Data Products @LinkedIn – Culture, People and Tools
Before we begin …                 A dog teaches a boy fidelity,              perseverance, and to turn around             ...
What qualifies as a Data Product?                                                   Big                                   ...
Shift in Metrics                                                                 2012                                     ...
Data Products Timeline                                                               Netflix Challenge                    ...
What I’ll talk about            Culture                                People   Tools©2013 LinkedIn Corporation. All Right...
Culture                                People   Tools©2013 LinkedIn Corporation. All Rights Reserved.            ORGANIZAT...
Culture1. Everything is a Data Product2. If you can’t measure it, you  can’t fix it3. Fewer things are done better©2013 Li...
Data Products on your LinkedIn homepage                                          ORGANIZATION NAME   9
Measurement1. Have core metrics2. Define measure of success3. Rinse and repeat©2013 LinkedIn Corporation. All Rights Reser...
Measurement©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 11
Culture©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 12
Culture                                People   Tools©2013 LinkedIn Corporation. All Rights Reserved.            ORGANIZAT...
People1. World class talent is the  number one priority2. Data scientists are unicorns3. Let people be©2013 LinkedIn Corpo...
People©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 15
Some of LinkedIn’s Data Scientists  Joseph Adler                                         Gloria Lau     Monica RogatiDanie...
Letting people be©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 17
Culture                                People   Tools©2013 LinkedIn Corporation. All Rights Reserved.            ORGANIZAT...
Tools1. For real data products, you  need real data2. Invest in infrastructure3. Open Source = Happiness©2013 LinkedIn Cor...
Real Data©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 21
LinkedIn Infrastructure              Project Voldemort                                  Espresso                          ...
Apache Kafka©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 23
Project Voldemort©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 24
Azkaban©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 25
DataBus©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 26
The Technologist’s Hierarchy of Needs                                                      BDFL          External         ...
If you need to remember just 3 things1. People are everything2. Data Products drive business3. Easier life => More product...
©2013 LinkedIn Corporation. All Rights Reserved.   ORGANIZATION NAME 29
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LinkedIn Data Products

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Great data leads to great insights which leads to great products.

Vitaly Gordon, senior products data scientist, talks about the culture, people and tools that have helped LinkedIn become the world’s leading professional social network and one of the most visited sites on the web.

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  • Please take my words with a grain of salt. No everything you will learn today, you should run to implement and not everything you do that doesn’t appear here is wrong. I’ve just came to tell you about some of the stuff I found interesting that made LinkedIn successful in the development of data products
  • What are data products (in the context of this talk) – something that involves algorithms and some consumer web facade. For example dashboards and visualization are not because they don’t have algorithms and HFT algorithms and missile guidance systems don’t have this consumer web façade
  • Metrics - Explain the shift in metrics as well, from eyeballs (bottom page counters) to segmented eye balls (e.g. Google analytics) to web funnels (i.e. looking at more metrics than just views) to multi dimensional engagement (don’t know if it is that different than the previous).Timeline – Explain the involvement of data products from Amazon’s “People who viewed this …” through Google Ads (don’t know if falls under the previous definition through PYMK to Endorsements. Also explain that data products are not just cool, but they are very valuable to your business
  • Metrics - Explain the shift in metrics as well, from eyeballs (bottom page counters) to segmented eye balls (e.g. Google analytics) to web funnels (i.e. looking at more metrics than just views) to multi dimensional engagement (don’t know if it is that different than the previous).Timeline – Explain the involvement of data products from Amazon’s “People who viewed this …” through Google Ads (don’t know if falls under the previous definition through PYMK to Endorsements. Also explain that data products are not just cool, but they are very valuable to your business
  • The power of 3 
  • Almost every element on the LinkedIn pages is a data productEverything should be data driven – from the idea conception, through iteration until the successFocus is really important – The attention span of your customers is limited, for every feature you add, think what you need to remove
  • Everything should be data driven – from the idea conception, through iteration until the success
  • Everything should be data driven – from the idea conception, through iteration until the success
  • If you could only do one thing, what would it be? -- Steve JobsShortly after Jerry Yang became the CEO of Yahoo, he invited Steve Jobs to address the company's leadership. Among many insightful things that Steve shared that day, the one that continues to have the most profound influence on me was his discussion regarding prioritization. Jobs said that after he returned to Apple in 1994, he recognized there were far too many products and SKUs in development so he asked his team one simple question: If you could only do one thing, what would it be? He said that many of the answers rationalized the need to do more than one thing, or sought to substantiate bundling one priority with another. However, all he wanted to know was what "the one thing" was. As he explained it, if they got that one thing right, they could then move on the next thing, and the next thing after that, and so on. Turned out the answer to his question was the reinvention of the iMac. After that, it was the iPod, the iPhone, and the iPad, and the rest, as they say, is history.Interestingly enough, years later I heard Jobs speak at All Things D and he explained that the company had actually been working on the iPad before the iPhone, as he had long written off pursuit of the phone as being prohibitively challenging given the carrier landscape. However, once a window of opportunity opened up to successfully bring a phone to market, he hit the pause button on the tablet, and only returned to it once Apple got the iPhone right. Pretty mind blowing to think that a company as large and successful as Apple, and someone as prodigiously talented as Steve Jobs, would temporarily shelve something as important as the iPad for the sake of focus, but that's exactly what he did.
  • The power of 3 
  • Really, it is. Give examples that show that this stuff is taken seriously (like Jeff’s all hands and Jim’s getting sent back to do his homework for not putting it first on his roadmap)Famous Conway’s diagram. Explain the day to day a data scientist at LinkedIn and why is it important to have those skills. Give some examples of people backgroundsHow to hire good data scientists – by using real examples you both test for truly needed skills and do some selling while interviewing, maybe give examples of interview questions
  • Really, it is. Give examples that show that this stuff is taken seriously (like Jeff’s all hands)
  • Joe Adler – Author of R in a NutshellGloria Lau – Associate professor at StanfordMonica Rogati - Wall Street Journal & The Economist to NPR & CNN to Real Simple & (yes!) Howard Stern.Daniel Tunkelang – Chief Scientist of Endeca that was sold to Oracle for > $1BDaria Sorokina – Creator of additive groves and competitor for the national heritage health prizeMatheiu Bastian – Co-founder and technical lead at GephiTalk about the day to day work of those people
  • The power of 3 
  • Most companies don’t have an exact replica of their production cluster in their development environment, explain why is it crucialInfrastructure increases the productivity and let’s data scientists to focus more on actual data scienceMaybe refers more to culture, but people are really curious why LinkedIn open sources so much. Explain the benefits in hiring and retention and mention few of those projects
  • Developing data products without real data is like learning swimming from a book
  • Infrastructure increases the productivity and let’s data scientists to focus more on actual data science
  • BDFL – Benevolent Dictator for LifeBenevolent - נדיב
  • I don’t know if those are the main 3 takeaways from the talk
  • Transcript of "LinkedIn Data Products"

    1. 1. Data Products @LinkedIn – Culture, People and Tools
    2. 2. Before we begin … A dog teaches a boy fidelity, perseverance, and to turn around three times before lying down. Robert Benchley – American Humorist©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 2
    3. 3. What qualifies as a Data Product? Big DataData Product Machine AI Consumer Learning Facade©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 3
    4. 4. Shift in Metrics 2012 2008 2003 1998©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 4
    5. 5. Data Products Timeline Netflix Challenge PYMK Recommendation 2009 2007 Personalization 2006 2004Crawl Search 1998 ©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 5
    6. 6. What I’ll talk about Culture People Tools©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 6
    7. 7. Culture People Tools©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 7
    8. 8. Culture1. Everything is a Data Product2. If you can’t measure it, you can’t fix it3. Fewer things are done better©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 8
    9. 9. Data Products on your LinkedIn homepage ORGANIZATION NAME 9
    10. 10. Measurement1. Have core metrics2. Define measure of success3. Rinse and repeat©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 10
    11. 11. Measurement©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 11
    12. 12. Culture©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 12
    13. 13. Culture People Tools©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 13
    14. 14. People1. World class talent is the number one priority2. Data scientists are unicorns3. Let people be©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 14
    15. 15. People©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 15
    16. 16. Some of LinkedIn’s Data Scientists Joseph Adler Gloria Lau Monica RogatiDaniel Tunkelang Daria Sorokina Matheiu Bastian ©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 16
    17. 17. Letting people be©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 17
    18. 18. Culture People Tools©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 19
    19. 19. Tools1. For real data products, you need real data2. Invest in infrastructure3. Open Source = Happiness©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 20
    20. 20. Real Data©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 21
    21. 21. LinkedIn Infrastructure Project Voldemort Espresso Apache Kafka DataBus Azkaban Zoie / Bobo Avatara DataFu©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 22
    22. 22. Apache Kafka©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 23
    23. 23. Project Voldemort©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 24
    24. 24. Azkaban©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 25
    25. 25. DataBus©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 26
    26. 26. The Technologist’s Hierarchy of Needs BDFL External Validation Fame Recognition Salary Functionality©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 27
    27. 27. If you need to remember just 3 things1. People are everything2. Data Products drive business3. Easier life => More productivity©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 28
    28. 28. ©2013 LinkedIn Corporation. All Rights Reserved. ORGANIZATION NAME 29

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