Every company has structured and unstructured data. Both types of data are valuable, and the difference between them matters more than you might realize. Each has pros and cons, they’re collected in different ways, and using each type requires a different approach.
Unstructured data is more difficult to work with and manage because there’s no single way to organize and make sense of the data. Some data processing solutions are better at handling unstructured data than others. To find the right one for your organization, it helps to understand the challenges unstructured data creates and the benefits you stand to gain by harnessing it.
AI brings clarity and organization to unstructured data that has been historically out of reach for companies. Using generative AI and large language models, Instabase helps companies unlock the value of unstructured data with easy-to-use apps that don’t require engineering or coding. Let’s explore the differences between structured and unstructured data and how AI can help you tap into the value of your unstructured data.
What Is Structured Data?
Structured data is information that has a defined, standardized structure. This type of data is typically organized in a table, such as a database or a spreadsheet, where each column represents a different attribute and each row represents a complete record of information. This defined structure makes locating information, comparing data, and conducting analysis easier.
Examples of Structured Data
- Digital forms, such as job applications or check-out pages
- Financial records
- Customer relationship management (CRM) systems
- Reservation systems
| Pros | Cons |
|---|---|
| Easily accessed, searched, sorted, compared, and analyzed | Limited flexibility, making it difficult to add new data that follows a different schema |
| Maintains data integrity due to its defined structure | Can only be used for its intended purpose |
| Integrates with applications and systems | Can only be stored in systems with a predefined schema |
| Efficient to store and retrieve, which can lead to lower storage costs |
What Is Unstructured Data?
Unstructured data is data that doesn’t follow any predefined schema. As a result, it can’t be stored in relational databases. About 80% to 90% of business data is unstructured, which means that companies have a wealth of information and insights hidden in unstructured data and it’s incredibly important for companies to understand and make use of their unstructured data.
Examples of Unstructured Data
- Handwritten medical records
- Social media posts, which usually include a mix of text, images, and links
- Emails
- Business contracts and agreements
- Media files such as videos or audio files
- Web pages
- Business presentations and notes
| Pros | Cons |
|---|---|
| Can be highly detailed and contain nuanced insights | Difficult to organize, search, manage, and access |
| Flexible, as it can capture a diverse range of information | Requires expertise to process and analyze in order to extract meaningful insights |
| Stored in its native format, which makes it adaptable to other formats | Often requires specialized tools to manipulate the data |
| Rapidly accumulated since it doesn’t need to be formatted before it’s stored | Requires more storage space |
| Multiple use cases, such as discovering consumer sentiment, real-time decision making, or developing effective marketing strategies | Quality and accuracy can vary due to the lack of a defined structure |
| Typically stored in data lakes, which is cost-effective | May be harder to protect sensitive information due to diverse formats and storage needs |
KEY DIFFERENCES
Structured Data vs. Unstructured Data
Both structured and unstructured data provide businesses with valuable insights. Let’s compare these two data types to further identify the differences between them.
| Structured Data | Unstructured Data | |
|---|---|---|
| Data Types and Formats | Typically quantitativeMust adhere to a defined formatOften takes the form of text, numbers, and values | Typically qualitativeDoes not adhere to a specific formatOften takes the form of multimedia, freeform text, images, and documents |
| Storage | Spreadsheets, SQL databases, and data warehousesTakes up less space, making it highly scalable | Data lakes and NoSQL databasesTakes up more space |
| Use Cases | Typically limited to its intended useUsed to understand quantitative aspects of a businessAccounting, inventory management, e-commerce, reservations, customer relationship management, and more | Can be used for a wide variety of use casesUsed to understand qualitative aspects of a businessBusiness decision-making, trend predictions, sentiment analysis, and more |
Data Types and Formats
Structured data is typically quantitative, consisting mostly of text, values, and numbers that adhere to a specific structure or schema.
Unstructured data can come in a range of formats, including audio files, freeform text, images, documents, and videos. It can come from a myriad of sources, from internal meetings to social media to press releases and more.
Storage
Structured data lives in spreadsheets, SQL databases, and data warehouses — storage systems that have rigid schemas and are highly scalable.
Unstructured data lives in data lakes or non-structured relational databases (NoSQL). They might also be part of file systems that don’t impose a rigid structure and can handle diverse data types. Because unstructured data includes media files that can be large in size, you’ll need more storage space compared to storing structured data.
Use Cases
Due to its predefined nature, structured data can only be used in the way it was intended, limiting its flexibility. Structured data tends to be the norm in scenarios that require reliability and data integrity. Examples include inventory management, reservations, and customer relationship management.
In comparison, unstructured data can be used in a variety of ways and is ideal for scenarios that require holistic or nuanced views of various and complex data. While structured data is quantitative, unstructured data is more qualitative. It can help companies make decisions that impact customers, employees, and operations. For example, it can be used to predict trends or analyze customer sentiment, which can then inform new products or marketing strategies.
Overcoming the Challenges of Working With Unstructured Data
While both types of data are essential to business, it’s especially important for companies to find ways to work with unstructured data. As much as 90% of enterprise data is unstructured, but only about 0.5% of this data gets used. This leaves a wealth of insights on the table that could play a transformational role in your business.
Traditional data or document processing solutions that use rules or templates aren’t able to handle the complexity and variability of unstructured data. These solutions lack the contextual element required to make the best use of this data. However, the advancements in AI have made it the best type of solution for efficiently working with unstructured data.
In the beginning, heuristics were easy and quick to implement but could result in inaccurate outputs. Then there was machine learning, which was too intensive in terms of computational power and volume of data. Although deep learning was a notable improvement due to its use of neural networks, it was still an intensive process. Now, large language models and generative AI represent a step change in AI’s ability to interpret, handle, and automate processes that involve unstructured data.
AI’s ability to recognize patterns, continuously learn, predict outcomes, and understand context form the backbone of its transformative impact across various functions. It can:
- Identify patterns within large datasets that would evade the human eye.
- Learn from data and user input to become more intelligent over time.
- Make predictions based on historical data.
- Grasp nuances and make decisions based on the current environment and conditions.
Instabase uses AI to solve the challenges of working with unstructured data while making AI technology accessible and user-friendly to non-technical users. Our no-code solutions use large language models and generative AI so that it’s as simple as using natural language prompts to tell an application what you’d like to do with your data. With Instabase, manipulating and working with data doesn’t require SQL or Excel skills, nor do you need engineers to build data workflows.
Instabase AI Hub is an enterprise content activation platform that turns content and data into insights and actions. Users can put their unstructured data to work with our range of out-of-the-box applications. You can use the Instabase Converse app for one-off needs, such as pulling text from a screenshot. Or, try the Build app to create repeatable workflows, such as organizing expense reports and receipts. Whether you need to extract information from handwritten forms, summarize social media content, or analyze multiple charts, Instabase makes it easy to unlock the value of your data and automate these processes.
Enterprise companies across industries are already using Instabase to operate more efficiently and free up employees to focus on more strategic or growth-oriented work. For example, Sonic Automotive, one of the nation’s largest automotive retailers, uses Instabase to streamline invoicing and vendor payments. Invoices from different vendors vary in format, which has required Sonic Automotive to manually process in the past. By using Instabase, they can automatically extract key information from invoices and integrate them with downstream systems to reduce payment processing times.
Commercial insurance provider AXA is also using Instabase to reduce manual, repetitive tasks for their underwriters. In an industry that’s still very paper-heavy and reliant on manual processes, Instabase is automating data extraction from various sources, such as emails, presentations, documents, and Excel sheets, which frees up time for underwriters to apply their skills to making underwriting decisions.
These are just a few of the many ways Instabase helps companies harness the power of their unstructured data. Discover all the potential ways you can use Instabase by creating your free account today.
Harness the Power of Your Unstructured Data
Use Instabase AI Hub to uncover the insights you need from documents, images, and more.
