Martin Szugat presented on designing a data strategy using an open source toolbox and method for data thinking. He discussed why a data strategy is important given that around 85% of data and analytics projects fail due to a lack of business impact, user acceptance, or having the right data. A data strategy involves understanding the business objectives, accessible data, potential use cases, and roadmap for data-driven business cases. It is designed through an interdisciplinary team that understands the business, users, and data. The presentation provided an overview of the key components and considerations for developing a successful data strategy.
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Data Strategy Design: An Open Source Toolbox & Method for Data Thinking.
1. Martin Szugat @ Data Brain Meetup on 10/08/2020
Data Strategy Design:
An Open Source Toolbox &
Method for 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
2014-dato
Managing Director & Founder of
Datentreiber GmbH
2014-dato
Chief Data Officer & Shareholder of
42AI GmbH
2018-dato
Martin Szugat
5. Because ~85% of data analytics & AI projects fail!
https://designingforanalytics.com/resources/failure-rates-for-analytics-bi-iot-and-big-data-projects-85-yikes/
11. Collection of Analytics
Use Cases
(Problem, Solution, Benefit)
Roadmap for Data-Driven
Business Cases
(Costs, Risks, Profits)
Assumptions
(Analytical, Economical, …)
Learnings
(Data, Business, User, …)
Business Value
(Information → Decision → Action →
Impact → Objective)
Data Sources
(Collection, Acquisition, …)
Data
Thinking
Data
Mining
Data Engineering
Data
Management
Data Strategy
Data Prototypes
Data Product
Data SourcesData AssetsData Product
Innovation Cycle
12. Data
Management
Data Engineering
Data
Mining
Data
Thinking
Data, Model &
Product
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 &
Visualization
3. Evaluation
1. Data
Exploration &
Preparation
3. Learn
1. Build
2. Measure
3. Monitor
1. Deploy
2. Orchestrate
CRISP-DM
Design
Thinking
Proof of Concept (PoC)?
Proof of Value (PoV)?
Lean
Develop-
ment
DataOps
24. Martijn: My Life Is All About Transformation
Personal
Transformation
• 26 year’s Yoga
• 23 year’s Tai Chi
• Yoga teacher:
• 7 Courses in India
• Tai Chi teacher
• Life long student
• Traditional, rational
Projects
• 22 year’s projects
• 14 year’s project/
program manager
• 11 year’s PMO
• 1½ year’s audit lead
• 1+ year Agile rollout
• Growth Mindset
Digital
Transformation
• Past 2½ years:
• PM & Consultancy
• Data Strategy
Design Method:
• Certified Consultant
• Hosted 3 workshops
• Hosted 2 trainings
• Design Thinking
24LinkedIn profile
33. Thank You for Your Attention
Feel free to contact me if you have questions:
LinkedIn profile
E-mail: martijnbakker@excite.com
Tel.: +31 (0)6 14505759