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Retail Capability Academy

The Retail Capability Academy - Applied Learning is designed to help you better understand your digital assets and their value. This knowledge will result in easier forecasting and control on both the supply side and the demand side of the business. The program is designed to support you in transforming your organization to become data driven and enable you to obtain business value with analytics. We have created an eight-month learning framework where we will give you the opportunity to learn and reflect on critical analytics skills for retail data professionals. Rather than exclusively feeding you technical knowledge that can quickly become obsolete, we cover other critical skills to succeed with analytics to create a permanent behavioral change. The program includes 10 days of mandatory training to translate new knowledge into real business issues and cases. Optional days for deeper tool and lab sessions during the period are available, both for the individual and in plenum.

Termíny
Cílová skupina
Course structure
Prerequisites

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Cílová skupina

Business analysts (data exploration, data visualization, analytic analysis, report creation, report consumption, domain expertise); product owners, department managers, and management (domain experts, decision makers; quantitative analysts and data scientists (exploratory analysis, descriptive segmentation, predictive modeling); and IT professionals such as administrators, coders, DBA, ETL personnel, and enterprise architects

Course structure

Lesson 1

Introduction to analytics methods.
Segmentation.
Threshold tuning.
Leadership perspective.
Create Value.
Personal communication.
Introduction to retail methods.
Retail analytics.

Lesson 2

Unsupervised learning.
Predictive modelling.
Business model.
Decision-making process.
Identifying stakeholders.
Forecasting, attraction, and retention.

Lesson 3

Text analytics.
NLP/NLG.
QKB – Match codes.
Contextual analysis.
Preparing meetings.
Interviewing techniques.
Building trust.
Deployment of models and machine learning.
Adaption.

Lesson 4

Entity resolution.
Entity consolidation.
Dynamic networks.
Data collection.
Interact with stakeholders.
Impact business.
Explaining with simplicity.
Category management.
Price Elasticity.
Halo effect analytics.

Lesson 5

RPA, Deep Learning.
Agents, auto learning.
Challenges with change.
Human stages – transition model.
Eight-step model.
AI next gen.

Prerequisites

A high engagement to learn more about the drivers for analytics success is the main requirement. You need to have the willingness to change your mindset, and you should be looking forward to having an impact on the further development of your department. There are no formal technology prerequisites for this program.