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Managing Successful
Data Projects:
Technology Selection and
Team Building
Strata Data Conference, San Jose 2018
Ted Malaska | @ted_malaska
Jonathan Seidman | @jseidman
About the presenters
▪Technical Group Architect at Blizzard Entertainment
- Cloud, Build, Deployment, Data
▪Principal Solutions Architect at Cloudera
▪Big Data Architect at FINRA
▪Contributor to Apache HDFS, HBase, Flume, Avro, Pig, Spark, YARN,
Sqoop, Kudu, Kafka, …
▪Co-Author of O’Reilly’s Hadoop Application Architectures
▪O’Reilly Online Trainer Course Creator
▪Adviser to the Board of MetiStream
▪Video Gamer
Ted Malaska
About the presenters
▪Software Engineer at Cloudera
▪Co-Author of O’Reilly’s Hadoop Application
Architectures
▪Previously Technical Lead on the big data team at
Orbitz, co-founder of the Chicago Hadoop User Group
and Chicago Big Data
Jonathan Seidman
Ted Malaska & Jonathan Seidman
Foundations
forArchitecting
Data Solutions
MANAGING SUCCESSFUL DATA PROJECTS
Enterprise software then…
Enterprise software now…
Well, actually…
Technology Selection
Before we get started…
§ A story of two paths:
- Vendor
- Customer
There’s a lot on the line
§ Limited amount of time to make decisions
§ Time and resource cost money
§ Don’t want to paint yourself into a corner
§ Everyday something new comes up
§ Mistakes can be career/project damaging
And many voices
§ There are the high profile companies
§ There are the venders
§ There are the hype trains
§ There are the demands from your business
§ There is the desire to build up your resume
Gartner Hype Cycle
Tricks to Evaluate Hype and Trends
Google Trends
Tricks to Evaluate Hype and Trends
Github activity
Tricks to Evaluate Hype and Trends
Jira Activity
Tricks to Evaluate Hype and Trends
Meetup.com
Build or buy? It depends
§ Internal culture
§ Technical religions
§ Skill sets
§ Opportunity for upside
- Incremental
- Revolutionary
- Control
§ Effectiveness of a vender
Consider buy in
§ Internal buy in
§ Allow for fail fast and restarting
How to stay focused
§ Where is the Business Value
§ All things are possible but not all things are easy
§ Stay dumb
§ You must hate the technology before you select it
§ Treat a vender as a vender not a friend
§ There must be a desire
Reducing risk
§ Interface design
§ Fail fast
§ Cloud based provisioning
§ Containers
§ Identify weak points with a passion
Building Successful Teams
First thing, don’t do this:
Data
Scientists Admins
Instead, build well rounded teams
Sysadmins Developers Analysts Data Scientists
Other roles:
Data Protection Officer Network/Systems EngineersProduct Managers
How to find people?
Start with people you already have, but make sure you invest in
training…
§Linux, network, DBAs –> sysadmins
§Developers –> developers
- Easy if you’re at a company like Orbitz, otherwise maybe not so much.
§Analysts –> analysts
§It’s not an easy path though.
- Set goals instead of micro-managing development.
- Be prepared to iterate, don’t be afraid to fail.
Also don’t forget other teams
Communication is key
DBAs Other Project Teams
Think beyond just skills
§ Also look for complementary personalities.
§ And avoid toxic personalities.
- But what if they’re really talented?
- See above.
Customer Engagement
§ Your teams should work closely with your customers, whether they’re external or internal.
Thank you!
Ted Malaska | @ted_malaska
Jonathan Seidman | @jseidman

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Managing Successful Data Projects: Technology Selection and Team Building

  • 1. Managing Successful Data Projects: Technology Selection and Team Building Strata Data Conference, San Jose 2018 Ted Malaska | @ted_malaska Jonathan Seidman | @jseidman
  • 2. About the presenters ▪Technical Group Architect at Blizzard Entertainment - Cloud, Build, Deployment, Data ▪Principal Solutions Architect at Cloudera ▪Big Data Architect at FINRA ▪Contributor to Apache HDFS, HBase, Flume, Avro, Pig, Spark, YARN, Sqoop, Kudu, Kafka, … ▪Co-Author of O’Reilly’s Hadoop Application Architectures ▪O’Reilly Online Trainer Course Creator ▪Adviser to the Board of MetiStream ▪Video Gamer Ted Malaska
  • 3. About the presenters ▪Software Engineer at Cloudera ▪Co-Author of O’Reilly’s Hadoop Application Architectures ▪Previously Technical Lead on the big data team at Orbitz, co-founder of the Chicago Hadoop User Group and Chicago Big Data Jonathan Seidman
  • 4. Ted Malaska & Jonathan Seidman Foundations forArchitecting Data Solutions MANAGING SUCCESSFUL DATA PROJECTS
  • 9. Before we get started… § A story of two paths: - Vendor - Customer
  • 10. There’s a lot on the line § Limited amount of time to make decisions § Time and resource cost money § Don’t want to paint yourself into a corner § Everyday something new comes up § Mistakes can be career/project damaging
  • 11. And many voices § There are the high profile companies § There are the venders § There are the hype trains § There are the demands from your business § There is the desire to build up your resume
  • 13. Tricks to Evaluate Hype and Trends Google Trends
  • 14. Tricks to Evaluate Hype and Trends Github activity
  • 15. Tricks to Evaluate Hype and Trends Jira Activity
  • 16. Tricks to Evaluate Hype and Trends Meetup.com
  • 17. Build or buy? It depends § Internal culture § Technical religions § Skill sets § Opportunity for upside - Incremental - Revolutionary - Control § Effectiveness of a vender
  • 18. Consider buy in § Internal buy in § Allow for fail fast and restarting
  • 19. How to stay focused § Where is the Business Value § All things are possible but not all things are easy § Stay dumb § You must hate the technology before you select it § Treat a vender as a vender not a friend § There must be a desire
  • 20. Reducing risk § Interface design § Fail fast § Cloud based provisioning § Containers § Identify weak points with a passion
  • 24. Instead, build well rounded teams Sysadmins Developers Analysts Data Scientists Other roles: Data Protection Officer Network/Systems EngineersProduct Managers
  • 25. How to find people? Start with people you already have, but make sure you invest in training… §Linux, network, DBAs –> sysadmins §Developers –> developers - Easy if you’re at a company like Orbitz, otherwise maybe not so much. §Analysts –> analysts §It’s not an easy path though. - Set goals instead of micro-managing development. - Be prepared to iterate, don’t be afraid to fail.
  • 26. Also don’t forget other teams Communication is key DBAs Other Project Teams
  • 27. Think beyond just skills § Also look for complementary personalities. § And avoid toxic personalities. - But what if they’re really talented? - See above.
  • 28. Customer Engagement § Your teams should work closely with your customers, whether they’re external or internal.
  • 29. Thank you! Ted Malaska | @ted_malaska Jonathan Seidman | @jseidman