Smart Data and Dataviz - m13h - Benchmark y EBG Berlin 2019

1. #digitbench19WIFI digitbench19
Smart Data
& Dataviz
In association with

2. digitbench19WIFI digitbench19
SPEAKER INTRO
THIBAULT
LEFÈVRE
Data Science
director

3. digitbench19WIFI digitbench19
VISUALISATION :: SYNTHESIS
5%
https://en.wikipedia.org/wiki/Charles_Joseph_Minard
Clay tablet with map of the Babylonian city of Nippur
(ca. 1400 BC)
Charles Minard's map of Napoleon’s Russian campaign of 1812
https://en.wikipedia.org/wiki/History_of_cartography

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RELEVANT TO US: DIGITALATTRIBUTION
Data acquisition (integration)
• Platforms– ad centric
• Web analytics – site centric
Modelling / analytic processes
• Cleansing
• Internal rules (page exclusion, sources, campaign grouping / naming etc…)
• Attribution model application (statistical / deterministic, last / first / linear….)
Visualisation
• Represent the scores of each levers depending on the chosen model

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UNDER THE HOOD
DATA SOURCES INTEGRATION
(RAW
STORAGE)
CONSOLIDATED
MODEL
ANALYTIC
PROCESSES
VISUALISATION
30% of the workload 60% of the workload 10% of the workload

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VISUALISE: WHAT, FOR WHOM ?
> Operations monitoring dashboard
BU management
> Real-time monitoring dashboard
Acquisition team
> Weekly performance report
Acquisition team
Agency counterparts
> Data exploration
Data analysts / scientists
> Attribution project debrief presentation
BU management
Acquisition team

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POINTS OF ATTENTION ?
RELIABILITY
NAVIGATION
MODELLING
EASE OF USE
INDUSTRIALISATION
DATA ACCESS

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RECAP
integrationmodélisation
cleansing
analytic processes
consolidation
storage
automatisation
direct access
authorisations
governance
5
%

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BENCHMARK CRITERIA
• EASE OF USE : Some solutions are particularly intuitive and can
be made available to end users with no particular expertise
(usually limited in functionalities as well)
• IMPLEMENTATION: Is the solution available in SaaS mode ?
Are technical operations / setup required before users can access
the necessary functionalities ?
•COLLABORATION : What functionalities are implemented that
promote users working on the same report and sharing insights ?
•STORYTELLING : Are there functionalities dedicated to story
telling ?
•STORAGE / MODELLING: Is data cached within the solution ?
Modelling capabilities can help mitigate database limitations, but
also create a risk for complexity / discrepancy
•STATISTICAL FUNCTIONS : similarly to storage / modelling
capabilities, the availability of statistical functions in the
visualisation solution can help accelerate application development
but also increase the risk of discrepancy between reports

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Advanced visualisation configuration
Enterprise ready
Technical skills required for setup
TABLEAU
SOLUTIONS BENCHMARK
60%
5%

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In-memory engine
Advanced modelling capabilities
Enterprise ready
Technical skills required for setup
QLIK SENSE
SOLUTIONS BENCHMARK
60%
5%

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Ease of use
Turnkey approach
Full outsourcing of modelling skills
POCKET RESULT
SOLUTIONS BENCHMARK
60%
5%

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Easy to use / no setup
Performance on massive data volumes
Limited functionalities (not entreprise ready)
DATASTUDIO
SOLUTIONS BENCHMARK
60%
5%

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Ease of use
Performance on massive data volumes
Enterprise ready
Limited modelling capabilities
REEPORT
SOLUTIONS BENCHMARK
60%
5%

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Advanced statistical capabilities
Intended for technical teams
LOOKER
SOLUTIONS BENCHMARK
60%
5%

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Balanced compromise between technicality and sophistication
Native Microsoft integration for authorization
Technical skills required for setup
POWER BI
SOLUTIONS BENCHMARK
60%
5%

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Advanced story telling capabilities
Ad hoc navigation
Advanced technical skills required
TOUCAN TOCO
SOLUTIONS BENCHMARK
60%
5%

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DECISION PROCESS
#1 Your DNA #2 Maturity & Ambitions #3 Solution(s) selection

19. #digitbench19WIFI digitbench19
CONTACT
THIBAULT
LEFEVRE
M13h // Directeur Data
Science
thibault.lefevre@m13h.com