1. Data Analytics for
Mobile App
Development
● Turn your mobile data into real products
● Discover user interests in real-time way
Trieu Nguyen - http://nguyentantrieu.info/blog or @tantrieuf31
Lead Engineer at eClick Log Analytics team at FPT Online

2. If you like Big Data Analytic Intern
Jobs, submit your CV to me:
trieunt@fpt.com.vn
http://www.fptonline.net/Career/99/Default.aspx

3. Just little introduction
● 2007 I did my first Graph Analytics on Yahoo
360 friend' blogs (use Web Crawler)
● 2008 Java Developer, develop Social Trading
Network for a startup (Yopco)
● 2011 Join FPT Online, just develop social
network again, API for VnExpress Mobile App
● 2012 Join Greengar Studios to learn more
about mobile
● 2013 back to FPT Online, research about
Data Analytics, develop the Analytics Platform

4. Contents for this talk
● Trends of Now and the Future
● Why analytics for mobile development
● Core KPIs
● How to implement, case study and demo
● Lessons
● Questions & Answers

5. Trends of Now and the Future
● Mobile
● Big Data
● Analytics

6. In 2013, mobile devices will pass PCs to be most
common Web access tools.
By 2015, over 80% of handsets in mature markets will
be smart phones.
Source:http://www.forbes.com/sites/ericsavitz/2012/10/23/gartner-top-10-strategic-
technology-trends-for-2013/

8. We are in the age of Internet Cloud and
connected handheld devices

10. Why analytics for mobile development ?

11. Turn your data to actionable things ?

12. Measure UX using
quantitative research ?

13. Mobile Apps => Backend APIs =>
Statistics => Find the Trends & Insights?

15. How could we see "user interest graph" in our user's database ?

16. ● Social Graph
=> Keep the connection
● Interest Graph
=> Make new connection
=> recommendation
platform
Source: http://en.wikipedia.org/wiki/Interest_graph

17. Source: http://gigaom.com/2012/10/02/it-pays-to-know-you-interest-graph-master-gravity-gets-10-6m/

19. Why do analytics for your business ?
=> read these Behavioral Economics Books
http://www.goodreads.com/shelf/show/behavioral-economics

20. Core KPIs for Mobile Data Analytics

21. Web vs Mobile App
Web
Visitors
Visits
Pageviews
Events
Mobile App
Users
Sessions
Events

22. How we build KPIs for mobile
analytics ?
● Keep it simple as possible, but no simpler
● Identity => Tracking => Data Mashup (Social API)
● Leverage the "small" data in real-time

23. Metrics: Causes and Effects
● Screen Size => App Design, UI/UX, Usability
● App version => Deployment, Marketing
● Connectivity => Code, User Experience
● Location => Marketing, User Behaviour
● OS => Marketing, Cost, Development
● Memory => User Experience
● Feature Session => How to engage app users

24. Big Data on Small Devices: Data Science goes Mobile
http://strataconf.com/strata2013/public/schedule/detail/27605

25. Keep it simple: Just log them all !
How to implement, case study and demo

26. And your databases
could be overloaded ?

28. We can't solve problems
by using the same kind of
thinking we used when we
created them.
Albert Einstein

30. “lambda architecture”
proposed by @nathanmarz
We, at FPT Online, have applied
this architecture for 6 months

31. The “lambda architecture”
technology stack
● Java, Groovy, Scala , ..blah ..blah
● Netty (http://netty.io)
● Kafka (http://kafka.apache.org)
● Storm (http://storm-project.net )
● Redis ( http://redis.io )
● Hadoop (Hive, HBase,...)
● Phoenix: A SQL skin over HBase
● D3 - http://d3js.org
● Graph Query DSL http://gremlin.tinkerpop.com

32. Too theory.
I want
"Seeing is
believing"

33. Case Study (from my freelance project)
Problem:
● Build the app to promote advertising
information in real time way
● Measure everything
● Report useful information
● Mashup and data integration with Facebook
API for social data analytics
Context:
● PhongCachMobile - Smartphone Retail Store
https://play.google.com/store/apps/details?id=com.mc2ads.browser4x

34. Simple architecture
● App <=> PHP API <=> JVM Data Analytics API
● User tap on an item, tracking it.
● User shares/likes an item with Facebook ID,
tracking these events, crawling data using
Graph API for Statistics.

37. Data Collector

40. Social Data Integration

41. Social Data Integration

42. Lessons
What I have learned from Mobile World
and Big Data World

43. What I have learned
● Keep it as simple as possible, but no simpler !
● Choose right KPI, right questions => Profit
● Design an architecture for your data products
● Implement it! Just right tools for right jobs.
● Turn your data into the things everyone can
"look & feel"

44. Stay focused, keep innovating

45. “Logic will get you from A to Z;
imagination will get you
everywhere.” - Albert Einstein
Use your imaginationwith data analytics, not
just logic

47. See you at Barcamp Saigon
Date and time
6 July, 2013 - 08:00 to 7 July, 2013 - 17:00
Location
RMIT Saigon South
Address
702 Nguyen Van Linh Boulevard, District 7, Ho
Chi Minh City