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. 7 Ideas on Encouraging Advanced Analytics Mark Tabladillo Ph.D. Microsoft MVP, SAS Expert; Trainer & Consultant, SolidQ July 17, 2014
- 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. 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. 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. 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. 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. Volume Baseline: Ignore it Alternative: Technology (flat files, tape, CSV Hadoop) Sampling
- 8. Velocity Baseline: Ignore it Alternative Streaming (StreamInsight) Sampling
- 9. Variety Baseline: Ignore it Alternative: Different database types SQL NoSQL: Excel, Power Pivot, OLAP, Graph, HDInsight, Hadoop Sampling
- 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. 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. Obtaining Talent Baseline: Ignore the issue Alternatives Buy Rent Create Lead
- 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. One Book to Read Thomas Kuhn: The Structure of Scientific Revolutions
- 15. Tommy Lasorda, Manager LA Dodgers You can make it happen You can let it happen Or you can wonder, what happened?