Designing machines for Data Mining

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DESIGNING MACHINES FOR DATA MINING

Alexander Efremov

Challenges in Retail Industry

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Data Science, Data

Data Mining Workflows – Specifics

Analytics for Retail

Agenda

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Data Science?

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Data Science?

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Data?

Data Science?

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Data Mining Workflows – Specifics

Use Data

Use Business Logic

Reduce/Remove human intervention

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Analytics for Retail Why A4Retail?

Demand forecast, Storage planning, Price Optimization, etc.

Retail System – Spec.Dynamic, Time-Varying, Non-Linear, MIMO system

Retail Data – Spec.Missings, Outliers, Uninformative vars, Seasonality, Trend, etc.

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……

Analytics for Retail

……

…Retail

System

product1:price, disc., adv., disp...

sale1

salen

…

weather

social events

other

productn:price, disc., adv., disp...

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…

Analytics for Retail

Data Prep Modelling Validation

Business knowledgeData

Model

OK?no yes Sales

Forecast& Stats

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Analytics for RetailData PrepCleaning- Miss, Outs, LowVarPreprocessing- Vars decomp. /detrend,

deseas./- Transform- Standardization- Remove multicol., etc.

Modelling & ValidationMultistage modellingSWR - Model devModel val

Sales forecast & StatsModel destandardizationDetransformationAdd trend & seas

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Analytics for Retail Wrong Interconnections

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Analytics for Retail Multistage Modelling

Modelling 2

Modelling 1Fact. Set 1Product

Modelling 3

Fact. Set 2Category

Fact. Set 3Rest

y

e1

e2

Depend.

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Analytics for Retail A4Retail – Results

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alexander.efremov@a4everyone.com

Thank you!

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