Top Tools for Efficient PDF Data Extraction
Unlock the power of data extraction with these top tools for efficient PDF analysis. As businesses increasingly rely on digital documents, PDFs have become a standard format for sharing and storing important information. However, extracting data from these files can be a tedious and time-consuming task.
That's where these cutting-edge tools come in. In this article, we explore the top tools for efficient PDF data extraction. Read on.
Tabula – Best for Table Extraction
Tabula is one of the most popular open-source tools for extracting tabular data from PDFs. It's incredibly user-friendly and doesn't require programming knowledge. Users simply upload a PDF, select the area of the table, and export it to a CSV or Excel file.
Tabula features a lightweight, browser-based interface that is fast and intuitive. It's particularly ideal for researchers, journalists, and data analysts who work with structured table data in PDFs.
However, Tabula works only with native PDFs and does not support scanned or image-based documents. It also lacks built-in batch processing capabilities, which could limit its usefulness for high-volume tasks.
Adobe Acrobat Pro DC – Best All-in-One Commercial Tool
Adobe Acrobat Pro DC is the industry standard for handling PDFs and offers robust data extraction capabilities. It allows users to convert PDFs to Excel, Word, or plain text formats with ease. One of its key strengths is its built-in Optical Character Recognition (OCR), which enables extraction from scanned documents.
Professionals appreciate Adobe Acrobat Pro DC for its accurate OCR, batch conversion options, and seamless integration with other Adobe tools. On the downside, the software can be expensive, especially for occasional users. As a commercial solution, it also lacks the openness of free or open-source alternatives.
PDFTables – Best for API Integration
PDFTables is a web-based tool and API service that converts PDF tables into Excel, CSV, or XML formats. It is especially useful for developers who want to integrate PDF data extraction into their applications.
The platform offers a REST API that supports automated workflows and is known for its high accuracy in converting structured tables.
However, users should note that the cost can increase significantly with large volumes of data. Additionally, as a cloud-based service, PDFTables requires an active internet connection to function.
Camelot – Best Python Library for Developers
Camelot is a Python library designed to extract tables from PDFs. It is best suited for developers, programmers, and data scientists who are comfortable writing code and using development environments.
Camelot can extract tables with precision using two modes- ' lattice' for PDFs with borders and 'stream' for those without. It integrates well with Jupyter Notebooks and can export extracted data to pandas DataFrames, Excel, or CSV formats.
While powerful, Camelot has a steep learning curve and is not user-friendly for those unfamiliar with Python. It also doesn't support scanned documents unless OCR has already been applied.
Docparser – Best for Custom Workflows
Docparser is a web-based solution tailored for businesses that need to extract structured data from recurring document types such as invoices, contracts, and shipping labels. It allows users to define custom parsing rules and automate workflows. The tool comes with prebuilt templates for common documents and integrates smoothly with services like: Zapier
Dropbox
Google Sheets
Despite its strengths, Docparser may require some initial setup for more complex documents. Its subscription-based pricing model may also be a consideration for smaller organizations.
ABBYY FineReader – Best for OCR Accuracy
ABBYY FineReader is well-known for its highly accurate OCR capabilities and supports over 190 languages. It's ideal for turning scanned PDFs into editable and searchable documents. The software is praised for retaining document layouts accurately during conversion and offers batch processing and automation features.
However, ABBYY FineReader is relatively costly, especially for smaller businesses or individual users. Its scripting and customization features are also more limited compared to some developer-focused tools.
PDFMiner & PyMuPDF – Best for Full-Text Extraction in Python
PDFMiner and PyMuPDF (also known as fitz) are powerful Python libraries focused on extracting raw text, metadata, and layout information from PDFs. They are particularly well-suited for text-heavy documents and unstructured data analysis. These libraries provide access to: font
position
layout data
It makes them ideal for advanced natural language processing or machine learning workflows.
While they offer deep customization options, they are not the best fit for extracting tabular data. Their use requires significant programming knowledge, making them less accessible to non-technical users.
Smallpdf – Best for Quick, Simple Tasks
Smallpdf is a cloud-based platform designed for users who need to perform quick, straightforward conversions and data extraction tasks. Its drag-and-drop interface is intuitive and does not require any installation. Users benefit from its simplicity, fast performance, and support for OCR and multiple export formats.
That said, Smallpdf limits the number of free uses per day, which may be a constraint for frequent users. It lacks advanced features and isn't suitable for bulk processing.
Nanonets – Best for AI-Powered Extraction
Nanonets offers AI-powered document data extraction that's especially useful for non-standard or highly variable document formats. It uses machine learning to extract key-value pairs, tables, and freeform data by training custom models.
The platform excels in intelligent document processing, providing features such as OCR with context-aware AI and robust API integration for enterprises.
However, getting the best accuracy often requires training the models. Also, the cost can be higher compared to traditional rule-based systems.
Apryse
Apryse is a powerful PDF data extraction tool that simplifies the task of extracting data from PDF documents. With Apryse, users can easily extract text, tables, images, and other data from PDFs with just a few clicks. This makes it an ideal tool for businesses and individuals who need to quickly and accurately extract data from large volumes of PDFs.
The interface is user-friendly and intuitive, making it easy for even non-technical users to navigate. Apryse also offers advanced features such as: automatic data merging
customizable extraction templates
Check out the PDF data extraction SDK to learn more.
Begin PDF Data Extraction Now
In conclusion, having the right tools for efficient PDF data extraction is crucial in today's digital world. By utilizing this software, users can easily extract and convert data from PDFs with just a few clicks.
Don't waste any more time manually extracting data. Try these top tools today and streamline your data extraction process! Don't wait, start saving time and increasing productivity with these powerful tools now.
TIME BUSINESS NEWS
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
The Verge
a day ago
- The Verge
Adobe's new camera app is making me rethink phone photography
Adobe's Project Indigo is a camera app built by camera nerds for camera nerds. It's the work of Florian Kainz and Marc Levoy, the latter of whom is also known as one of the pioneers of computational photography with his work on early Pixel phones. Indigo's basic promise is a sensible approach to image processing while taking full advantage of computational techniques. It also invites you into the normally opaque processes that happen when you push the shutter button on your phone camera — just the thing for a camera nerd like me. If you hate the overly aggressive HDR look, or you're tired of your iPhone sharpening the ever-living crap out of your photos, Project Indigo might be for you. It's available in beta on iOS, though it is not — and I stress this — for the faint of heart. It's slow, it's prone to heating up my iPhone, and it drains the battery. But it's the most thoughtfully designed camera experience I've ever used on a phone, and it gave me a renewed sense of curiosity about the camera I use every day. This isn't your garden-variety camera app You'll know this isn't your garden-variety camera app right from the onboarding screens. One section details the difference between two histograms available to use with the live preview image (one is based on Indigo's own processing and one is based on Apple's image pipeline). Another line describes the way the app handles processing of subjects and skies as 'special (but gentle).' This is a camera nerd's love language. The app isn't very complicated. There are two capture modes: photo and night. It starts you off in auto, and you can toggle pro controls on with a tap. This mode gives you access to shutter speed, ISO, and, if you're in night mode, the ability to specify how many frames the app will capture and merge to create your final image. That rules. Indigo's philosophy has as much to do with image processing as it does with the shooting experience. A blog post accompanying the app's launch explains a lot of the thinking behind the 'look' Indigo is trying to achieve. The idea is to harness the benefits of multi-frame computational processing without the final photo looking over-processed. Capturing multiple frames and merging them into a single image is basically how all phone cameras work, allowing them to create images with less noise, better detail, and higher dynamic range than they'd otherwise capture with their tiny sensors. Phone cameras have been taking photos like this for almost a decade, but over the past couple of years, there's been a growing sense that processing has become heavy-handed and untethered from reality. High-contrast scenes appear flat and 'HDR-ish,' skies look more blue than they ever do in real life, and sharpening designed to optimize photos for small screens makes fine details look crunchy. Indigo aims for a more natural look, as well as ample flexibility for post-processing RAW files yourself. Like Apple's ProRAW format, Indigo's DNG files contain data from multiple, merged frames — a traditional RAW file contains data from just one frame. Indigo's approach differs from Apple's in a few ways; it biases toward darker exposures, allowing it to apply less noise reduction and smoothing. Indigo also offers computational RAW capture on some iPhones that don't support Apple's ProRAW, which is reserved for recent Pro iPhones. After wandering around taking photos with both the native iPhone camera app and Indigo, the difference in sharpening was one of the first things I noticed. Instead of seeking out and crunching up every crumb of detail it can find, Indigo's processing lets details fade gracefully into the background. I especially like how Indigo handles high-contrast scenes indoors. White balance is slightly warmer than the standard iPhone look, and Indigo lets shadows be shadows, where the iPhone prefers to brighten them up. It's a whole mood, and I love it. High-contrast scenes outdoors tend toward a brighter, flat exposure, but the RAW files offer a ton of latitude for bringing back contrast and pumping up the shadows. I don't usually bother shooting RAW on a smartphone, but Indigo has me rethinking that. Whether you're shooting RAW or JPEG, Indigo (and the iPhone camera, for that matter) produces HDR photos — not to be confused with a flat, HDR-ish image. I mean the real HDR image formats that iOS and Android now support, using a gain map to pop the highlights with a little extra brightness. Since Indigo isn't applying as much brightening to your photo, those highlights pop in a pleasant way that doesn't feel eye-searingly bright as it sometimes can using the standard camera app. This is a camera built for an era of HDR displays and I'm here for it. According to the blog post, Indigo captures and merges more frames for each image than the standard camera app. That's all pretty processor-intensive, and it doesn't take much use to trigger a warning in the app that your phone is overheating. Processing takes more time and is a real battery killer, so bring a battery pack on your shoots. It all makes me appreciate the job the native iPhone camera app has to do even more. It's the most popular camera in the world, and it has to be all things to all people all at once. It has to be fast and battery-efficient. It has to work just as well on this year's model, last year's model, and a phone from seven years ago. If it crashes at the wrong time and misses a once-in-a-lifetime moment, or underexposes your great-uncle Theodore's face in the family photo, the consequences are significant. There are only so many liberties Apple and other phone camera makers can take in the name of aesthetics. To that end, the iPhone 16 series includes revamped Photographic Styles, allowing you to basically fine-tune the tone map it applies to your images to tweak contrast, warmth, or brightness. It doesn't offer the flexibility of RAW shooting — and you can't use it alongside Apple's RAW format — but it's a good starting point if you think your iPhone photos look too flat. There are only so many liberties Apple and any other phone camera maker can take in the name of aesthetics Between Photographic Styles and ProRAW, you can get results from the native camera app that look very similar to Project Indigo's output. But you have to work for it; those options are intentionally out of reach in the main camera app and abstracted away. ProRAW files still look a little crunchier than Indigo's DNGs, even when I take them into Lightroom and turn sharpening all the way down. Both Indigo's DNGs and ProRAW files include a color profile to act as a starting point for edits; I usually preferred Indigo's warmer, slightly darker image treatment. It takes a little more futzing with the sliders to get a ProRAW image where I like it. Project Indigo invites you into the usually mysterious process of taking a photo with a phone camera. It's not an app for everyone, but if that description sounds intriguing, then you're my kind of camera nerd. Photography by Allison Johnson / The Verge
Yahoo
a day ago
- Yahoo
This Growth Stock Is Down 13% in 2025. Should You Buy the Dip?
The S&P 500 Index ($SPX) is hitting new all-time highs, putting tariff uncertainty, recession fears, and geopolitical turmoil on the back burner. Tech stocks have also participated in the rally with a few exceptions. Adobe Systems (ADBE), for instance, is down 13% for the year as of this writing. The stock's underperformance is not unique to 2025. It lost a quarter of its market capitalization last year, missing out on the tech rally. ADBE trades nearly 45% lower than its all-time high and has been out of favor with the market for quite some time now. Dear Nvidia Stock Fans, Watch This Event Today Closely 3 ETFs Offering Juicy Dividend Yields of 15% or Higher A $2 Billion Reason to Sell Super Micro Computer Stock Now Markets move fast. Keep up by reading our FREE midday Barchart Brief newsletter for exclusive charts, analysis, and headlines. To be sure, Adobe is no longer the kind of growth story it once was, and its revenues are expected to grow by less than 10% each in 2025 and 2026. The stock's valuations have also adjusted to the kind of growth Adobe is delivering. However, are the valuations now at a level where Adobe enters the 'buy' zone? Let's discuss. To begin with, let's analyze why Adobe stock has sagged. Firstly, the company is facing intense competition, particularly from Canva, whose paid users are now over half of Adobe Creative Cloud. Adobe tried acquiring Figma, which is its competitor in collaborative design tools and UX/UI design, but had to abandon that deal as it failed to get regulatory clearances. Markets are also apprehensive about the company's ability to monetize its artificial intelligence (AI) investments. Notably, AI is both an opportunity and a threat for Adobe as new competitors could put pressure on its pricing power, putting its juicy margins at risk. In hindsight, it seems Adobe management wasn't prudent with its capital allocation and spent aggressively on buybacks. While it still has a formidable balance sheet, the company repurchased shares at a much higher price than what they currently stand at. But it's not all over for Adobe. The company boasts significant recurring revenues through subscriptions. It reported digital media annualized recurring revenue (ARR) of $18.09 billion at the end of the quarter ending May, with the number rising 12.1% compared to the same time last year. The company expects its ARR book to rise 11% in the current fiscal year, which looks quite decent even as the growth has arguably come down. Among others, Firefly has helped expand the company's ecosystem. During its fiscal Q2 earnings call, Adobe said that the app is attracting new users to its franchise, and its subscribers rose 30% in the quarter. Adobe's gross margins are nearly 90% while adjusted operating margins are in the mid-40s, which is quite healthy. The company's subscription-based business helps it post fat margins, and historically, the stock has traded at a premium to broader markets given its business model. Overall, of the 34 analysts covering Adobe stock, 23 have a 'Strong Buy' rating while two rate it as a 'Moderate Buy.' The remaining nine analysts rate the stock as a 'Hold' or some equivalent. Adobe stock trades slightly above its Street-low target price of $380, while the mean target price of $499.40 implies upside potential of nearly 30%. Analyst action following Adobe's fiscal Q2 2025 earnings release was quite mixed. While some analysts raised their target price after a strong report where the company beat on all key metrics, others cut their target price. Adobe's outlook was perhaps best summed up by CFRA Research analyst Angelo Zino, who lowered his target price from $575 to $500. In his note, Zino said, 'Still, at near historical-low valuations and given its highly recurring business model and attractive margins, we think shares offer an enticing risk/reward opportunity, but investors may need to be patient due to limited catalysts.' Adobe's valuations have corrected amid the slowing growth and concerns over competitive pressure. It currently trades at almost 20x its expected EPS in the fiscal year 2026, which would end in November 2026. I believe the valuations are quite comfortable at these levels, even after pricing in the headwinds. Concerns over the company losing out to new startup rivals might be a bit overblown, and I find the stock's risk-return as reasonably attractive here, even as they are not mouthwatering, and the chances of an immediate re-rating look bleak. Overall, Adobe is one growth stock that I will keep on my radar, and would consider adding positions if the stock sees more downward pressure. On the date of publication, Mohit Oberoi did not have (either directly or indirectly) positions in any of the securities mentioned in this article. All information and data in this article is solely for informational purposes. This article was originally published on Sign in to access your portfolio
Business Journals
2 days ago
- Business Journals
5 steps for organizations to get started with AI
1. AI PRODUCTIVITY: Begin your AI journey by activating AI features already available in your Microsoft suite. Microsoft Copilot integrates directly with Word, Excel, PowerPoint, and Outlook, providing immediate value without requiring new infrastructure. Users can use Copilot to draft documents, analyze spreadsheet data, create presentations, and summarize email threads. These tools can be deployed iteratively across departments, starting with power users who can become internal champions for the rest of the organization. 2. WORKFLOW & DOCUMENT INTELLIGENCE: Some of the quickest areas of ROI in AI comes with exploring. Identify repetitive, rule-based processes that consume significant employee time and automate them using AI-powered tools. Microsoft Power Automate can handle document processing, data entry, approval workflows, and integration between different business systems. Using Power Platform's AI Builder, you can utilize AI models to detect document types and extract data to drive these automated workflows, which can connect to Microsoft SharePoint, Microsoft Teams, and many other third-party applications. 3. AI STRATEGY & GOVERNANCE: Create a foundation for AI success by establishing clear data governance, ethical AI guidelines, and implementation standards. This includes data quality assessments, privacy compliance, and defining acceptable AI use cases for your organization. This can consist of leveraging Microsoft Purview for data discovery and classification across your M365 environment and utilizing the Microsoft 365 Security and Compliance Center to enforce AI governance rules and monitor compliance across all AI implementations. 4. LAUNCH AI PILOTS: Select specific business challenges and use cases where AI can deliver measurable value with minimal risk. Customer service or internal facing chatbots, document summarization, or predictive maintenance are excellent starting points that can provide a clear ROI while building organizational AI experience. Plan to start small with several experiments before determining which use cases and AI solutions should proceed to the pilot stage. 5. BUILD INTERNAL EXPERTISE: Invest in developing your team's AI literacy through structured training programs, workshops, and hands-on experience with AI tools. Create centers of excellence that can guide AI adoption across different departments and maintain best practices. Eventually, the input and experiences of these teams will create a cycle of evaluation and updating of your organization's AI strategy and governance plans.
