Structured Data vs Big Data

YOU HAVE NOW ENTERED THE DATA DIMENSION. WE HOPE YOU ENJOY YOUR STAY.


Structured Data vs Big Data

Data is essentially any information that can be stored on a computer. Some of the most common types of data are characters, strings, integers, floating-point numbers, and booleans. The number of visitors to a website is considered data. Even something like your name is considered data.

There are two more types of data, though: structured data and big data. How do you differentiate these? That isn’t something that comes very easy, since even structured data can fall into big data at points. That said, there are a few key differences. If you’re already familiar with structured data, then this blog post should provide a nice transition into big data.

Let’s start off with structured data. There are other types of data like semi-structured and unstructured data, but let’s just focus on structured data for now. It's a type of data where you know the structure of the data well in advance so you know how to store, access, and process it. It’s like you already have a blueprint of a house that you want to build. For example, you know that names are always strings, and that age is always an integer. You obviously cannot say that your name is 7 or that your age is yes. Traditionally, structured data is mainly stored in data tables. Has your science teacher ever told you to record the results of a lab in a data table? That can be seen as structured data. It’s often stored in relational databases, such as the aforementioned data tables. You can access and process structured data using structured query language (SQL).

Now, what is big data? In a nutshell, it’s a collection of data that’s huge in volume and only gets bigger over time. It’s like the universe itself, it’s already humongous and yet it only expands rapidly over time. For example, take any social media site, like FaceBook or Instagram or Twitter. The new data that gets ingested into their databases can exceed 500 terabytes every day. This isn’t structured data like your name. This includes pictures, video, chats, comments, etc. Now I can’t imagine how these can be stored in a data table.



Many data professionals describe the four characteristics of big data as four V’s: volume, velocity, value, and variety.

Big data is very large in volume, as discussed earlier. Big data is generated even just through your phone. 6 billion of the 7 billion people in the world have a phone, so that should give you an idea of how big it truly is.

Velocity, or speed, is commonly used in physics classes, but in the context of data, the velocity refers to the speed at which the data is generated and processed. It’s how when texting, your messages get sent to the person within seconds.

This data has a wide variety generated from every sector in society today, ranging from medical to business to gaming to even this very blog itself. The volume and variety will only continue to increase in the future

Veracity is how truthful the big data is, since it can quickly become outdated or incorrect. Not all information shared through the internet is correct. Think of the misinformation cycle seen during the 2020 elections.

This should probably give you a sense of how big of a challenge it is to organize and access the correct data since if big data is organized and used correctly, it can be very helpful in our lives.

YOU ARE NOW EXITING THE DATA DIMENSION. SEE YOU SOON!

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