Published on February 26, 2014
Finding (and using) Big Data in your Business Simon Elliston Ball Head of Big Data ! @sireb !#ﬁndBigData ! ! ! http://bit.ly/ﬁndBigData
Now THAT's Big Data • A modern Ford kicks out 25GB per car, in a day. • Ad networks: over a billion event logs per day. • PayPal: 3 billion transactions a year • Climate Corporation: soil type record for every square meter in the USA • Facebook: 10PB a day
So you're probably not Facebook • Big Data takes many forms • Velocity • Variety • Volume • Value • Veracity
Feature usage at Red Gate • We are obsessed with UX • Knowing what our users do helps us make their life better • Error reporting • Feature usage reporting • Conversations, survey, sales everything goes into making products better.
The default: SQL Server
The problem: SQL Server "I used to use FUR all the time! I can't use it anymore, it's too slow." - Michelle, Product Manager "I'm running a query right now... It started yesterday :(" - Ben, Product Manager "Hey, this database is taking up a few TBs, can we just delete it?" - Simon, DBA
DELETE IT!?!?!? • Thinning out old data • Archiving to cheaper storage (even tape) • Turning down collection
Big Data to the rescue • Cheap storage in Hadoop • Scale out, not scale up • Distributed computing required for speed • Occasional bursty workloads • Semi-structured
Hadoop • Created by Doug Cutting as a backend for a search engine and crawler (Nutch) in 2005. • Developed further at Yahoo • Based on Google's papers on Google Filesystem, and MapReduce • Since grown into an ecosystem of tools • Now version 2.0
All grown up
Really complex • Lots of moving parts • Integrating into your network can be complex • Getting all the tools to play nice • • • Self build Fixing up from a good starting point Use a distro
Sandboxes • Quick Start • Great to learn
What we did • Test cloud • Virtualization is not Hadoop's friend. • • • Performance is not good “Can we have 2TB on the SAN for /tmp?” Ur. No. "Borrowed" some old hardware, and got a small cluster running.
Putting data in • Sqoop • Cleaning • ORC
How to not kill SQL server • To a DBA Sqoop is a DDOS attack • Limit the number of mappers Sqoop uses • Import from a replica, or backup
Immediate value • The data was a lot smaller • Cheaper to store • Column formats • Compression: use lzo, bzip costs too much, and gzip is bad for Hadoop.
Give it back! Queries and ETL • Hive. Reuse your SQL • Pig. New, but worth learning • MapReduce? (Optional. Warning: may contain java. Or snakes)
Give it back to the business • Summary report in Excel • Batch jobs • Pump back into SQL for slicing and dicing • Give us MORE!
Give it back! The platform • To the cloud! • Reuse all our existing queries and workflow • On demand compute • Takes time to lift the initial data set into cloud storage, but incremental updates are fast
Thinking like a data scientist • Plan your experiments • Precision is subjective. • Show the error bars • Use whatever tool works • Embrace uncertainty
Know your business
Think strategically • Business buy-in • Show quick wins • What is your analysis for? • What will it deliver to the business?
Break down the requirements • Prioritize • Go for the top value pieces • Perfect ﬁt for Agile methodologies
Communication • Talk to everyone you can • Before • After • During • Organizational knowledge • Keep a log
Communication • Conversations • Coffee machine • Formal talks
So what's next? • Denormalize • Democratize • Machine learning for alerts • Marketing • Sales
And of course new tools • We want to talk to you...
Questions Simon Elliston Ball email@example.com ! @sireb #ﬁndBigData http://bit.ly/ﬁndBigData
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