In this presentation Michael J. Radwin talks about the uses of Big Data in a smaller company like Intuit, and how they can still benefit from the same kinds of data that the larger businesses use. Radwin discusses the statistics and data that can be scaled down and managed at a small company level, but also with real life examples of how a family could use it in regards to their spending.

1. Big Data for the Little Guy
powerful data-driven insights for individuals and small businesses
Michael J. Radwin, Intuit Data Group
Big Data Innovation Summit, April 25, 2012

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Big Data for the Little Guy
empowers individuals and small
businesses by allowing them to tap
the collective wisdom of millions of
fellow Intuit customers.

3. Big Data for the Little Guy
powerful data-driven insights for individuals and small businesses
Intuit is a leader in this trend
because we are entrusted with the
collective data of our 50 million
customers.

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Trends: pools the data of
our QuickBooks Online
customers and allows small
business owners to answer
the primal question of how
they are doing and what is
normal for someone like
them.
Is five percent growth
normal or better than
companies in your area like
you?
For example, If you are a
roofer in the Bay Area
grossing $250,000 a
year, is that good or bad?

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Based on a small business’s unique data
we offer them customized deals on items
they buy, sell and use to run their
business that are relevant to them.
EasySaver: a data-driven feature in QuickBooks that
helps Small Business owners save real money.

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PayTrends: insights on salaries for a wide
range of positions across the USA.
We do this by pooling the
aggregated data of our millions of
small business customers.
Allows both employers and
employees to know what others
like them are making.

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Am I spending more or less
on groceries, restaurants, or
childcare than my neighbors?

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Intuit is proud to have been voted
one of the Most Trusted
Companies for Privacy in America
for the past 5 years running.
We build data-driven innovations
on a foundation of
strong privacy and security.

12. Transaction categorization
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03/11/2011 TRADER JOE'S #127 QPS - LOS ALTOS CA -- 4369 $30.93
03/23/2011 TACO BELL #16100161406 - MOUNTAIN VIE CA -- 7336 $3.58
03/25/2011 CHILDRENS DSCVRY MUSEU - SAN JOSE CA -- 0092 $120.00
04/10/2011 HOUSE OF BAGELS - MOUNTAIN VIE CA -- 1784 $20.45
04/11/2011 INTUIT *TURBOTAX - 800-446-8848 CA MAIL/PHONE -- 7830 $19.95
Financial Institution-specific rules
Regular expressions
Trained pattern matching
N-Gram analysis
Synonyms & aliases
Payment, Fee, Transfer, Check logic
Gelocation extraction
3rd-party
Business
Directory
Intuit-curated
Business
Directory
Google,
Facebook,
etc
Intuit user-
defined
categories
Unique ID
Business name
Category (primary)
Category (secondary)
Geolocation
Telephone number
URL
Intuit small business ID
Confidence score
Geolocation

13. Crowd-sourcing category corrections
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Learning from user feedback
to constantly improve
transaction categorization
accuracy for all.

14. TurboTax Live Community Search
14
1m Q&A
15m searches
6b pageviews
Most Popular
Answers and
Questions
Moderator Selected
for this Context

15. Commercial Graph: Architecture
Business
names, address, phone, in
dustry code
Offline ETL and Relationship Mapping
Applications
Request
Response
Consumers, de-duped
businesses, categorized
income & expenses
Transactions
Invoices, bills,
payments, ve
ndors, custom
ers

16. Thank You!
Michael J. Radwin, Intuit Data Group
Michael_Radwin@intuit.com
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