A recap on the Unified Log "manifesto" for new ULPers, with my regular presentation on "Why your company needs a Unified Log". Given at Unified Log London in May 2015

1. Why your company needs a
Unified Log
Unified Log London, 20th May 2015

2. Introducing myself
• Alex Dean
• Co-founder and technical lead at Snowplow,
the open-source event analytics platform
based here in London [1]
• Weekend writer of Unified Log Processing,
available on the Manning Early Access Program
[2]
[1] https://github.com/snowplow/snowplow
[2] http://manning.com/dean

3. So what’s a Unified Log?

4. A quick history lesson: the three eras of business data
processing [1]
1. The classic era, 1996+
2. The hybrid era, 2005+
3. The unified era, 2013+
[1] http://snowplowanalytics.com/blog/
2014/01/20/the-three-eras-of-business-data-processing/

5. The classic era of business data processing, 1996+
OWN DATA CENTER
Data warehouse
HIGH LATENCY
Point-to-point
connections
WIDE DATA
COVERAGE
CMS
Silo
CRM
Local loop Local loop
NARROW DATA SILOES LOW LATENCY LOCAL LOOPS
E-comm
Silo
Local loop
Management
reporting
ERP
Silo
Local loop
Silo
Nightly batch ETL process
FULL DATA
HISTORY

6. The hybrid era, 2005+
CLOUD VENDOR / OWN DATA CENTER
Search
Silo
Local loop
LOW LATENCY LOCAL LOOPS
E-comm
Silo
Local loop
CRM
Local loop
SAAS VENDOR #2
Email
marketing
Local loop
ERP
Silo
Local loop
CMS
Silo
Local loop
SAAS VENDOR #1
NARROW DATA SILOES
Stream
processing
Product
rec’s
Micro-batch
processing
Systems
monitoring
Batch
processing
Data
warehouse
Management
reporting
Batch
processing
Ad hoc
analytics
Hadoop
SAAS VENDOR #3
Web
analytics
Local loop
Local loop Local loop
LOW LATENCY LOW LATENCY
HIGH LATENCY HIGH LATENCY
APIs
Bulk exports

7. The hybrid era: a surfeit of software vendors
CLOUD VENDOR / OWN DATA CENTER
Search
Silo
Local loop
LOW LATENCY LOCAL LOOPS
E-comm
Silo
Local loop
CRM
Local loop
SAAS VENDOR #2
Email
marketing
Local loop
ERP
Silo
Local loop
CMS
Silo
Local loop
SAAS VENDOR #1
NARROW DATA SILOES
Stream
processing
Product
rec’s
Micro-batch
processing
Systems
monitoring
Batch
processing
Data
warehouse
Management
reporting
Batch
processing
Ad hoc
analytics
Hadoop
SAAS VENDOR #3
Web
analytics
Local loop
Local loop Local loop
LOW LATENCY LOW LATENCY
HIGH LATENCY HIGH LATENCY
APIs
Bulk exports

8. The hybrid era: company-wide reporting and
analytics ends up like Rashomon
The bandit’s story
vs.
The wife’s story
vs.
The samurai’s story
vs.
The woodcutter’s story

9. The hybrid era: the number of data integrations
is unsustainable

10. So how do we unravel the
hairball?

11. The unified era, 2013+
CLOUD VENDOR / OWN DATA CENTER
Search
Silo
SOME LOW LATENCY LOCAL LOOPS
E-comm
Silo
CRM
SAAS VENDOR #2
Email
marketing
ERP
Silo
CMS
Silo
SAAS VENDOR #1
NARROW DATA SILOES
Streaming APIs /
web hooks
Unified log
LOW LATENCY WIDE DATA
COVERAGE
Archiving
Hadoop
< WIDE DATA
COVERAGE >
< FULL DATA
HISTORY >
FEW DAYS’
DATA HISTORY
Systems
monitoring
Eventstream
HIGH LATENCY LOW LATENCY
Product rec’s
Ad hoc
analytics
Management
reporting
Fraud
detection
Churn
prevention
APIs

12. CLOUD VENDOR / OWN DATA CENTER
Search
Silo
SOME LOW LATENCY LOCAL LOOPS
E-comm
Silo
CRM
SAAS VENDOR #2
Email
marketing
ERP
Silo
CMS
Silo
SAAS VENDOR #1
NARROW DATA SILOES
Streaming APIs /
web hooks
Unified log
Archiving
Hadoop
< WIDE DATA
COVERAGE >
< FULL DATA
HISTORY >
Systems
monitoring
Eventstream
HIGH LATENCY LOW LATENCY
Product rec’s
Ad hoc
analytics
Management
reporting
Fraud
detection
Churn
prevention
APIs
The unified log is Amazon Kinesis, or Apache Kafka
• Amazon Kinesis, a
hosted AWS service
• Extremely similar
semantics to Kafka
• Apache Kafka, an append-
only, distributed, ordered
commit log
• Developed at LinkedIn to
serve as their
organization’s unified log

13. “Kafka is designed to allow a
single cluster to serve as the
central data backbone for a
large organization” [1]
[1] http://kafka.apache.org/

14. So what does a unified log give us?
A single version of the truth
Our truth is now upstream from the data warehouse
The hairball of point-to-point connections has been
unravelled
Local loops have been unbundled
1
2
3
4

15. What does a unified log let us do that we couldn’t do before?
Populating a unified log with
your company’s event streams
Real-time
management
reporting
To enable…
Holistic
systems
monitoring
Re-running
models from
Day 0
A/B testing
end-to-end
pipelines
Shipping
offline
models to RT
… anything requiring low
latency response /
holistic view of our
company’s data!

16. But garbage in, garbage out: it’s crucial to properly model the
event streams feeding into the unified log
Subject
Direct
Object
Indirect
Object
Verb
Event Context
Prep.
Object~
• We are working on a semantic model for events – an “event
grammar” at Snowplow [1]
• The event grammar borrows concepts from human language:
• A semantic model prevents business and technology assumptions
leaking in to the event stream – making it less brittle over time
[1] http://snowplowanalytics.com/blog/2013/08/12/
towards-universal-event-analytics-building-an-event-grammar/

17. We also need to store and version the schemas used to describe
our events, as these will change over time
Unified
log

18. Questions?

19. Questions?
http://snowplowanalytics.com
https://github.com/snowplow/snowplow
@snowplowdata
To meet up or chat, @alexcrdean on Twitter or
alex@snowplowanalytics.com
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