Designing machines for Data Mining
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Data analytics challenges in Retail
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Designing machines for Data Mining
- 2. DESIGNING MACHINES FOR DATA MINING Alexander Efremov Challenges in Retail Industry http://www.a4everyone.com
- 3. Data Science, Data Data Mining Workflows – Specifics Analytics for Retail Agenda http://www.a4everyone.com
- 7. Data Mining Workflows – Specifics Use Data Use Business Logic Reduce/Remove human intervention http://www.a4everyone.com
- 8. 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. http://www.a4everyone.com
- 9. …… Analytics for Retail ……… Retail System product1: price, disc., adv., disp... sale1 salen … weather social events other productn: price, disc., adv., disp... http://www.a4everyone.com …
- 10. Analytics for Retail Data Prep Modelling Validation Business knowledgeData no yes Sales Forecast & Stats http://www.a4everyone.com
- 11. Analytics for Retail Data Prep Cleaning - Miss, Outs, LowVar Preprocessing - Vars decomp. /detrend, deseas./ - Transform - Standardization - Remove multicol., etc. Modelling & Validation Multistage modelling SWR - Model dev Model val Sales forecast & Stats Model destandardization Detransformation Add trend & seas http://www.a4everyone.com
- 12. Analytics for Retail Wrong Interconnections http://www.a4everyone.com
- 13. Analytics for Retail Multistage Modelling Modelling 2 Modelling 1 Fact. Set 1 Product Modelling 3 Fact. Set 2 Category Fact. Set 3 Rest y e1 e2 Depend. http://www.a4everyone.com
- 14. Analytics for Retail A4Retail – Results www.a4everyone.com alexander.efremov@a4everyone.com