The document outlines a workshop on data thinking led by Martin Szugat, highlighting the importance of data strategy in successful analytics projects due to a high failure rate attributed to lack of business impact, user acceptance, and appropriate data. It includes various aspects of data management, engineering, and understanding, along with a structured approach for effective data utilization. The agenda features virtual conferences and workshops scheduled for May 2020, focusing on concepts like user understanding, business viability, and modeling.

1. PAW Workshop Preview:
Data Thinking

2. 1996-2008
Consultant, Author
and Software Developer
Study and Research of
Bioinformatics (Data Science)
2001-2008
Managing Director &
Shareholder of SnipClip GmbH
2008-2013
Program Director of the Predictive
Analytics World & Deep Learning
World Conferences Germany
2014-dato
Managing Director & Founder of
Datentreiber GmbH
2014-dato
Chief Data Officer & Shareholder of
42AI GmbH
2018-dato
Martin Szugat

4. Agenda

5. Three virtual conferences on 11-12 May …
➔

6. … and two virtual workshops on 13 May 2020:

7. Why think about data …

8. … before doing data science?

9. Because ~85% of data analytics projects fail!

10. Reason #1: no business impact.

11. Reason #2: no user acceptance.

12. Reason #3: no (right) data.

13. → →
→ →
Data
Thinking
Data
Mining
Data
Engineering
Data
Management
Data Strategy
Data Prototypes
Data Product
Data SourcesData AssetsData Product
Innovation Cycle

14. Data
Management
Data
Engineering
Data
Mining
Data
Thinking
Data, Model &
Application
Management
Data,
Software & UI
Engineering
Data
Mining & User
Experiments
Data & Design
Thinking
2. User
Under-
standing
(Desirability)
3. Data
Under-
standing
(Feasibility)
1. Business
Under-
standing
(Viability)
2. Modelling
3.
Evaluation
1. Data
Preparation
3. Learn
1. Build
2. Measure
(Test)
3. Act
1. Deploy
2. Monitor

15. Data, Model &
Application
Management
Operating
Data,
Software & UI
Engineering
Engineering
Data & Design
Thinking
Data
Mining & User
Experiments
Designing
Experiment-
ing
➔➔

16. „Fail early to succeed sooner.“

17. Which tools?

18. Your head.

19. And the Data Strategy Designkit

20. Workshop Agenda for 13 May 2020

21. ➔

22. Q&A