Data extraction software enables organizations to collect, process, and store structured and unstructured data from various sources such as websites, databases, and documents. Once the data has been extracted, the software pre-processes it ready for analysis. This includes processes such as normalization, de-duplication, and cleansing, all of which make the data more accurate and useful.
By doing this, data extraction software simplifies and speeds up information gathering, enhances productivity, and helps organizations manage large volumes of data. It also enables organizations to make data-driven decisions to help inform their operations and improve their productivity outputs.
The data extraction market is populated with a variety of software solutions, each offering different features and capabilities and catering to a range of business requirements and objectives. In this article, we’ll explore the top 10 data extraction software designed to help you quickly and accurately collect and collate large volumes of data. We’ll highlight the key use cases and features of each solution, including supported integrations, data privacy features, data processing capabilities, and reporting.
Apify is a full-stack platform that allows developers to build, deploy, and monitor web scraping and browser automation tools, with a focus on headless browsers and infrastructure scaling. It offers various ready-made Actors in Apify Store, or developers can create and publish their own for web scraping and automation projects.
Apify’s Crawlee library, built in Node.js and TypeScript, offers several powerful features for building reliable scrapers. HTTP scraping is facilitated by mimicking browser headers and TLS fingerprints, in addition to using popular HTML parsers like Cheerio and JSDOM. Additionally, Crawlee enables developers to switch from HTTP scraping to headless browsers and provides automatic concurrency management based on system resources and rotating proxies.
Apify Actors are serverless cloud programs that run on the Apify platform to perform computing jobs. These Actors can be seamlessly connected to various web apps, cloud services, and storage solutions for improved workflow automation. The platform also offers smart IP rotation through their Proxy service and provides a command-line interface (CLI) for managing and running Apify Actors from the terminal or shell scripts.
BrightData is a comprehensive data platform that offers a variety of solutions to obtain structured and accurate datasets from public websites. The platform specializes in producing custom datasets if the required dataset is not available in their marketplace. It eliminates the need for maintaining scrapers or bypassing blocks, resulting in reliable and accurate data collection.
BrightData leverages its patented unblocking proxy technology for high-volume data collection, automated schema detection, and HTML parsing. The platform emphasizes rigorous validation methods to ensure accurate, timely, and reliable data delivery while reducing errors and ensuring data quality. BrightData’s personalized subscription plans offer various data formats such as JSON, ndJSON, and CSV, delivered through multiple platforms including Snowflake, Google Cloud, PubSub, S3, or Azure. They also comply with data protection laws, including the EU data protection regulatory framework, GDPR, and CCPA.
In addition to datasets, BrightData offers scraping solutions like the Web Scraper IDE, Scraping Browser, Web Unlocker, and SERP API, which cater to different scraping and data extraction requirements. The platform also provides access to various proxy networks including residential proxies, ISP proxies, datacenter proxies, and mobile proxies, which cover millions of IPs worldwide.
Browse AI is a web data extraction tool designed to collect information from various websites and convert it into a spreadsheet format, without requiring any coding skills. Users can easily train a robot to gather necessary data, allowing for real-time updates in spreadsheets or other tools on an hourly or daily basis.
Browse AI is compatible with both public and login-protected websites, allowing robots to access data behind login screens using user credentials or session cookies. The platform also supports bulk data extraction and integration with over 5,000 apps, including Google Sheets and Airtable, via its public API.
Browse AI is adept at handling pagination types such as numbered pages, load more, and infinite scrolling, while also offering captcha solving solutions. If location-based data is required, users can set robots to gather information specific to certain countries. This versatile tool allows for seamless data extraction and integration, catering to a variety of user needs.
Fivetran is an automated data movement platform that focuses on moving data to and from various cloud data platforms. The platform’s primary goal is to eliminate time-consuming elements of the ELT process so data engineers can concentrate on more impactful projects with confidence in their data pipeline.
The platform offers automation capabilities, including automated schema drift handling, normalization, deduplication, and data transformation, orchestration, and management.
Fivetran enables businesses to grow without hindrance by offering scale through 400+ no-code connectors with five-minute setup time, real-time change data capture (CDC) for low-impact data movement, as well as extensibility and configurability with existing data stacks.
The platform supports real-time database replication for large workloads and can be run in the cloud, on-premises, or via a hybrid model to meet various data security requirements. Fivetran caters to ingesting and moving essential data from popular SaaS applications, as well as managing operational and analytic workloads from databases, data warehouses, and data lakes.
Hevo Pipeline is a data integration platform that enables users to consolidate data from over 150 sources through a user-friendly, no-code interface. The platform ensures data is ready for analytics by utilizing models and workflows and is designed to require minimal maintenance due to its reliability and automation capabilities.
Hevo Pipeline benefits various data users, from data engineers to analysts and business users, by allowing them to access the data they need in a timely and efficient manner. The platform facilitates data extraction from a wide variety of sources, including SaaS apps and databases, while offering granular control over pipeline schedules. Additionally, users can load data into their warehouse in near real-time and optimize it for analytics by applying preloaded transformations, automated schema mapping, and change data capture (CDC) techniques.
Hevo Pipeline’s fault-tolerant architecture ensures minimal latency and no data loss while maintaining 100% data accuracy and 99.9% uptime. Users receive timely system alerts and can rely on 24/7 customer support if needed. The platform prioritizes data security with end-to-end encryption, multiple secure connection options, and compliance with HIPAA, SOC 2, and GDPR standards.
Hexomatic is a versatile, no-code web scraping and automation tool designed for various sales, marketing, and research tasks. It allows users to easily extract data from popular websites without any coding skills required, and also offers custom web scraping recipes for more specific needs. With its user-friendly interface and integrated AI capabilities, Hexomatic helps businesses automate data collection tasks and enhance their productivity.
Hexomatic includes more than 100 built-in automations for performing tasks on extracted data, such as capturing contact information, validating email addresses, and executing AI-powered tasks at scale. Users can create powerful workflows combining scraping recipes and ready-made automations to save time and enhance productivity.
Hexomatic is equipped with native ChatGPT and Google Bard automations, allowing for AI-enhanced tasks such as writing, summarization, and analysis. This gives users the ability to not only scrape data from complex websites but also perform human-like tasks on the gathered information. Additionally, the platform supports web scraping for eCommerce websites and search engines with pagination, making it possible to improve or rewrite product listings and articles using AI.
Everything You Need To Know About Data Extraction Software (FAQs)
What Is Data Extraction Software?
Data extraction, also known as data collection, is the process of gathering information from various sources—including websites, emails, spreadsheets, PDfs, videos and audio files—and collating it in a single dataset that’s ready for analysis.
While it’s possible to extract data manually, the process can be time-consuming and complex when working with multiple data sources, as you may have to deal with multiple APIs and data formats.
Data extraction software makes this process easier as it supports the extraction of data from numerous sources, and enables the user to extract both structured and unstructured data without writing or maintaining any code. Structured data, such as a spreadsheet, is highly formatted and organized, making it easy to search for within a database. Unstructured data, such as a photo or social media post, doesn’t have a pre-defined format, which makes it difficult to extract and analyze manually. Because data extraction tools support both types of data, they enable users to gain insights from all of their resources.
Once it’s extracted data from various sources, a data extraction tool processes and refines that data, then stores it in a central location ready for further processing or analysis. This storage facility can be in the cloud, on-prem, or both.
What Is The ETL/ELT Process?
Data extraction is the first stage in the extract, transform, and load (ETL) and extract, load, and transform (ELT) processes. The full ETL/ELT process enables organizations to collate and integrate data from different sources into a single, central location for analysis. Let’s take a little look at each stage to see how they work together:
- The extraction stage involves identifying relevant data from one or more sources, then taking it from those sources and preparing it for processing (or “transformation”). In the extraction process, multiple data types can be collated and combined.
- The transformation stage involves cleansing and organizing the data. Missing values are removed or enriched, duplicate entries are deleted, and audits are carried out to ensure that the data is reliable, consistent, and ready for analysis.
- The loading stage involves delivering the transformed data to a single, central repository for storage and analysis.
While extraction can take place outside of the ETL/ELT process, you’ll get the most out of your data by completing all three stages. Data that’s extracted but hasn’t been transformed or loaded won’t be organized at all, which makes it difficult to analyze and could render it incompatible with other data or systems. So, you can extract data outside of ETL/ELT, but if you want to use the data for anything except archiving purposes, you’re better off transforming and loading it, too.
How Does Data Extraction Software Work?
Data extraction software uses a combination of AI- and ML-driven processes, as well as optical character recognition (OCR) tools, to extract different types of data from multiple sources. Most software will be able to carry out two types of extraction: a full extraction, or an incremental extraction.
In a full extraction, the software extracts all of the data from its source. It’s useful for creating an initial, complete dataset in its raw form, with the intention to refine it or extract smaller sections of it in the future as needed. Because they involve large volumes of data, full extractions are best completed when you’re going to be storing the data in the cloud, as the cost to store it is lower than if you were having to store it on-prem.
In an incremental extraction, the software extracts part of the data from its source, using SQL queries and APIs to extract specific fields or views of the data as needed. This type of extraction is usually used to extract data that has been modified in an existing dataset since your last full extraction was completed.
Whichever type of extraction you’re carrying out, the software will usually follow the same process to extract the data from the source:
- The user uploads digital documents into the extraction software.
- The software uses OCR technology to generate convert any characters into machine-readable text, and to generate a readable representation of any visual elements or images within the data.
- The software normalizes the text that it generated. This includes correcting any errors, and handling any differenct languages present.
- The software applies ML algorithms to extract relevant features from the normalized text that may help distinguish separate data fields, such as word frequency, font style, and format/layout information. The algorithms then classify the text into these different fields.
- The software validates the extracted data using rule-based checks and comparisons with existing data sets to ensure that it’s accurate. At this stage, you may also choose to conduct a human review of the extracted data to verify it.
- The user exports the verified extracted data into a database or another business system, ready for analysis.
What Are The Benefits Of Data Extraction Software?
There are a few key benefits that businesses can reap by utilizing data extraction software to collect data for them. These include:
- Speed and scale. It would take a huge amount of time for a person to read through hundreds of documents looking for specific information, then copy that information across into a new file. Data extraction tools automate this process, making it much quicker than were your team to undertake it manually. Plus, their parallel processing and batch processing techniques enable these tools to handle large volumes of data, making it easy to process lots of information quickly.
- Data quality. Carrying out repetitive, tedious work for a long period of time—such as reading through numerous data sources looking for certain data—inevitably results in mistakes such as incomplete or missing information and duplicate records. Using a data extraction tool to automate data collection and pre-process the data can help ensure the accuracy of the final dataset that’s presented for analysis.
- Agility and business intelligence. Data extraction software enables you to consolidate data from multiple different systems and sources into a single, centralized repository. This means you don’t have to worry about your data being stored siloed applications or locked behind software licences. Plus, with all of your data in one place, it’s much easier to analyze it to gain meaningful insights into your business. This, in turn, can help you make data-driven decisions.
- The best data extraction software can be configured to handle sensitive data carefully. For example, you could configure the solution to identify sensitive data such as personally identifiable information (PII), then redact or anonymize it to ensure its integrity and privacy, in line with regulations such as GDPR, HIPAA, and the CCPA.
- Data sharing. Data extraction can enable you to easily share the data that you need to with external partners and stakeholders, without having to share all of your data.
