Course boundaries: what do we call data management?

Business Opportunities: From Simple Analytics to Big Data and AI.

Big Data and Analytics: What and Who Did They Really Change?

5 basic principles of data management: what else is meaningless?

Effective tools for easy data management

Visualization. How to show the data so you can better understand it yourself and explain it to others
Whiteboarding. How to show data to motivate yourself and others.
Dashboarding. How to understand where we are and where we are heading and how to respond to new challenges in a timely manner.
People vs machines: what are the best experts?

Expert data models: when to apply.

Expert team: what specialists we need and where to look for them.

Self-diagnosis: How to quickly evaluate what to focus on first.

Expert models in different business areas:

Finance: forecasting and factor analysis.
CRM: Timely and relevant sales and customer drain campaigns.
Marketing: segmentation (key customers and NPS), the best approaches to differentiate products and services.
Retail: Effective commodity management.
Production: less defects and more efficiency.
Self-diagnosis: How to quickly evaluate what to focus on first.

When machines work better than experts.

Work with Small Data (when there is little or no data).

Big Data: what it really is and how it works.

How artificial intelligence and Big Data are changing the work of data in finance, CRM, marketing, retail and manufacturing.

Machine Learning and Artificial Intelligence (AI)

Basic types and models of machine learning.

How Big Data and AI help you create new products and move to the latest business models.

Self-diagnosis: How to quickly evaluate what to focus on first.

Data Analysis Project Management: How Not to Spend Money?

Creating a company transformation strategy in data smart enterprise: methodology and examples.

Presentations of program participants.