7 Ideas on Encouraging
Advanced Analytics
Mark Tabladillo Ph.D.
Microsoft MVP, SAS Expert; Trainer & Consultant, SolidQ
Ju...
Abstract
Many companies are starting or expanding their use of data mining and machine
learning. This presentation covers ...
MarkTab
Microsoft MVP
SAS Expert
Trainer & Consultant
Data Scientist
Associate Faculty – University of Phoenix
(School of ...
Premise
Advanced Analytics promises to handle the common challenges facing organizations
How do we respond to: Volume, Vel...
Scientific Method
Baseline = Null Hypothesis
Alternative = Alternative Hypothesis
Questions:
Is there evidence to reject t...
Seven Areas
Advanced Analytics promises to handle the common challenges facing organizations
1-3 How do we respond to: Vol...
Volume
Baseline: Ignore it
Alternative:
Technology (flat files, tape, CSV  Hadoop)
Sampling
Velocity
Baseline: Ignore it
Alternative
Streaming (StreamInsight)
Sampling
Variety
Baseline: Ignore it
Alternative:
Different database types
SQL
NoSQL: Excel, Power Pivot, OLAP, Graph, HDInsight, H...
Achieving Rapid Analytics
Baseline: IT (Information Technology) produces, business units consume
Alternative:
Business Uni...
Developing Technology
Baseline: Let the vendors do it
Alternative
Build it
Virtual Machines: Cloud, On Premise, Hybrid
Dev...
Obtaining Talent
Baseline: Ignore the issue
Alternatives
Buy
Rent
Create
Lead
Stories
Baseline 1: internal focus because we’re just like everyone else
Baseline 2: the whole world is unique with no uni...
One Book to Read
Thomas Kuhn: The Structure of Scientific Revolutions
Tommy Lasorda, Manager LA Dodgers
You can make it happen
You can let it happen
Or you can wonder, what happened?
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7 ideas on encouraging advanced analytics

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Many companies are starting or expanding their use of data mining and machine learning. This presentation covers seven practical ideas for encouraging advanced analytics in your organization.

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7 ideas on encouraging advanced analytics

  1. 1. 7 Ideas on Encouraging Advanced Analytics Mark Tabladillo Ph.D. Microsoft MVP, SAS Expert; Trainer & Consultant, SolidQ July 17, 2014
  2. 2. Abstract Many companies are starting or expanding their use of data mining and machine learning. This presentation covers seven practical ideas for encouraging advanced analytics in your organization.
  3. 3. MarkTab Microsoft MVP SAS Expert Trainer & Consultant Data Scientist Associate Faculty – University of Phoenix (School of Advanced Studies) @marktabnet Linked In http://marktab.net
  4. 4. Premise Advanced Analytics promises to handle the common challenges facing organizations How do we respond to: Volume, Velocity, Variety How do we achieve rapid analytics How do we develop technology How do we obtain more skilled analysts and data scientists How do we tell stories
  5. 5. Scientific Method Baseline = Null Hypothesis Alternative = Alternative Hypothesis Questions: Is there evidence to reject the null hypothesis? How do you know that? So what? Epistemology: Science relies on presuppositions
  6. 6. Seven Areas Advanced Analytics promises to handle the common challenges facing organizations 1-3 How do we respond to: Volume, Velocity, Variety 4 How do we achieve rapid analytics 5 How do we develop technology 6 How do we obtain more skilled analysts and data scientists 7 How do we tell stories
  7. 7. Volume Baseline: Ignore it Alternative: Technology (flat files, tape, CSV  Hadoop) Sampling
  8. 8. Velocity Baseline: Ignore it Alternative Streaming (StreamInsight) Sampling
  9. 9. Variety Baseline: Ignore it Alternative: Different database types SQL NoSQL: Excel, Power Pivot, OLAP, Graph, HDInsight, Hadoop Sampling
  10. 10. Achieving Rapid Analytics Baseline: IT (Information Technology) produces, business units consume Alternative: Business Units share production and consumption with Information Technology Approach: Learn the business, work on better data
  11. 11. Developing Technology Baseline: Let the vendors do it Alternative Build it Virtual Machines: Cloud, On Premise, Hybrid Development Environments D = Development R&D = Research and Development
  12. 12. Obtaining Talent Baseline: Ignore the issue Alternatives Buy Rent Create Lead
  13. 13. Stories Baseline 1: internal focus because we’re just like everyone else Baseline 2: the whole world is unique with no unifying patterns Alternative Technology conferences Industry conferences Benchmarking Eric Siegel: Predictive Analytics
  14. 14. One Book to Read Thomas Kuhn: The Structure of Scientific Revolutions
  15. 15. Tommy Lasorda, Manager LA Dodgers You can make it happen You can let it happen Or you can wonder, what happened?

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