dst lecture 03_multidimensional data analysis.pdf
TRANSCRIPT
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Module Outline
Management Decision-Making
Multi-Dimensional Data Analysis
Stair, Reynolds & Chesney 124-125 & 219-221
Group and Executive Support Systems
Model-based Decision Support Systems
Intelligent Systems
Knowledge Management
Managing Decision Support Tools
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Business Intelligence (BI)3
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What is Business Intelligence?4
Business Intelligence is
A broad category of applications and technologies forgathering, storing, analysing, and providing access to
data, to help enterprise users make better business
decisions.
BI applications include the activities of decision support
systems, query and reporting, online analytical
processing (OLAP), statistical analysis, forecasting, and
data mining.
Definition from TechTarget.com
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Relate BI to decision support5
Intelligence stage (of decision-making)
Becoming aware of the problem (or opportunity) Defining the problem details and scope
Design stage
Identifying alternative solutions Evaluating feasibility of each solution
Choice stage
Deciding on the best solution
Internal or external data? Actual or estimated values?
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Knowledge Discovery7
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Multi-dimensional data analysis8
OLAP and Data Mining
Explores the relationship between multiple variables
Usually at least three variables involved
Relies on large data sets Usually has a time component
Graphical display aids understanding
Identifies patterns occurring in data
Can provide a basis for developing mathematical
models
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On-Line Analytical Processing (OLAP)
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Initiated by users
Reveals relationships between data items
Detects trends
Clarifies problem definition
Easy to use
Visual interface
Flexible
Drill-down
NOT done on operational database
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Example of OLAP output10
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Slice and dice views11
Different people may have
different interests in the
same dataset
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OLAP vs standard DBMS queries12
Quick to compose, run and modify
No programming skills needed
Visual output is more user friendly
Key measures are already calculated
OLAP structure can be used to build models (e.g.
financial)
Can provide input to other applications (e.g.
performance management)
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Equivalent Excel functions13 Pivot tables
Pivot charts
Statistical analysis
Correlation
Multiple regression
Analysis of variance
Cluster analysis
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18 months & R10 million15 The business value of Supply Chain Intelligence enabled
by a Global Procurement Intelligence solution would bederived through: The ability to identify, measure, manage and report
procurement spend, price and consumption variances, trendsand cost pressures across the group as well as by providing
contract and vendor spend visibility; The ability to drive group cost optimisation through best
practice sourcing strategies;
Risk identification and mitigation capability;
Visibility and standardisation of consolidated spend andrelated policies; and
Data consolidation across the group, aligned to budgets andexpenditure forecasts.
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Moving on to Data Mining16
Automated process to extract information from
large data setsOnly as effective as the data it uses
Relies on advanced logical, statistical and
mathematical techniques
Infers rules and relationships that allow the
prediction of future results
But cant explain underlying reasons
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How is data mining being used in SA?
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CRM and direct marketing
Customer and product planning
Fraud detection
Credit scoring
Benefits include:
Customer attraction and retention
Product design Bad debt reduction
Bank robbery prediction
Product cross-selling
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Comparing OLAP and data mining18
Characteristic OLAP Data Mining
Purpose Supports data analysis and
decision making
Supports data analysis and
decision making
Type of analysissupported
Top-down, query-driven dataanalysis
Bottom-up, discovery-drivendata analysis
Skills required
of user
Must be very knowledgeable
about the data and its
business context
Must trust in data mining
tools to uncover valid and
worthwhile hypotheses
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Web mining
Web Content Mining
Extraction of information from documents and databases
Web Structure Mining
Link structures within the Internet, most frequently visited
paths etc
Web Usage Mining
Analyses data from the actions of Internet users (web
and proxy server logs, user sessions, user profiles,registration data, cookies, bookmarks, mouse clicks etc.)
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And thats all for today20