Investigative Analytics

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Investigative Analytics Data science for
everybody Curt A. Monash, Ph.D. President,
Monash Research Editor, DBMS2 contact
_at_monash.com http//www.monash.com http//www.DBMS2
.com
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Agenda

• Six aspects of analytic technology
• Investigative analytics
• Uses
• Tools
• Pitfalls

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Six things you can do with analytic technology

• Make an immediate decision.
• Plan in support of future decisions.
• Research, investigate, and analyze in support of
  future decisions.
• Monitor whats going on, to see when it necessary
  to decide, plan, or investigate.
• Communicate, to help other people and
  organizations do these same things.
• Provide support, in technology or data gathering,
  for one of the other functions.

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Investigative analytics
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Investigative analytics defined

• Seeking patterns in data via techniques such as
• Statistics, data mining, machine learning, and/or
  predictive analytics.
• The more research-oriented aspects of business
  intelligence tools.
• Analogous technologies as applied to non-tabular
  data types such as text or graph.
• where the patterns are previously unknown.
• Source http//www.dbms2.com/2011/03/03/investigat
  ive-analytics/

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Analytic progression

• Trends ?
• Correlations ?
• Decisions
• Source http//xkcd.com/552/

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Core drivers for investigative analytics

• The big three
• Make a better offer
• Make a better product
• Diagnose a problem
• And more
• Trading, inventory, logistics, science

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Make a better product (or service)

• Discover what people care (or dont care) about
• Uncover flaws (and their root causes)
• Test, test, test

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Detect and diagnose problems

• Manufacturing (classic)
• Manufacturing (modern)
• Customer satisfaction
• Network operation
• Bad actors
• Terror
• Fraud
• Risk

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And more

• Inventory optimization
• Distribution planning
• Algorithmic trading
• The risk analysis revolution
• Science

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The prerequisite -- capturing data

• Transactions
• Loyalty cards
• Credit cards
• Logs
• Sensors
• Communications metadata
• Communications content
• Data is the food for analytics

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Two aspects of investigative analytics

• Monitoring and sifting data
• Exciting because its Fast, Fast, Fast!!
• and has cool visuals
• Serious math
• Geek supremacy
• See also Big, Big, Big!!!

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Monitoring and sifting data

• Cool dashboards
• Drilldown and query from those cool dashboards

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Serious math

• Statistics, which overlaps with
• machine learning
• Graph theory
• Monte Carlo simulation
• Maybe more?

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Investigative analytics concerns

• The future may not be like the past
• Dont ignore what you cant measure
• Privacy

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Illumination? Or just support?