We often hear jaw-dropping statistics about big data and what it can do for your company. However, all of these wild claims assume that your data is already in pristine condition and is ready for processing. You can’t derive useful insights from data if it’s not curated and ready for analysis. One of the biggest obstacles is dealing with structured vs unstructured data.
Before you can properly analyze your data, you need to know what you’re dealing with. You almost certainly have a large quantity of both structured and unstructured data in your organization. So, how can you tell which is which?
Structured data is so named because all of the data in the set follow rules. These rules give the data structure and allow us to easily search and sort the data. A good example of structured data are values in an Excel sheet. Each cell contains a string of data that must conform to Excel’s rules, and each cell is identified by a column and row code. We could ask Excel what’s in cell B7, and we’ll get a specific piece of data.
On the other hand, unstructured data doesn’t play by any rules. For instance, consider the text in an email. An email may have no text at all, or it could contain a whole novel. Is that really a problem, though?
Unstructured data is most commonly accessed by the same program that created it. If you want to search your Gmail inbox, you go into Gmail and use its search tool. This means that much of your unstructured data goes unseen by data management software, and this is a serious problem for your business.
When data gets locked into a single environment, unable to be accessed by certain people or only accessible through certain platforms, it’s in what we call a data silo. This presents risks to your business since you often won’t know what’s actually in each silo. Furthermore, silos frequently create redundant data which could pose a security risk. But unstructured data isn’t the only way silos form.
Structured data can also be siloed off if it’s not easily accessible. While it’s easier to search and identify data from structured files, access permissions often keep the doors to the silo locked shut.
Although both forms of data can end up in silos, unstructured data is more likely to do so. Furthermore, unstructured data loves to hide in the dark. Since it’s often only accessible with a specific program, your average search tool or data management platform just isn’t going to find it. Data of any kind can become dark data, lurking in the shadows of your organization.
Dark data may very well be worse than a data silo. In a sense, it already is. You can’t see dark data because you don’t know where it is, and even if you find a rogue file, you won’t know what’s in it. Since unstructured data readily evades detection, it tends to remain dark. You can’t derive insights from data you don’t know about, but you certainly can suffer the consequences of dark data.
Many companies discover data breaches well after the fact. Just recently, Mobikwik’s customers discovered their own data for sale on deep web markets. Mobikwik had no idea anything had happened, and still denies responsibility, but the breach seems to be from months ago. When your data is dark, you can’t keep an eye on it and you might only find out about it in the worst of circumstances.
So, how do you put a stop to data silos and make all of your data searchable and useful? In comparing structured vs unstructured data, it’s clear that while structured data is easy to manage, unstructured data is going to create headaches for your business. An automated platform built specifically for tackling the problem of unstructured data is what you need.
Aparavi integrates your entire file system and searches for data in every nook and cranny. It reads the contents of unstructured files and give you an idea of what’s inside with its smart automated classification tools. All of your files instantly become assets when you have automation at your service.
Try Aparavi for yourself, Get a demo and see how quickly it can make even the most difficult data a pleasure to process.