3 years, 10 months ago

IT4IT™ Reference Architecture Version 2.0, an Open Group Standard

By The Open Group 1 Title/Current Version IT4IT™ Reference Architecture Version 2.0, an Open Group Standard 2 The Basics The Open Group IT4IT Reference Architecture standard comprises a reference architecture and a value chain-based operating model for managing the business … Continue reading

3 years, 10 months ago

Agile Development And Data Management Do Coexist

A frequent question I get from data management and governance teams is how to stay ahead of or on top of the Agile development process that app dev pros swear by. New capabilities are spinning out faster and faster, with little adherence to ensuring compliance with data standards and policies.

Well, if you can’t beat them, join them . . . and that’s what your data management pros are doing, jumping into Agile development for data.

Forrester’s survey of 118 organizations shows that just a little over half of organizations have implemented Agile development in some manner, shape, or form to deliver on data capabilities. While they lag about one to two years behind app dev’s adoption, the results are already beginning to show in terms of getting a better handle on their design and architectural decisions, improved data management collaboration, and better alignment of developer skills to tasks at hand.

But we have a long way to go. The first reason to adopt Agile development is to speed up the release of data capabilities. And the problem is, Agile development is adopted to speed up the release of data capabilities. In the interest of speed, the key value of Agile development is quality. So, while data management is getting it done, they may be sacrificing the value new capabilities are bringing to the business.

Let’s take an example. Where Agile makes sense to start is where teams can quickly spin up data models and integration points in support of analytics. Unfortunately, this capability delivery may be restricted to a small group of analysts that need access to data. Score “1” for moving a request off the list, score “0” for scaling insights widely to where action will be taking quickly.

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3 years, 10 months ago

Agile Development And Data Management Do Coexist

A frequent question I get from data management and governance teams is how to stay ahead of or on top of the Agile development process that app dev pros swear by. New capabilities are spinning out faster and faster, with little adherence to ensuring compliance with data standards and policies.

Well, if you can’t beat them, join them . . . and that’s what your data management pros are doing, jumping into Agile development for data.

Forrester’s survey of 118 organizations shows that just a little over half of organizations have implemented Agile development in some manner, shape, or form to deliver on data capabilities. While they lag about one to two years behind app dev’s adoption, the results are already beginning to show in terms of getting a better handle on their design and architectural decisions, improved data management collaboration, and better alignment of developer skills to tasks at hand.

But we have a long way to go. The first reason to adopt Agile development is to speed up the release of data capabilities. And the problem is, Agile development is adopted to speed up the release of data capabilities. In the interest of speed, the key value of Agile development is quality. So, while data management is getting it done, they may be sacrificing the value new capabilities are bringing to the business.

Let’s take an example. Where Agile makes sense to start is where teams can quickly spin up data models and integration points in support of analytics. Unfortunately, this capability delivery may be restricted to a small group of analysts that need access to data. Score “1” for moving a request off the list, score “0” for scaling insights widely to where action will be taking quickly.

Read more

5 years, 11 months ago

The Next Phase of Agile Development

Guest post by Alan Morrison It’s human nature for people to build sturdy structures to shield themselves from the unpredictability of the elements. But, if you are too sheltered for too long, you weaken your ability to continuously confront change. That’s the dilemma facing IT departments. Change is raining down on them, and they are having trouble continuously adapting. A term is gaining momentum in the IT community to describe an ideal state for IT […]