Productivity issues for Agile in BI/DW – Part 2: Technology

Agile in a BI/DW environment faces a unique set of challenges that make becoming productive more difficult. These issues fall into a couple of categories. First are the difficulties in  getting the team to the productivity nirvana promised, which I covered in this post. Second are the difficulties posed by technology and process, which I’ll talk about today.

Some obstructions cannot be moved by thought alone.

Solving problems by thought alone
Solving problems by thought alone

Agility in traditional coding environments runs at a very high level like this: User states requirements, Coder develops an application that meets those requirements, test, showcase, done.

In BI/DW environments there process is less contained and has a lot of external dependencies. A user requesting a metric on a report is not a matter of coding to meet that requirement – we need to find the data source, find the data owner, get access to the data, process it, clean it, conform it and then finally put it on the report. Depending on the size and complexity of the organisation this can take anywhere between days and months to resolve.

Agile development as it is traditionally understood, with short sprints and close user engagement works well for reporting and BI when the data has already been loaded into the Warehouse. If you are starting from scratch, your user will often have become bored and wandered off long before you give them any reporting.

(Yes, once again, nobody cares about the back end because it’s boring and complicated)

Rather than move the mountain to Mohammed…

There are some steps you can take to mitigate this. The product backlog is your friend here. Often with some relatively light work on the backlog you can identify which systems you are going to hit and broadly what data you will need from those systems.

On a large scale project you may find that you have multiple systems to target, all of which will vary in terms of time from discovery to availability in the DW. Here I generally advocate switching to a Kanban type approach (i.e. task by task rather than sprint based) where you try and move your tasks forward as best you can, and once you are blocked getting at one system, while you wait for it to unblock move on to another.

As systems get delivered into the EDW you can start moving to delivering BI in a more interactive, sprint based fashion. I generally advocate decoupling the BI team from the DW team for this reason. The DW team work on a different dynamic and timescale to the BI team (though note I count building Data Marts as a BI function, not a DW function). You do run the risk of building Data Warehouse components that are not needed, but knowing you will discarding some effort is part of Agile thinking so shouldn’t be a big concern.

Once again its about people

You may notice that none of the issues I’ve raised here are set in stone technical issues. It’s still about people – the ability of external people to react to or accommodate your needs – the capacity of users to be engaged in protracted development processes – the flexibility of project sponsors not to have a rigid scope.

Good people who can be flexible and accommodate change are the keystone to agile success. No tool or process with ever trump these factors.

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