Empirical process control

Which Project Delivery Approach Is Right For My Project?

This is an excellent article from Portland webworks on choosing project methodology for a specific project. It highlights the role of complexity in project approach and also generally speaking the simpler a project is the more it is suited to a waterfall approach and the more complex it is the more its suited to an agile approach.

stacey

“The Stacey Diagram, developed by Prof. Ralph Stacey in the 1990s, is the simplest and most powerful tool for understanding project complexity. It has been adopted throughout the world by many different industries.”

ScrumDesk

A while back I found this excellent scrum management tool. I have used it and I do highly recommend it. There is also a free sign up option with no time limit, but with limited users, projects allowed etc.. (In case you wondered I don’t work or haven’t been asked by scrumdesk to put this recommendation on line! 🙂

www.scrumdesk.com

 

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Companies will ‘get serious’ about AI technology in 2017

Here is another very interesting article on the coming of AI from Tech Target.

Companies will ‘get serious’ about AI technology in 2017

Tom Davenport points out two key things –

1. Artificial intelligence is an umbrella term that includes everything from speech recognition software to robotics, and the maturity of each technology varies. Because AI is so broad, “you really have to disaggregate it,” Davenport said.

2. This is the year of the artificial intelligence “science project;” next year, companies will “get serious about…the application of AI,”

Data Migration

I recently worked on a data migration and it was challenging and complex to say the least. I have listed out the key (but not all) issues and actions that had to be carried as part of the migration.

  1. Comparing and analysing the new data set to the old data set to find any discrepancies to make sure the new data contained all the required fields or information.
  2. Making sure the new data set was uploaded correctly and people were on hand to deal with any issues that could occur when it was loaded in.
  3. Checking if the system could be rolled back if the data migration caused a lot of issues when it was completed.
  4. Also looking at how the new data set was structured and how the different segments or categories connected to each other and if this was any different from how the old data sets segments or categories linked to each (this in itself brought up some issues that had to be resolved).

From this I can honestly say it’s so important for organisations to keep on top of the data that they use and store. It must be kept tidy, audited, organised and well maintained. So often this does not happen and it gets pushed to one side because of other business priorities. Then once a data migration is required or a new system needs to use the data there can often be all types of issues that come up that have to be resolved, and that can cost more money than properly maintaining the data to begin with.

Here is also an interesting article from information week on data migration: 10 Big Data Migration mistakes

 

 

Software Development Life Cycle – Summary

Here is a link to a useful and interesting overview of the Software Development Life Cycle “SDLC.”

sdlc_stagesAn interesting read for anyone new or just getting into software development. It does appear to outline a some what Waterfall approach in the body of the article – which these days is a method no longer used, or being used less and less. However, at the bottom it does out line different models for software development including that of Agile and Waterfall.

I would also add that it’s really important to test as you proceed the build and not to start testing once the build is completed!

Stage 5: Testing the Product

This stage is usually a subset of all the stages as in the modern SDLC models, the testing activities are mostly involved in all the stages of SDLC. However this stage refers to the testing only stage of the product where products defects are reported, tracked, fixed and retested, until the product reaches the quality standards defined in the SRS.