Smart Data & Dataviz Solutions - The Digital Benchmark - Berlin 2019

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Smart Data & Dataviz In association with

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SPEAKER INTRO

THIBAULT LEFÈVRE

Data Science director

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VISUALISATION :: SYNTHESIS 5%

Clay tablet with map of the Babylonian city of Nippur (ca. 1400 BC) https://en.wikipedia.org/wiki/History_of_cartography

Charles Minard's map of Napoleon’s Russian campaign of 1812 https://en.wikipedia.org/wiki/Charles_Joseph_Minard

WIFI digitbench19

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RELEVANT TO US: DIGITAL ATTRIBUTION 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

30% of the workload

INTEGRATION (RAW STORAGE)

CONSOLIDATED MODEL

ANALYTIC PROCESSES

60% of the workload

VISUALISATION

10% of the workload

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

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

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RECAP

5 %

authorisations storage

automatisation analytic processes

direct access

modĂŠlisation integration cleansing consolidation

governance

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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

WIFI digitbench19

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SOLUTIONS BENCHMARK

TABLEAU

5%

Advanced visualisation configuration Enterprise ready Technical skills required for setup

60%

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SOLUTIONS BENCHMARK

QLIK SENSE

5%

In-memory engine Advanced modelling capabilities Enterprise ready

60%

Technical skills required for setup

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SOLUTIONS BENCHMARK

POCKET RESULT

5%

Ease of use Turnkey approach Full outsourcing of modelling skills

60%

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SOLUTIONS BENCHMARK

DATASTUDIO

5%

Easy to use / no setup Performance on massive data volumes Limited functionalities (not entreprise ready)

60%

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SOLUTIONS BENCHMARK

REEPORT

5%

Ease of use Performance on massive data volumes Enterprise ready

60%

Limited modelling capabilities

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SOLUTIONS BENCHMARK

LOOKER

5%

Advanced statistical capabilities Intended for technical teams 60%

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SOLUTIONS BENCHMARK

POWER BI

5%

Balanced compromise between technicality and sophistication Native Microsoft integration for authorization 60%

Technical skills required for setup

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SOLUTIONS BENCHMARK

TOUCAN TOCO

5%

Advanced story telling capabilities Ad hoc navigation Advanced technical skills required

60%

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DECISION PROCESS

#1 Your DNA

#2 Maturity & Ambitions

#3 Solution(s) selection

WIFI digitbench19

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CONTACT THIBAULT LEFEVRE

M13h // Directeur Data Science thibault.lefevre@m13h.com

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