This document provides a roadmap for establishing a successful data excellence program. It recommends starting with the right cross-functional team to define goals and prioritize use cases. It then advises performing a data assessment to understand existing data sources before implementing a simple but high-impact use case as a first step. Subsequent steps include managing the program, adding additional use cases, training personnel, and dealing with potential resistance, with an emphasis on continual improvement and evolving a data-driven culture.

1. Anchormen’s lessons learned
Roadmap to Data
Excellence

2. 22-09-16 2

3. Why is starting with Big Data complex?
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Lack of knowledge
Lots of assumptions
Lots of stakeholders
Talk about data driven
instead of ‘big data’

4. Start with the right people
22-09-16 4
Business stakeholder
Big Data Expert
Data manager
Enterprise IT
Legal officer

5. Goals and use cases
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Company strategy
Concrete use cases
Prioritize
‘Big Data’ is not a goal!

6. Data assessment
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Types of data sources
Volumes and velocity
Data quality
Fix data issues right away

7. Use cases
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One use case at a time
Start with a simple but sexy one!
Do not build spaceships! Keep it simple and
improve it later

8. Building it
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Start small, grow later
If possible, start in the
cloud
Your first steps take time
It is not free

9. In operation
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Manage, evaluate and
improve
Add cases
Learn, it is ok to fail!
Change culture
Data Driven

10. Continue with the right people
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Business stakeholders
Data engineers
Data scientists
Train your people
(learn.mapr.com)
Give them time to play
(and fail)

11. Resistance
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Big Data is a thread
Targets are not aligned
People want proof
Be patient

12. Summarizing
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Select the right team
Define your goals
Setup first version
Perform data assessment
Define and prioritize
use cases
Implement the first use case
Manage, evaluate
and improve
Change culture
Add cases
Data Driven
Training
Deal with resistance, be patient!