Page 250 - Data Architecture

Chapter 6.4: Introduction to Data Vault Methodology
review process) can see sprint cycles drop to about 4 weeks. From there, it simply
improves to 2 weeks as the team gets better at it. Currently, there is a team implementing
Data Vault 2.0 methodology and attempting to achieve 1-week sprint cycles. There
doesn’t seem to be a bottleneck to optimizing the processes.

But as a reminder, where does the optimization of these processes come from? CMMI—
in direct correlation with the KPAs and KPIs of building a data warehouse. It is tied as

well to repeatable designs, pattern-based data integration, pattern-based models, and yes
—pattern-based business intelligence build cycles. This is the value of Data Vault 2.0
methodology—it provides the patterns out of the gate, to get the teams kick-start in the
right direction.

Why Include PMP, SDLC If CMMI and Agile Should

Be All That's Needed?

That said, CMMI doesn’t describe how to achieve these goals; it just describes what
should be in place. Agile doesn’t describe what you need, but rather how to manage the
people and the life cycle. Projects and SDLC components are necessary for the next step:
pattern-based development and delivery. The next pieces of the puzzle come from project
management professional (PMP) and software development life cycle (SLDC). PMP lays
the project foundation for the common project best practices.

While the team strives to be agile in the end, at some level, waterfall project practices
must be adhered to. Otherwise, a project cannot progress through its lifecycle to
completion.

According to project management body of knowledge (PMBOK) guide:

The project management framework embodies a project life cycle and five major project
management process groups:

• Initiating
• Planning
• Executing
• Monitoring and controlling
• Closing

Reference: http://encyclopedia.thefreedictionary.com/Project+Management+Professional

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