With so many businesses placing an emphasis on collecting and analyzing data, it’s important to take a closer look at the forms that data can come in. Data, after all, is the fuel that drives most companies nowadays. Even industries not normally associated with cutting edge technology are using massive amounts of data to gain a competitive advantage, lower costs, and optimize efficiency. The era of big data is here, and more companies than ever before are seeking to utilize it.
So with that in mind, it’s time to break down data into its types. Data can best be placed into two categories: structured and unstructured. Understanding the differences between the two is key to getting the most out of both of them, especially when it comes to benefitting from web data. Let’s tackle each one in turn.
What is Structured Data?
Most people are familiar with how structured data works. Structured data, as can be assumed from the term, is data that is highly organized and neatly formatted. It’s the type of data that can be put into tables and spreadsheets. It might not be the easiest type of data to look through for a human, but compared to unstructured data, it is certainly the easier of the two types for humans to consume. Computers, on the other hand, can search it with ease.
Structured data is also often referred to as quantitative data. These are objective facts which can be looked up in a relational database or a data warehouse. Customer data, for example, would include facts like the customer’s name and the transactions he or she engaged in. Searching for these terms would be easy for a computer program when using a structured query language or SQL.
Some other examples of structured data include credit card numbers, dates, financial amounts, phone numbers, addresses, product names, and more. These are all data points that aren’t open for interpretation, making it easy for big data applications to collect and analyze.
What is Unstructured Data?
As the term suggests, unstructured data isn’t so easily organized or formatted. Collecting, processing, and analyzing unstructured data also represents a significant challenge. That has created some issues since unstructured data makes up the vast majority of available data out there on the web, and it only grows larger every year. With more information becoming available on the web, and most of it unstructured, finding ways to use it has become a vital strategy for many businesses. More traditional data analysis tools and methods aren’t enough to get the job done.
Unstructured data can also be called qualitative data, which basically covers everything that structured data does not. It doesn’t conform to any predefined models, so it is stored in non-relational databases and is queried using NoSQL.
Unstructured data is also quite diverse, so examples can make up a long list. Some of the most common unstructured data examples include reports, audio files, images, video files, text files, social media comments and opinions, emails, and more. From these instances, it’s clear to see how analysis can be more complex, especially for computer programs to understand.
Structured vs. Unstructured Data: Getting to Know the Difference
From the above explanations, the differences between structured and unstructured data should become clear. Structured data is easy to collect, analyze, and store while unstructured data is unorganized and requires more work to properly investigate. Unstructured data also covers a lot more ground than the structured variety, with many more examples that are only growing as the internet continues to expand.
In a sense, unstructured data is similar to how we as humans process and analyze information. If you have a conversation with someone, all the information that is conveyed is done so in an unorganized fashion. Despite this, we’re still able to digest that data and understand it. Structured data, on the other hand, is more in line with how computers process data. It’s neatly organized and easy to analyze. Being able to analyze unstructured data through computer processes then becomes the challenge.
Understanding Unstructured Web Data
Data and computer programming experts have worked hard to make it easier to analyze unstructured data. Much progress has been made, and the future looks bright, especially when it comes to extracting and analyzing web data.
Luckily, making good use of web data is easier than ever with the Web Data Integration platform provided by Import.io. Unstructured data and alternative data can be analyzed for valuable insights that can greatly benefit your business.
Since unstructured data requires more specialized and advanced skills to analyze, having a platform or managed service like Import.io’s Web Data Integration solution becomes extremely advantageous. You can try out the SaaS version yourself by signing up for a free seven day trial, or you can let the experts handle all the hard work by talking to a consultant.