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The year is 1985 and Microsoft has just released the first ever version of Excel. In the same month, David Bowie and Mick Jagger release the infamous music video for ‘Dancing in the Street’. Both were major hits at the time. But, flash forward to today, and neither has aged particularly well.
The difference is that while most people accept Jagger’s theatrics as a flamboyant disaster, 70 percent of us still rely on Excel for everyday data preparation and reporting. In many cases, it even acts as an intermediate data store when moving data from one application to another.
The issue with this approach is that Excel was never designed to handle the large-scale data volumes we see in modern business. Yet, more than two-thirds of organizations still see it as the best form of data management.
So, are there really no better solutions available?
Fortunately, no. In this article, we’ll explain why exporting to Excel is no longer the gold standard of data preparation and offer an alternative approach.
Change is never easy – especially if you’ve relied on the same data management tool for the last 30 years. But just because you’ve always done things a certain way, doesn’t mean it’s right. While Excel is great for simple calculations in restricted datasets, it is not a database software.
Here are some of the drawbacks of exporting complex data to Excel:
If you’re struggling with any of these issues, now is the time to consider a new method of data preparation and reporting.
Okay, so we’ve established that Excel is a bit of a fixer-upper. But, since it doesn’t seem to be going anywhere any time soon, is there a way to export your data that is relevant, accurate, and consistent?
The answer, of course, is yes, but most of these methods require clunky, complex code. So, again, you’re at risk of human error. And, even if there is a native Excel export in the application you’re using, it won’t always be enough. Common problems with this approach include:
Of course, you could always convert your data to a Text or XML file. But this often results in the same issues.
Fortunately, this is where an automated integration tool comes into play. With CloverDX, for example, you can generate XLS/XLS(X) file formats effortlessly without the need for any coding.
Here are a few key benefits:
If you’re doing a one-time analysis, you’ll likely be okay with the way you’ve been exporting your data. But, if you find yourself repeating the same processes on your data regularly, it’s better to implement CloverDX’s automated integration tool. This could end up saving you weeks’ worth of work.
In this scenario, you can use CloverDX to integrate your data directly with the new application, cutting out the need for Excel entirely.
While Excel remains a stalwart of workplace activity, it’s no longer the smartest application on the block. When exporting your data to Excel, you need to question exactly why you’re doing it. Is it to quickly query and analyse a static dataset? Or are you stretching the app beyond its original intentions?
If, like many organizations, you’ve become over reliant on Excel for heavy-duty data migrations and reporting, you could be limiting your ability to make accurate and progressive decisions. Don’t wind up stuck in 1985 – choose a more modern approach to data management and stay in control of all your data processes.
Editor's note: We updated this blog posts in October 2019 to add new, relevant content. Enjoy!