Everything You Need to Know About Unstructured Data Processing

Riley Walz

Dec 11, 2024

man helping a junior - Unstructured Data Processing

Consider you’re a data analyst. It’s the end of the quarter, and you need to present your findings to stakeholders. You’ve crunched the numbers, and now you need to organize and analyze hundreds of customer feedback surveys to understand better how their responses impact business performance. The problem? Most of the feedback is unstructured data. No one enjoys the tedious task of processing unstructured data, but it’s vital to your analysis.

With the best AI for Excel tools, you can automate unstructured data processing, quickly generating the insights you need to create a thorough report for your stakeholders. This guide will help you get started. We’ll cover everything you need to know about unstructured data processing, including how it works, why it’s essential, and best practices for analyzing unstructured data.

One of the best tools for speeding up unstructured data processing is Numerous spreadsheet AI tool. This powerful Excel add-in uses artificial intelligence to help you make sense of your messy data by rapidly identifying patterns, trends, and anomalies that can lead to better business decisions.

What is Unstructured Data?

data flowing - Unstructured Data Processing

Unstructured data is information that doesn’t fit neatly into tables or spreadsheets. Think of everything you do daily that isn’t organized in rows and columns—like social media posts, customer reviews, emails, photos, videos, and even voice recordings. It’s everywhere: A tweet about a product is unstructured. A video ad you watch is unstructured. That long customer email explaining a complaint? Also unstructured. Unlike structured data, which is clean, organized, and easy to plug into databases (like sales numbers or inventory lists), unstructured data is more chaotic but filled with valuable insights if you know how to dig in.

What Makes Unstructured Data Special?

Unstructured data is messy, but it’s rich in details that can give businesses a deeper understanding of their customers, products, or trends. Here’s what makes it stand out:

No Fixed Format

It doesn’t follow a standard structure. For example, a video file or a customer comment doesn’t fit neatly into rows like an Excel sheet.

It’s Everywhere and Growing Fast

Did you know unstructured data makes up over 80% of all data worldwide? And it’s growing every second—think of all the photos uploaded to Instagram or product reviews left on Amazon daily.

Full of Insights

It tells stories that numbers alone can’t. A customer review, for example, doesn’t just tell you if someone liked your product—it tells you why they liked it or what went wrong.

How is Unstructured Data Different from Structured Data?

Consider two types of information:

Structured Data

Think of a neat, organized spreadsheet where everything has its place. For example, a sales report might show rows for each product sold and columns for the quantity, price, and total revenue. It’s easy to read, search, and analyze.

Unstructured Data

Now consider a jumble of information like customer emails, social media posts, or photos. There’s no clear format, so it’s not as easy to organize or analyze. For example, a tweet about your product might contain words, emojis, hashtags, and links—it doesn’t fit neatly into rows and columns.

Why Does Unstructured Data Matter?

This data type might seem tricky, but it’s incredibly valuable. Here’s why:

It’s All About the Details

Structured data can tell you that sales are down, but unstructured data explains why—like a flood of customer complaints on social media about a packaging issue.

A Goldmine for Businesses

It helps you understand customer feelings (sentiment analysis), predict trends, and discover untapped opportunities, such as new product ideas, based on customer feedback.

Cross-Industry Impact

Retail: Organize product reviews by sentiment to see what’s working and what’s not.
Marketing: Analyze social media buzz to fine-tune campaigns.
Customer Service: Identify recurring issues from email complaints to improve service.

Why is Processing Unstructured Data Important?

output of data - Unstructured Data Processing

Uncover Hidden Insights in Unstructured Data

Unstructured data is everywhere—tweets, emails, customer reviews, videos—packed with helpful information. But it’s like leaving a goldmine untouched if you don't process it. Understanding customer sentiment is one of the most valuable applications of unstructured data. Businesses can learn how customers feel about their products or services by analyzing reviews or social media comments. For instance, are they happy with your new feature? Or are they frustrated about delays? Processing unstructured data also helps you spot trends and predict behaviors. For example, analyzing Instagram posts can reveal trending colors or styles that could inspire your next product launch. The clearer picture you get from unstructured data can lead to better decision-making. By combining unstructured data with structured data (like sales numbers), you understand what’s going on. If sales drop, unstructured data might show that negative social media feedback about a new policy is the reason.

Unstructured Data: It’s Too Big to Ignore

Unstructured data makes up over 80% of all data created globally. Daily, people generate billions of social media posts, emails, and other unstructured content. If you’re not processing this data, you’re missing out on understanding most of your customers’ thoughts and behaviors.

Real-Life Applications of Processing Unstructured Data

Here’s how businesses are already benefiting from it:

E-Commerce

Categorize thousands of product reviews into “positive,” “negative,” or “neutral” categories to improve offerings.
Use customer feedback to identify common complaints and fix issues quickly.

Marketing

Analyze social media conversations to determine what’s trending and adjust campaigns to suit your audience's mood.
Generate hashtags and captions that resonate with specific customer groups.

Customer Service

Process emails and chat logs to identify recurring problems, which will help you improve your support systems and reduce response times.

Healthcare

Extract insights from doctors’ notes, patient feedback, or scanned medical records to improve care and identify trends.

The Risk of Ignoring Unstructured Data

If you’re not processing unstructured data, you’re leaving valuable insights on the table. Here’s what can go wrong:

Missed opportunities

You need to analyze social media or reviews to see trends that competitors are capitalizing on.

Wasted time

Trying to sort through emails, comments, or logs could be faster, error-prone, and more efficient.

Incomplete strategies

Relying only on structured data gives you a limited view, which can lead to better decisions.

The Potential of Automation in Processing Unstructured Data

Manually processing unstructured data is nearly impossible because of its volume and variety. This is where tools like Numerous come in. With AI-powered solutions, businesses can quickly analyze unstructured data, transforming it into actionable insights without the headaches of manual sorting or analysis. Processing unstructured data isn’t just a trend—it’s becoming essential for staying competitive in today’s fast-paced world. In the next section, we’ll talk about how this process works!

Make Decisions At Scale Through AI With Numerous AI’s Spreadsheet AI Tool

Numerous is an AI-powered tool that enables content marketers, Ecommerce businesses, and more to do tasks many times over through AI, like writing SEO blog posts, generating hashtags, mass categorizing products with sentiment analysis and classification, and many more things by simply dragging down a cell in a spreadsheet. With a simple prompt, Numerous returns any spreadsheet function, simple or complex, within seconds.

The capabilities of Numerous are endless. It is versatile and can be used with Microsoft Excel and Google Sheets. Get started today with Numerous.ai so that you can make business decisions at scale using AI in both Google Sheets and Microsoft Excel. Learn more about how you can 10x your marketing efforts with Numerous’s ChatGPT for spreadsheets tool.

How Unstructured Data Processing Works

how processing works - Unstructured Data Processing

Gathering the Goods: Data Collection

Processing unstructured data begins with gathering the information. Unstructured data sources include social media platforms like Twitter and Instagram, emails, customer feedback, chat logs from customer support systems, scanned documents or PDFs such as invoices or contracts, and multimedia files like images, videos, and audio recordings. The collection phase can be tedious, requiring manual extraction from each source. Automated tools like APIs, web scrapers, or customer relationship management (CRM) systems can help pull data directly from relevant sources to streamline the process.

Cleaning Up: Data Preprocessing

Once you gather the data, the next step is to clean it up, removing any errors or irrelevant information to make it usable. Unstructured data can be messy containing lots of noise, so it needs to be organized before you can analyze it. Some standard preprocessing techniques for unstructured data include:

Text Cleaning

This technique removes irrelevant data like punctuation, special characters, or duplicates.

Tokenization

This process breaks text into smaller units, such as words or phrases, for easier analysis.

OCR (Optical Character Recognition)

This tool extracts text from scanned images or PDFs.

Normalization

This method standardizes data formats, such as converting text to lowercase or using consistent date formats.

Structuring the Data: Transformation

Unstructured data must be converted into a format that analytics tools can handle. Here's where the real fun begins! Natural language processing (NLP) tools analyze text-based data to identify patterns, extract keywords, or perform sentiment analysis. For example, NLP can categorize customer reviews as positive, negative, or neutral. It can also identify frequently mentioned words in social media comments. You can also use computer vision to recognize objects, faces, or scenes in photos and videos. For example, a retail company might analyze customer-uploaded photos to identify popular products. Finally, audio analysis can transcribe and analyze audio recordings to detect sentiments or key themes in calls or podcasts.

Crunching the Numbers: Data Analysis and Interpretation

Once the data is structured, it is ready for analysis. Techniques for analyzing unstructured data include:

Sentiment Analysis

This method helps you understand how customers feel about your brand or products.

Classification

This process sorts data into categories, like sorting emails into “urgent” or “non-urgent.”

Trend Analysis

This technique identifies patterns or emerging topics from social media conversations or customer reviews. Let’s look at an example. An e-commerce company might use sentiment analysis to determine which products customers love and which need improvement.

The Tools of the Trade: Technologies Used in Processing

Processing unstructured data requires advanced tools and techniques. Here are some of the most common:

AI and Machine Learning (ML)

AI models can quickly process large datasets and identify patterns humans might miss.

NLP Tools

OpenAI, Numerous, and Google NLP APIs are popular for analyzing text-based data.

Data Management Tools

Data lakes or cloud platforms like AWS and Google Cloud store and manage large volumes of unstructured data.

How Automation Speeds Up Processing

Manual processing of unstructured data is time-consuming and prone to errors, so automation is critical. Here’s how automation helps:

Speed

Automation speeds up data cleaning and analysis, reducing turnaround times.

Accuracy

Automation improves accuracy by eliminating human errors.

Scalability

Automated processes scale quickly to handle large datasets that would overwhelm manual workflows. Let’s look at an example with Numerous. Consider you’re categorizing hundreds of customer reviews by sentiment. Instead of manually reading each review, you can use Numerous’s AI-powered tools to do it automatically within a spreadsheet. With a simple prompt, the tool can classify the reviews as positive, negative, or neutral in seconds.

The Final Output: Transforming Data into Insights

After processing, the unstructured data is transformed into actionable insights that businesses can use. Here are a few examples of the final outputs:

Reports showing customer sentiment trends over time.
Visualizations highlighting key areas of customer interest or concern.
Predictive models that help forecast future customer behavior or market trends.

Challenges in Processing Unstructured Data

woman facing challenges - Unstructured Data Processing

The Scale of Unstructured Data: The Sheer Volume of Unstructured Data Can Be Overwhelming

Social media platforms, emails, customer reviews, and multimedia files produce terabytes of unstructured data daily. It’s nearly impossible to process such a large volume without efficient tools manually. Unstructured data isn’t slowing down—it’s growing exponentially. Businesses must keep up or risk falling behind competitors who use this data to gain insights.

Diversity of Formats: Unstructured Data Comes In Many Forms

Unstructured data comes in many forms—text, images, videos, audio files, etc. Each format requires a unique approach for analysis. For example, emails or customer reviews need natural language processing (NLP) to extract insights. Next, images and videos require computer vision algorithms to identify objects or patterns. Finally, voice recordings need transcription and sentiment analysis to be functional. Processing multiple formats simultaneously can be complex without the right tools.

Noise and Irrelevance in Data: Unstructured Data Often Contains “Noise”

Unstructured data often contains “noise” that isn’t useful for analysis, such as spam, irrelevant comments, or duplicate entries. For instance, a company analyzing tweets about its product might encounter posts filled with irrelevant hashtags or unrelated content. Cleaning and preprocessing noisy data takes significant time and effort, mainly manually.

Lack of Organization: Unstructured Data Has No Inherent Order

Unlike structured data, which fits neatly into databases, unstructured data has no inherent order. Organizing unstructured data into usable formats is fast and efficient with proper tools. For example, finding specific pieces of information in unstructured data can feel like searching for a needle in a haystack.

Technical Requirements: Processing Unstructured Data Requires Advanced Skills

Processing unstructured data often requires advanced technical skills and infrastructure. Businesses need experts in machine learning, NLP, or big data processing, which can be costly and difficult to hire. Additionally, handling large datasets requires powerful servers, cloud platforms, or data lakes—resources, not all businesses have readily available.

Overcoming These Challenges with Automation: Modern Tools Make Unstructured Data Processing Manageable

Thankfully, modern tools like Numerous make these challenges more manageable. For one, Numerous can handle massive datasets in seconds, reducing the burden on your team. Next, it supports text, sentiment, and classification analysis within spreadsheets, making processing and organizing diverse data formats easy. Finally, with intelligent algorithms, Numerous can quickly clean data, removing irrelevant or duplicate entries so you only analyze what matters.

How Numerous Can Simplify Unstructured Data Processing

What Makes Numerous Different?

Numerous transform unstructured data processing by embedding AI technology directly in spreadsheets like Microsoft Excel and Google Sheets. It transforms complex data processing tasks into simple, user-friendly actions that anyone can perform with just a few clicks.

No Technical Expertise Required

You don’t need to be a data scientist to process unstructured data. Numerous allow users to input simple prompts and get instant results without coding knowledge.

Fast and Scalable

Whether you’re processing six entries or 6,000, Numerous handles the workload quickly, saving hours of manual effort.

Versatility Across Data Types

Numerous accommodates diverse unstructured data formats from text to images and even sentiment analysis.

Examples of Numerous Action

Numerous offer practical solutions for real-world unstructured data challenges. Here’s how it works in three different scenarios.

Scenario 1: Sentiment Analysis on Customer Reviews

Consider you run an e-commerce store with thousands of product reviews. You want to know whether customers are happy, dissatisfied, or neutral about your products.

How Numerous Helps

Input the reviews into a spreadsheet.
Use a prompt like “Classify reviews as positive, neutral, or negative.”
Numerous data processes are used to categorize each review instantly.

Benefit

Quickly understand customer sentiment and identify areas for improvement without manually reading every review.

Scenario 2: Categorizing Social Media Comments

You’ve launched a marketing campaign on Instagram and need to analyze hundreds of comments to gauge the response.

How Numerous Helps

Import the comments into a Google Sheet.
Ask Numerous to “Group comments by keywords like ‘love,’ ‘hate,’ or ‘confused.’”
The tool organizes the comments into clear categories for analysis.

Benefit

Gain insights into how people perceive your campaign and adjust your strategy based on the feedback.

Scenario 3: Product Categorization for E-commerce

You need to organize a list of 5,000 products into categories like “clothing,” “electronics,” and “home goods.”

How Numerous Helps

Upload the product names and descriptions into Excel.
Use a prompt such as “Categorize products based on their descriptions.”
Numerous analyses of the data were performed, and accurate categories were assigned.

Benefit

Save time and ensure consistency across product listings, making your online store more straightforward to navigate for customers.

Key Features of Numerous Unstructured Data

Numerous offer several powerful features designed to make unstructured data processing smooth:

AI-Driven Functions

Numerous uses of advanced AI to process data based on your prompts, whether you’re classifying, summarizing, or transforming information.

Customizable Automation

You can tailor processes to fit your needs, such as extracting specific phrases, categorizing data, or filtering out irrelevant information.

Built-In Scalability

Numerous works equally well for small and massive datasets, ensuring businesses of all sizes can leverage their capabilities.

Smooth Integration

It connects effortlessly with Google Sheets and Excel, letting you work within familiar platforms without additional software.

Why Numerous is a Game-Changer for Businesses

Time-Saving Efficiency

Manual data processing could be faster and more labor-intensive, especially with unstructured data. Numerous automates these tasks, reducing hours of work to seconds.

Actionable Insights at Scale

Numerous transform messy, unstructured data into clean, organized formats, allowing businesses to extract insights that drive better decision-making.

Affordable and Accessible

Unlike expensive, complex data analysis tools, Numerous brings advanced capabilities into widely used spreadsheets, making it a cost-effective option for businesses.

Real-World Benefits of Using Numerous

For Content Marketers

Analyze customer feedback on blog posts, campaigns, or products to fine-tune strategies.

For E-commerce Businesses

Easily categorize products, analyze reviews, and predict customer preferences.

For General Business Use

Organize internal documents, sort through emails, or analyze meeting transcripts to identify key themes.

Make Decisions At Scale Through AI With Numerous AI’s Spreadsheet AI Tool

Numerous is an AI-powered tool that enables content marketers, Ecommerce businesses, and more to do tasks many times over through AI, like writing SEO blog posts, generating hashtags, mass categorizing products with sentiment analysis and classification, and many more things by simply dragging down a cell in a spreadsheet. With a simple prompt, Numerous returns any spreadsheet function, simple or complex, within seconds.

The capabilities of Numerous are endless. It is versatile and can be used with Microsoft Excel and Google Sheets. Get started today with Numerous.ai so that you can make business decisions at scale using AI in both Google Sheets and Microsoft Excel. Learn more about how you can 10x your marketing efforts with Numerous’s ChatGPT for spreadsheets tool.

What is Unstructured Data?

Unstructured data is information that doesn’t fit neatly into tables or spreadsheets. Think of everything you do daily that isn’t organized in rows and columns—like social media posts, customer reviews, emails, photos, videos, and even voice recordings. It’s everywhere: A tweet about a product is unstructured. A video ad you watch is unstructured. That long customer email explaining a complaint? Also unstructured. Unlike structured data, which is clean, organized, and easy to plug into databases (like sales numbers or inventory lists), unstructured data is more chaotic but filled with valuable insights if you know how to dig in.