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Irene Gonzálvez, Product Manager at Spotify
Big Data,
Big Quality?
Irene Gonzálvez
Product Manager
Data Infrastructure
Music Streaming Service
Launched in 2008
Premium and Free Tiers
Available in 61 Countries
Over 140M Monthly
Active Users
More than 30M Songs
Over 1 billion plays per day
Data enables recommendations, advertising,
label and artist payments and more
$ $ $
$ $ $
Data First
Data of Good Quality First
Data quality problems cost US
business $600B a year!
Data Warehouse Institute
Data Quality Dimensions
Timely Correctness
Completeness Consistency
DataMon
Data Counters
MetriLab
MetriLab
MetriLab
Data Quality Dimensions
Timely Correctness
Completeness Consistency
Datamon Data Counters
MetriLab
TC4D: Test Certified for Data
Level 1: Set-up, monitoring, alerting and documentation
Level 2: Data management and Unit tests
Level 3: Build your defenses
What’s next?
Build an algorithm library for anomaly detection (ML4ALL)
Provide the infrastructure to ‘plug&play’ more algorithms
Provide parameter recommendations to tweak the algorithms
What’s next?
Spotify-wide strategy
● Have metrics to understand when a dataset qualifies
as ‘good’ quality.
● Identify which datasets are critical/ central to Spotify
and make them of ‘good’ quality
Key Takeaways
Lesson #1: Think Big
Understand your org’s pain points
Lesson #2: Start small
And start NOW!
Lesson #3: Data Quality is
not an add-on
Insights can ONLY be as good as the data
Data will increase
10x by 2025
International Data Corp
1 ZB = 1 trillion GB
20% 10%Critical Data Hypercritical Data
Q&A
Irene Gonzálvez
Product Manager,
Spotify
irene@spotify.com

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Big Data, Big Quality? by Irene Gonzálvez at Big Data Spain 2017