Why data isn’t dull

I’m a data-centric person. I’ve spent years working with data. Data is frequently one of the most valuable resources I have. So warning, this post may qualify as a rant.

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I think of all the ways I’ve worked with data – from acquiring sample data, test data, and snapshots of production. I appreciate, respect, and preserve data I can get my hands on. And I alter, manipulate, destroy, import, export data through a range of test activities. I analyze, interpret, back up, and restore data. But when I talk with some people about data, the comment deathly dull is used.

Do we forget that it is the data in many applications that make the application?

A few examples:

Web analytics – that’s dull too all the way until you’re trying to model user scenarios, or choose what functionality customers really use – not ask for but use. What’s web analytics without data pulled from logs?

Imagine amazon.com without a book inventory – the book inventory is data.

Order history on websites, data.

What are our blogs but data loaded into a portal?

Imagine the website LinkedIn without data.

Envision Google maps without data.

Or think about the wonderful way we can be lazy when accessing some of our most frequently used websites – the beauty of data stored in a cookie.

The defect systems we work with – it’s the data that matters.

And Excel? Without data, Excel would serve no purpose.

Chances are your attachment to your phone isn’t to the device but to the contact information stored on the device or your email which is also data.

So my WIFFM on data? If we see the value in what data offers us, then data isn’t dull. In fact, it’s the opposite. Data can be the essential setup to our sandbox test environments and the key to finding bugs.

Maybe the label data adds a layer of separation making data sound dull but when the data has meaning to what you do or care about – then data is fascinating.

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