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Yves de Burbure de Wesembeek
Wednesday, 22 February 2017 / Published in Technology

The good, the bad and the ugly – best practices of using data

Most of the times when I think of data, what comes to mind is that funny android aboard the USS Enterprise that most of the times bothered Captain Picard with his witty, sometimes childish comments.

But more often than not, since I work with mountains of data every day, as I’m sure you are, I think of how data is used, should be used, best practices and quite frankly, how data can either ease up the management of your business and ultimately, to translate into financial gains.

If you’re a Clint Eastwood fan, you’ll understand how my view of the best practices fall into one of the following three categories: the good, the bad and the ugly. Unlike the characters in the movie I referenced, the practices are not united one against each other—but rather in direct contradiction. These are of course my personal views and you should feel free to comment on them or simply share your own views.

So let’s get started on these.

The Good Practices: When using data, there are a number of common-sense (or at least, they should be) practices. Among these I’d like to mention using descriptive file-naming, versioning, choosing a format that will ensure compatibility down the road (more on this below), using full metadata whenever possible and securing sensitive data from prying eyes.

The Bad Practices: You’re most likely expecting the opposites of the above and even though you’d be mostly true, there are some other aspects worth mentioning, things I’ve seen over the years—lack of fail safe backups is paramount. If there’s one thing I would never skimp on paying for is a good, reliable backup. Digging further down, an incredibly bad practice is hoarding data without making any sense of it. This usually happens when different systems that were not designed with legacy in mind are “talking” to each other and until that happens, data just keeps piling up. Chances are, if you’re not transferring and analyzing data in real-time, your data will keep adding up and nobody will *ever* get back to it to analyze it or get any business intelligence out of it. And last on my list is of course, poor or no data management protocol in your business. This is especially hurtful when there’s either a data handoff (merger, acquisition) or onboarding new technical analysts. It’s not a matter of “if”, but “when”.

And there’s the ugly side of things: I like to call these practices used “when things go south”, as in either very bad or sloppy. These are mostly consequences of bad practices, good practices with bad implementation or simply carelessness. One example that comes to mind is when data is lost on a hacked server and administrators are in a hurry to recover it—generally the newly available data is gibberish, unorganized and quite frankly, impossible to be used without great effort. In most cases, data recovery is sloppy at best, recovered “as-fast-as-possible” without any regard to the usefulness for the business intelligence department.

Another example that comes to mind is the collection of what we generally call “big data”. If you think you’ve seen this mentioned before above, at bad practices, you are right. But it’s worth mentioning again, because it has probably the ugliest sides of all to it, that could potentially destroy a business: misinterpretation of data and using information that is erroneous due to corrupt, incomplete/discarded or disregarded data.

This last example is particularly relevant for when you’re collecting information from outside your organization, from various sources in different formats, data that will be used in multiple ways across departments that will make critical financial decisions based on it.

Make no mistake of thinking that your organization is immune to these practices—companies are run by people and we are all bound to make some mistake at some point in our lifetime. The question is what are YOU doing to to mitigate these risks and employ only the best of practices when it comes to data. One thing you can do is to “prepare for unforeseen consequences”.

And we here at Gloobus can help you prepare for any data handling situation. We’re experts in real-time data exchange and we serve organizations just like yours from all over the world. Get in touch with us today to learn how you can efficiently get more out of your data.

Feel free to message me directly—I love to travel and I’m happy to give you a thorough demo of our capabilities.

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