Stop waiting for 'perfect data' to start modernizing

Over the years, experts have become more specific about what needs to happen for "big data" to work. One consistent refrain has been that not just any data will do: Companies need to pay attention to the TYPES of data, rather, that they integrate into the cloud, and have reasonable goals for doing so. However, there's a problem with going too far in that direction, as Tech Republic recently touched on.

In an article concerning the "myths" of big data, the source mentioned the problems behind focusing on "clean" and "perfect data." Simply put, it could be unreasonable to demand data that is completely tidy.

Not only could doing so be time-consuming, it could also put impossible expectations on the project. Instead, one business intelligence director cited by the source suggested "diving in" when the data isn't immaculate, which could make it easy to see where the key problems lie.

It's possible to put too much focus on "clean" data in a big data project.

At the same time, there's one area where companies can afford to be careful: data security. In a recent article for InfoWorld, Adobe's VP of Mobile, Matt Asay, said that enterprise big data security has not been a huge priority over the years.

Even when it has been, Asay also said, the "rapid pace" of development makes it difficult to see security issues coming. Can enterprises still give their digital assets the protection they need without worrying too much about data perfection?

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