFERENT SEGMENTS
• COMPLEX QUERY IN NORMALIZED DB
• CAN BE BUILD EASILY
• EFFICIENT WAY TO MANAGE AND REPORT
• PROVIDES THE CAPABILITY TO ANALYZE LARGE
• AMOUNT OF HISTORICAL DATA

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Data Warehouse

• W H INMON,
• A DW IS A
• SUBJECT ORIENTED (Vs APPLN. ORIENTED),
• INTEGRATED,
• TIME VARIANT (HISTORICAL vs. CURRENT),
• NONVOLATILE (STABLE vs. CONTINUOUS CHANGE)
  
• COLLECTION OF DATA IN SUPPORT OF MANAGEMENTS
• DECISION MAKING PROCESS.
• Maintained separately from the organizations
  operational
• database

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A SAMPLE DATA CUBE /DIMENSION MODEL
Total annual sales by country and product
Date

2Qtr
1Qtr
sum
3Qtr
4Qtr
TV
Product
U.S.A
PC
DVD
sum
CHINA
Country
Total of all item sales in all countries by
product
Total of all product sales by country and quarter
INDIA
sum
Total annual sales of all items by Country
Total annual sales.
Total of all product sales in all countries by
quarter
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CARS SOLD
ORDER
DATE
NO
SANTRO
MARUTI
1
08/08/04
5
2
2
3
0
3
2
6
2
2
4
5
3
3
7
09/08/04
1
3
1
2
2
4
0
3
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NO OF RECORDS REDUCED BY AGGREGATION
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Transformation of Data
Information
Warehouse
Data
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Basic elements of Data warehouse
DATASTAGING AREA
OPERATIONAL SOURCE SYSTEM
DATAPRESENTATION AREA
DATAACCESSTOOLS
Services Clean, combine, and standardizeConform
DimensionsNo user query services Data
Store Flat files and relational
tables Processing Sorting and sequential
processing
Data Mart 1 DimensionalAtomic and summary
dataBased on a single business process
Ad hoc query tools Report Writers Analytical
Applications Modeling Forecasting Scoring Dat
a Mining
Extract
Load
Access
DW BusConformed facts and dimensions
Extract
Data Mart 2 Similar design
Extract
Load
Access
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METADATA
METADATA
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THE OLAP SOLUTION
A PROCESS OF FAST ANALYSIS OF SHARED
MULTIDIMENSIONAL INFORMATION --ENTERPRISE-WIDE
DATA ANALYSIS

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OLAP
- FAST ? - WHAT ANALYSIS? - SHARED -
MULTIDIMENSIONAL ON ENTERPRISE-WIDE DATA VIEW
FROM DIFFERENT ANGLE
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Drill-down Process (Browsing)
What all with OLAP?
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BI SYSTEMS DEVELOPMENT IN NIC

• SOCIO ECONOMIC DATA OF UP
• BHOOMI LAND RECORDS
• IRRIGATION SURVEY DATA
• SPECIAL FRAUD INVESTIGATION
• FERTILIZER PROD/MOVT/CONSUMPTION
• EXPORT/IMPORT OF MAJOR COMMINDEXES
• FOR RIS/COMMERCE MIN.
• CUSTOMS IMPORT
• --- ALL AT NIC
  HQR.

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BI SYSTEMS DEVELOPMENT IN NIC

• STATE UNITS
• KERALA
• Treasury Expenditure
• Sub-Reg Office Stamp Duty Collection
• Civil Supplies Office Expense
• Disease survelliance
• TAMIL NADU
• Child Labour
• Education
• MAHARASHTRA/PUNE
• ANDHRA PRADESH
• GUJARAT

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CUSTOMS IMPORT DATA
LIMITED INPUT CUSTOMS IMPORT DATA
ITEM LEVEL DATA Bill of Entry, Assessment
value, Duty, Duty Foregone, CTH, CETH, BCD
NOTFN, . 20 SITES ONLY TIME RANGE APRIL
2003 TO DEC. 2004 DATA SIZE 1.45 Cr RECORDS
5GB
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NIC DW ARCHITECTURE
DATA SOURCE
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BI FOR BHOOMI LAND RECORDS

• TO DEMONSTRATE THE POWER OF BI TECH
• JOINT EFFORT BY AM DIV AND NIC-KSU
• NIC KSU DOMAIN EXPERT
• AM DIV AS BI TECH EXPERT
• FOR KANNADA LANGUAGE TOOK ASSISTANCE
• FROM KEYSOFT

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BI SYSTEM PLAN FOR KSU STATE

• USE THE HW/SW FACILITIES AT THE HQRS.
• KEEP THE DATA AT KSU SERVER AND USE HQR
• FACILITIES FOR SW
• HAVE BOTH HW AND SW IN THE KSU SERVER