Introduction to Talas Data Intelligence by Alvin Gendrano

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The document discusses Alvin Gendrano's career path from developer to data scientist, including his education in computer science and work experience at Microsoft where he worked on SQL Server and Azure Machine Learning. It then outlines his current role at Talas developing an open data platform and mobile applications that use location and mobility data to help small businesses find and target potential customers.

Technology

Developers to
Data Scientists
Alvin Gendrano, VP of Data Science and Insights
Nov 6, 2016

BS - Computer Science
1991 - 1995
Favorite Subject -
Databases

MS - Computer Science
Distributed
Databases

Microsoft Career
1998 - 2014
SQL Server
SQL Azure
Azure Machine
Learning

Bilang Pilipino
Graphics by TV5
Talas Data Scientists in Action

Mark locations
of particular
interest
Send perks to
your audience
to increase
foot traffic
Select profiles
that best
describe your
customer
Know where
your
customers
dwell
Immediately see
how your campaign
performed
DISCOVER NEW
CUSTOMERS SEND THEM PERKS
MEASURE YOUR
CAMPAIGN’S SUCCESS
A mobile application that uses location and mobility data and
subscriber insights to empower the small business owner

PROFILING SAMPLE USE CASE
At lunch time, people within
a 500m x 500m area of Max’s
Lucky China Town are
predominantly Worker Bees
(approximately 24%).
Their top interests are
Travel (11%),
Food (9%),
and Finance (7%)

CALL & TEXT
MOBILE INTERNET &
BROWSING
APPS &
CONTENT
INTERNET OF
THINGS

New Formats:
Kindle
What Amazon
recommends
What other customers
are buying
What other customers
are thinking
What other customers
are saying
Amazon search and recommendation engine: Leveraging Data

Ideal Data Scientist Skills
SUPER HARD TO FIND

WHAT DO I LOOK FOR?
- Python with Data Science Libraries
- Pandas
- MatPlotLib
- SciKit and SciPy
- Big Data Development Experience
- Hadoop - Map/Reduce - SQL
- SCALA SPARK

THEN...
- Use Python
- SciKit, Pandas, MatPlot
- Learn Hadoop or Spark w/ Scala
- Join a Data Science Team
- With Real Big Data and
Real Data Science Experience
1
2
3

Data Science Questions?
1. How much / how many? Regression
2. Which category? Classification
3. Which groups? Clustering
4. Is it weird? Anomaly Detection
5. Which option? Recommendation

Learn how direct response marketers are adapting their strategies as their audiences move to mobile and as a result are growing revenue and eating their competition. Attendees will hear case studies highlighting best practices for lead generation, click-to-call, and mobile commerce, and will learn successful strategies on how to apply Direct Response techniques in the mobile world. This presentation was given by Ted McNulty, Senior Director of Performance Sales at Millennial Media, at NEDMA's Annual Conference on May 14, 2014.

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