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Data is an important part of our daily lives. Data analysis has great potential to transform businesses and improve their performance. To do this, we need to collect, store and manage big data effectively. There are mainly two types of data: structured data and unstructured data.

But beyond these two extremes, there is a third type of data that combines both. These types of data are called hybrid data sets. Examples include text documents with images, social media posts with geographic coordinates, and scientific research documents with metadata. This article, however, explores both structured and unstructured data.

 

1. Structured data

Structured data is just what it sounds like; data that is formatted and organized in some way. Data may be structured at many different levels. When organizing structured data we assign labels and values to each item in the dataset. For example, if I’m looking at customer records in a database, each record would have columns like first name, last name, address, city, state, zip code – all kinds of information about a person.

9 example use cases for structured data

1.1. Database table

A database table called Customer can have three fields: Name, Address, and Phone Number. In this example, each customer would have a row in the table. Each row could hold different values depending on what was entered. If you wanted to find out the name of the person who lived at 123 Main St., you could search for the row where the address field (field 2) had the value “123 Main Street”.

1.2. Images

An image file might have many records. One record may describe the color blue. Another record may describe the number of stripes. These two different records would both have columns and rows, just like the first example. You could use Image Recognition technology to recognize these images.

1.3. Customer Purchase Order

A Customer Purchase Order (CPO) transaction could be represented as a CPO document that includes details about the customer, purchase order, and any associated items. e.g. when you book flights online, you provide different information about yourself. You give your name, flight number, seat location, etc. All of these pieces of information are structured data that help airlines know where to send you luggage, where to put you on the plane, and how to get you to the destination safely.

1.4. Car sellers

A structured data format can be used to store a lot of information about a product. Think about how you would describe a car to someone who wanted to buy it. You'd probably use some kind of structured format (like JSON) to describe its make, model, engine size, price, etc.

1.5. Health centers

A structured data format could also be used to encode a human's medical history. If you had a patient record containing information about their medications, diagnoses, allergies, and surgeries, you could write that information down using a structured data format to create a record of what they've been doing.

1.6. Manage customers

A structured data format might even allow you to give a user access to a specific customer's account based on certain conditions. Say you have a website where users pay monthly fees to subscribe to different services. Each month, users receive an email telling them what they're paying for. You could save each subscriber's payment details in a database to provide a structured way of describing your customers' accounts. When a user wants to log in to their account, you could check whether they are eligible to use the service based on the conditions described by the structured data format.

1.7. Cooking recipe

A structured data format may even be used for something as simple as a recipe. Imagine you were making dinner tonight and needed to know what ingredients you should put in your pot for your spaghetti sauce. Instead of having to open up the cupboard, walk to the fridge, search for the spices, get out measuring cups, and read through a bunch of recipes until you find the right combination, you could simply let a computer do all the work for you. The cooking recipe would be saved in a structured data format, then once you start cooking, the computer could tell you exactly how much salt to add to your pan and how long to cook it for before turning off the stove.

1.8. Communication between websites

A structured data format isn't just reserved for storing data though. In fact, many websites use a structured data format to communicate with each other. An online retailer could send data to a manufacturer saying that they want a certain number of widgets produced. That manufacturer could respond back by sending the retailer a structured data format that says that they want to produce those widgets at no cost. Once the widgets arrive at the retailer's warehouse, the retailer could update their stock management software to reflect the order instead of manually recording it in an Excel spreadsheet.

1.9. Manage a site

Sometimes, we don't need a huge amount of data to be stored. We simply need a couple of pieces of information. For example, imagine you own a blog called "The Top 10 Things." You could use a structured data format to keep track of which posts you've written, which ones got the most views, and which ones have gotten the most comments. As users scroll through your blog, they'll see this information.

Pros and Cons of structured data

Pros
  • Easy to query – easily find out what happened at any point in time
  • Easily integrate with other systems
  • Information is easily shared across platforms
  • Structured data makes it easier for someone to understand what the information is and how to use it
  • It's easier to find relevant information about specific topics that interest you
Cons
  • Structured data is less flexible than unstructured data
  • You cannot delete fields from a database table if they have been used elsewhere, as they may be linked to other fields
  • When changing the name of a field in a database table, it will break all the old queries
  • Lack of Data: the collection of structured data requires a specialised team to avoid errors. This team will ensure that the confidentiality rule regarding the collected data is not violated and that the collected data is protected against hackers. Having such a team requires a considerable amount of resources

Structured data is essentially structured information that can be processed using special software programs. These programs can then be used to extract useful information from the data. In the context of web searching, structured data describes information that is organized into tables. In the context of business, structured data includes information about product and service offerings.

In addition to structured data, there is also unstructured data which, after deep exploration, can reveal valuable information.

 

2. Unstructured data

Unstructured data is any data that does not have a particular structure to it. Unstructured data is not organized in any way, meaning it's difficult to find specific information within the data. This makes finding useful facts about the data challenging. In terms of text mining this means that we cannot use regular expressions to find certain words or combinations of words in order to categorize information. These words may simply be missing or they could be present in various forms such as “I do” instead of just “do”, or “it was” instead of “was”.

There are many different types of unstructured data. Data that would fall under this category is text files, spreadsheets, images, videos, sound clips, email spam, phone calls, voicemails, social media messages, and even comments left on forums or blogs. In some businesses, these types of messages are often discarded because they are considered noise and do not provide relevant information about the business. However, some companies are using text analytics software to identify these messages and classify them for further analysis. Using the right tools for each type of unstructured data can help extract valuable information from otherwise useless messages.

6 example Use Cases for unstructured data

2.1. Customer Reviews

Customer reviews provide a unique perspective on the quality of products and services that companies offer. A customer review provides valuable information about how well the product works and whether or not it is worth buying. These reviews may range from simple text-based posts on social networks like Facebook or Twitter, to detailed text and video content on websites like .

2.2. Product Images

Product images are also valuable assets that companies need to manage properly. Like customer reviews they have two general types: visual and textual. Visual images provide a snapshot of what the product looks like, while textual descriptions describe the features and specifications.

2.3. Video Footage

Video footage is a great way for companies to showcase their products or services. It’s even possible to use videos to create a direct connection between potential buyers and company representatives. There are many different ways to use video footage for marketing purposes; some of them include product demonstrations, customer testimonials, event coverage, and Q&A sessions.

2.4. Audio Files

Audio files are a great way to capture a personal voice and personality behind a brand. For instance, if you were looking to promote your new fitness apparel line, audio clips of people wearing your clothes would help build excitement around your products. You can record these files yourself or hire outside recording studios to do it for you.

2.5. Surveys/Questionnaires

Surveys and questionnaires are both useful tools to collect feedback from consumers. By analysing the responses, it is possible to determine the likes and dislikes of certain brands. It also provides insight into consumer behaviour and buying habits. The survey results can then be analysed to identify any trends in demographics and preferences.

2.6. Web Analytics

Web analytics refers to the study of data collected from digital activities on websites, apps, and mobile devices. The data collected can be in the form of tables, texts or even images. This data can be used to measure website traffic, analyze user navigation, and track conversions. Companies interested in understanding how users interact with their websites can utilize web analytics to optimize site design and functionality.

Pros and Cons of unstructured data

Pros
  • Unstructured data is a great way to understand what is going on in your environment
  • The data can be obtained at anytime and anywhere, and at any rate
  • You can store everything you find (text, table, images, etc...)
  • Easy to edit. You can add new variables at will and change anything you deem necessary
Cons
  • Information is usually organized manually
  • It is harder to find specific information
  • There is no standardization to how information is encoded and presented
  • You need the right tools or services, and the right people to help you analyze the data and develop insights

Unstructured data can be defined as any type of data that cannot be easily organized and categorized into meaningful groups. Unstructured data can be difficult to manage, search, find relevant information in, or navigate around. However, with the right software tools, unstructured data can be converted into structured, easily consumable formats.

 

There are many use cases where ArerSoft can use structured or unstructured data to help you gained insight to your data.  Some example are text mining, image recognition, speech recognition, computer vision.