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Building an Insight Machine
Matthew Granade
Strata DDBD 2015
September 29, 2015
Big Data, Big Spending
50%
10%
• Market growing
at 10%1
• Big Data portion
growing at 50%1
• $60 billion1 on
information
m...
Common Question
“I know clearly how much I’m
spending on my data initiatives – it’s
millions of dollars. But I don’t feel ...
How do I generate
insight from all this data?
Data Insight
Three questions
1. What is insight?
2. Where does it come from?
3. How do I build a machine to generate it?
What is
insight?
Better
understanding.
Vx Vx + 1
Where does
insight come
from?
Lone genius?
Lone genius?
Lone genius?
Lone genius?
“If I have seen further,
it is by standing on the
shoulders of giants.”
-- Sir Isaac Newton
Compounding
Where does insight come from?
0
5000
10000
15000
20000
1 11 21 31 41 51
5% 6%
Compounding interest
“My wealth has
come from a
combination of
living in America,
some lucky
genes, and
compound
interest.”
-- Warren Buffett
Checklists
Academic Compounding
Compounding Code
“Reporters, investors, and
others are always asking
me for the secret
ingredient. There is no one
secret. We just worked
e...
What if you don’t?
• People waste time doing things that have
already been done.
• It’s difficult or impossible to make th...
Codify Do Learn
1
2
Invest in technology and related processes to
make analysts’ work accessible and reproducible
Build an...
Codify Do Learn
Codify Do Learn
Write down
your
procedure
Follow your
procedure
Compare
outcomes,
diagnose,
improve
The Full Circle
Codify Do Learn
1
2
Invest in technology and related processes to
make analysts’ work accessible and
reproducible
Build an...
Invest in technology and related processes to
make analysts’ work accessible and reproducible
2. Version control system
3....
Building the insight machine
Follow on twitter: @dominodatalab
@matthewgranade
Questions / Feedback?
Booth at Strata NYC: P3
matthew@dominodatalab.com
...
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Building an Insight Machine - Strata DDBD 2015

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First, we will explore the power of a compounding insight machine (as opposed to an ad hoc insight machine):
-Human time is focused on improving logic, rather than executing outcomes
-Less dependent on human biases or frailty
-Robust to and tested by a huge collection of scenarios

Second, we will explore the anatomy of such a machine:
-The roles you need to cast on your team and who to fill them with
-The key processes required for generating and capturing insight and, more importantly, for building upon those insights
-The technology required to enable this approach

Published in: Data & Analytics
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Building an Insight Machine - Strata DDBD 2015

  1. 1. Building an Insight Machine Matthew Granade Strata DDBD 2015 September 29, 2015
  2. 2. Big Data, Big Spending 50% 10% • Market growing at 10%1 • Big Data portion growing at 50%1 • $60 billion1 on information management software • Shortfall of 150,000 data scientists2 1 http://www.ovum.com/press_releases/ovum-forecasts-big-data-software-to-grow-by-50/ 2 McKinsey & Company
  3. 3. Common Question “I know clearly how much I’m spending on my data initiatives – it’s millions of dollars. But I don’t feel like our company is that much smarter. … Where’s all the insight I was promised?”
  4. 4. How do I generate insight from all this data? Data Insight
  5. 5. Three questions 1. What is insight? 2. Where does it come from? 3. How do I build a machine to generate it?
  6. 6. What is insight? Better understanding. Vx Vx + 1
  7. 7. Where does insight come from?
  8. 8. Lone genius?
  9. 9. Lone genius?
  10. 10. Lone genius?
  11. 11. Lone genius?
  12. 12. “If I have seen further, it is by standing on the shoulders of giants.” -- Sir Isaac Newton
  13. 13. Compounding Where does insight come from?
  14. 14. 0 5000 10000 15000 20000 1 11 21 31 41 51 5% 6% Compounding interest
  15. 15. “My wealth has come from a combination of living in America, some lucky genes, and compound interest.” -- Warren Buffett
  16. 16. Checklists
  17. 17. Academic Compounding
  18. 18. Compounding Code
  19. 19. “Reporters, investors, and others are always asking me for the secret ingredient. There is no one secret. We just worked every day to make the math better and express it well in code.” -- Early RenTech Employee Compounding Investments
  20. 20. What if you don’t? • People waste time doing things that have already been done. • It’s difficult or impossible to make things better. There is no place where ideas go.   • Idea generation suffers because people aren’t exposed to the thinking that came before them … they have no one to stand on.
  21. 21. Codify Do Learn 1 2 Invest in technology and related processes to make analysts’ work accessible and reproducible Build an Insight Machine: Two Steps
  22. 22. Codify Do Learn
  23. 23. Codify Do Learn Write down your procedure Follow your procedure Compare outcomes, diagnose, improve
  24. 24. The Full Circle
  25. 25. Codify Do Learn 1 2 Invest in technology and related processes to make analysts’ work accessible and reproducible Build an Insight Machine: Two Steps
  26. 26. Invest in technology and related processes to make analysts’ work accessible and reproducible 2. Version control system 3. Create building blocks 1. Clarity standard
  27. 27. Building the insight machine
  28. 28. Follow on twitter: @dominodatalab @matthewgranade Questions / Feedback? Booth at Strata NYC: P3 matthew@dominodatalab.com dominodatalab.com

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