Unstructured vs. Structured Data: Understanding the Differences

We all know that capital is critical for running business operations smoothly  but what many organizations don’t know is that data holds the same value and even more than capital. Today, you need to deal with different formats of data from relational databases to social media posts. So, there is a need to understand two main types of data such as unstructured and structured data. You must know what they are and how one type is different from another. Let’s get started.

What is Structured Data?

It is a type of data that can be organized in a table format, you can easily fit this data into rows and columns.


The best example of structural data is supplier databases. Your company can create a database of suppliers where they set one row each supplier while column provide details of every supplier name, address, etc.You can easily add name, number, location, and other details in this table.

What is Unstructured Data?

It is a type of data that can’t be organized in a table unless you identify or categorize it. 


The best examples of unstructured data are social media comments, open end Q&A of a survey.

Unstructured vs. Structured Data: Understanding the Differences 

Here are some main points of differences between both types of data.

Storage-Unstructured vs. Structured Data

When it comes to storing your data, you can easily store Structured Data with great speed because it’s already organized. But, you can’t store unstructured data efficiently unless you rely on AI or ML tools and platforms. Unstructured data will take more space, time, and resources of your storage than its structured counterpart. 

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Once you store both data, you can retrieve structured data. But the retrieval process of unstructured data will be neither efficient nor accurate, unless you use Sharearchiver’s e-discovery tools.

Normally structured data is stored in relational databases, HR records, spatial databases and OLAP. On the flip side, unstructured data stores include CMS -content management system, version control systems, DAM-Digital asset management systems, and file systems. 

Data format-Unstructured vs. Structured Data

Structured data always follow a strict format, which is a predefined data model-known as schema. Unstructured data, on the other hand, doesn’t follow any strict format. For example, the format of some audio surveillance files will be available in MP3 format while a video about the company will be available in MP4 format.

Analysis-Unstructured vs. Structured Data

Keeping your data store isn’t just the one goal you have in mind. You store data to make the most of it. In other words, you need to get insight through analysis. Since structured data is already organized, you can analyze it through programming logic. But unstructured data is going to give you a tough time. It will require advanced analytics tools that help you define and understand sentiments, data types, data patterns, and topics.As a result, structured data processing and analysis is usually faster than unstructured data.

If you want to analyze structured data, then SQL is the first choice of technology.However, organizations also utilize other techniques such as programmatic manipulation, machine learning, visualization and modeling. You can analyze unstructured data through complex programmatic manipulation, artificial intelligence, and machine learning technologies.

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Uses-Unstructured vs. Structured Data

Your business digital world requires both kinds of data. However, you use them for different purposes. Normally, structured data helps you analyze discrete, numeric data. You can easily perform scientific modeling and get insight into financial operations through it. This data is widely use in HR departments where you need to keep a database of your employees. Other uses of this data are inventory listing.

Unstructured data is used to maintain a record of the data that normally doesn’t fit in a scheme format. For example, you have to maintain a proper record of social media comments/posts, business documents, video and audio files of surveillance, etc.

Management–Unstructured vs. Structured Data

Since structured data is uniform and you can easily adjust it into relational databases, thereby it’s quite easy to manage and maintain. 

On the flip side, you can’t understand unstructured data unless you use some advanced tools such as Sharearchiver, it will help you analyze your data and get valuable insight from it. As structured data is quite sophisticated and have multiple format and no-structure, so it will always be a challenge to manage it on your own

Search-Unstructured vs. Structured Data

Let’s say you maintain a record of both structured and unstructured data and now you need to find specific data. It means you need to run some search to find data you are looking for. Now another difference between structured and unstructured data is the search process, which is quick and easy for structured data and quite complex for unstructured data.

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Finally, you are in a position to differentiate unstructured data from a structured one. I have provided you with examples of both types, so next time you need to manage either time, you are clear what type of data you are dealing with. If you want to manage and analyze your unstructured data efficiently without compromising its quality or integrity, it’s suggested to rely on Sharearchiver.