Did you like it? Check out our blog to stay up to date: https://getindata.com/blog Marek Wiewiórka and Tomasz Żukowski had a pleasure to give a presentation at Data Science Summit 2017 which took place in Warsaw on May 26th. They came forth with one of the most popular startup in Sweden - Trucaller. Please take a look at the presentation.

1. Truecaller
towards a data-driven company
Marek Wiewiórka, Tomasz Żukowski

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Agenda
1. Truecaller - a global phonebook
2. Evolution of the company’s data architecture
3. Data as a company asset

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Truecaller
■ World's largest mobile phone community ( > 250 mln users)

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Truecaller In Numbers
■ +6 billion application events daily
■ +3 TB of compressed user generated data daily
■ +65M active users and 250k application installations daily
■ +28M identified spam calls every day
■ ...

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Not ly Data-Driven Beginnings...
■ Data layer and analytics powered by MySQL databases
■ No separation of OLTP and OLAP domains
■ Daily ETL processes that used to take longer than one day ;)
■ Problems with storing and querying historical (cold) data
■ Basic reporting without possibility of doing real data
science
■ Almost no DWH design principles in place...

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Towards ly Scalable Data Architecture
DWH
Data ingestion
Schema
repo

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Towards ly Scalable Data Architecture
■ Both data ingestion and data storage/analytics layers are
horizontally scalable
■ High availability for both master and worker nodes
■ Apache Avro with schema evolution features and
centralized schema repository makes adding new event
types seamless for ETL processes
■ Clear separation of staging (raw - Avro format) and
reporting (cleaned and enriched in ORC format) data

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Towards ly Self-Service Analytics

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ly Analytical Tools

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Jupyter Notebooks

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What Can We Do With These Data?
■ Calculate spammer score

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What Can We Do With These Data?
■ Calculate spammer score
■ Visualize our business

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What Can We Do With These Data?
■ Calculate spammer score
■ Visualize our business
■ Monitor KPIs after upgrades

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What Can We Do With These Data?
■ Calculate spammer score
■ Visualize our business
■ Monitor KPIs after upgrades
■ Better target ads

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What Can We Do With These Data?
■ Calculate spammer score
■ Visualize our business
■ Monitor KPIs after upgrades
■ Better target ads
■ Detect fraudulent user behaviour

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LTV - how to calculate

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Market Share Estimation

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Is Brexit ly a Problem?
■ Calculated on anonymized data of
200k users in the UK
■ Analysis prepared just after Brexit
referendum

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Is Brexit ly a Problem?

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What’s next
■ More digging into data (a lot of areas not even touched yet)
■ More advanced modelling
■ Streaming analytics

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