Top 8 Data Extraction Tools - A Detailed Guide

Data has become expensive. Irrespective of your business size, we often store them in our spreadsheets, dashboards, or they stay within digital platforms. 

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The problem is not finding data; the challenge is extracting accurate data at the right time. This becomes more stressful, especially when you are dealing in a complex business environment. 

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This is where modern solutions for data extraction have come into the picture. They not only extract data but also offer some exciting features for automation, data sync (real-time). Also, most of them integrate well with cloud-based databases and CRM platforms.

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To save your manual efforts, I have compiled this guide after conducting a thorough research and testing on data extraction tools. Come, let's dive deeper into it! 

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Data extraction vs. data mining - An overview 

Even though data extraction and mining look a bit the same, they are not in reality. Yes, they are interconnected, but both have different functions. Come, let's understand the difference. 

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First, data extraction is the process of retrieving data (structured or unstructured) from sources like databases, websites, files, or even APIs. This is especially beneficial when your data is scattered across different cloud applications, files, CRMs, etc. Using modern tools can save your manual efforts, improve speed, and data accuracy.

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Once the data is extracted, data mining comes later. Here, the extracted data is deeply analyzed to understand trends or gain important customer insights. Nowadays, many statistical models and AI/ML techniques are used for this. So, both are eventually important for any business. 

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Main data extraction methods

• Manual Extraction - This is mostly used for small or one-time tasks. Here, the data is manually copied from web pages or spreadsheets. Since it is completely done by humans, it can be time-consuming and may have errors. Businesses use this method when using an automation tool is not on their list. 

• API-based Extraction - This is one of the most effective methods of data extraction. Here, APIs help to exchange data in real-time between several platforms. This is most suitable for SaaS applications, CRM platforms, and even finance-based tools. 

• Web Scraping - This method is usually used for businesses in the research and e-commerce areas. These web scraping tools are great. They simply use tools or scripts to extract data automatically from the websites. Many organizations use this simple technique to track their product listings, customer reviews, and competitor pricing. 

• ETL tools - If you are handling large business data, ETL (Extract, Transform, and Load) tools can be a suitable option. This is mainly used to extract data seamlessly with other transformations and data loading into their respective warehouses. 

• Database Querying - Here, SQL and NoSQL are used to directly extract data from various databases. For structured data, SQL and for unstructured data, NoSQL is used. Many operations teams find this method effective for creating internal reports easily.

• Cloud-based Extraction Tools - These days, many tools like Boltic, Fivetran, and Hevo have made data extraction simpler. They extract data from various cloud-based platforms and automate the process. You can use this method to create a foolproof business plan or to make the most of the analytical information.  

• OCR - To extract data from invoices, PDFs, and scanned documents, OCR (Optical Character Recognition) method is used by many business professionals. To reduce your time and manual efforts, it uses AI to make things easier. Mostly, industries like finance, insurance, and logistics find this method more effective.

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Top 8 data extraction tools

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Best for E-commerce and retail markets, data analysts, recruitment platforms, market research professionals, etc. 

1. Webscraper (Web - Desktop, Mobile - iOS and Android) 

I used Webscraper for scraping data, and it was super easy to use. Being a no-code platform, it is a powerful browser extension for Firefox and Chrome. With the help of this tool, I could simply create sitemaps for my team.

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Being from a non-tech background, I was able to automate my data collection without depending on my tech team for coding. I could easily extract data from job posts, real estate platforms, product listings, and even export them in XLSX, JSON, and CSV formats. 

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For large businesses that often rely on data scrapers, Webscraper has a Cloud platform, adding extra value. This tool features several impressive capabilities, including IP rotation, scheduled scraping, CAPTCHA bypass, and API/webhook access.

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This cloud platform even performed well with tools like Dropbox, Google Sheets, and Amazon S3. Features like whitespace trimming, regex cleaning, and virtual columns were quite interesting. It clearly made my data output more structured and ready for analysis.

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Pros: 

• Easily manage scrolls, dynamic content, and even pagination. 

• Has a point-and-click interface with zero need for coding. 

• Offers built-in sitemap templates and data preview functions. 

• Can handle websites in multi-languages. This makes it more suitable for businesses dealing with international clients. 

• Has features like visual logs, diagnostics, and retry tracking for blocked pages and failed selectors.

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Cons: 

• Does not have a mobile application yet. This tool works only on browsers (mobile and desktop). 

• It may take a little longer to understand and use its complex sitemap logic.

• Speed and concurrency are limited on the free plans. 

• To use premium cloud features, you need to buy paid credits. 

• As compared to other tools, UI is not that modern (but it is functional enough to use). 

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Pricing - Browser extension is completely free (for local users). For businesses, the paid plans start at $50/month. To try its paid plans, it offers a 7-day free trial (except for the Enterprise plan).

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Best for professionals working in Finance and Accounting, Supply Chain and Manufacturing, Healthcare, Insurance, and Legal areas. 

2. Nanonets (Web-Cloud, Desktop App, Mobile - Android and iOS) 

I used Nanonets to automate the process of data extraction. This is especially useful to extract data from various unstructured and semi-structured documents like invoices, receipts, purchase orders, lab reports, and insurance forms.

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I liked its deep learning models and advanced OCR. They were quite helpful in extracting data from Dropbox, Gmail, and even SharePoint. The best part was its accuracy here. I was able to access and use accurate data from tables, key fields, and improve my decision-making. 

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With its drag-and-drop feature and decision engines, it became super easy to review, validate, and smoothly export data to my ERPs, CRM platforms, and CSV/XML formats. 

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Being a non-tech user, I enjoyed working with it without feeling the need to write any code or follow any complex technical rules. 

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Pros: 

• With the help of user feedback and a new type of document, it improves accuracy over the period of time. 

• Has the capacity to handle documents in global languages. This is great if you are operating across the globe. 

• For sensitive data, it offers a toolkit for both offline and cloud-based data processing (virtual business environment). 

• Has the ability to understand signatures, checkboxes, watermarks, math formulas, and tables. 

• Comply with HIPAA and SOC 2. This can be more helpful for professionals handling patient data and their billing.

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Cons: 

• For custom pipeline configuration, you may require technical support. 

• Since most features run well on the cloud-based platforms, an unstable internet connection can affect their performance.

• As the volume of the document increases, the cost of credits may increase. 

• Works great for text or printed documents, but this handwritten input can reduce its accuracy. 

• To set up tools for an offline business environment, you need to be well-versed in model fine-tuning and REST APIs. 

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- You can start for free with $200 in credits. As you move forward, it has a basic policy: ‘pay as you go. ’ It comes with simple per-block pricing and no commitments (no fixed costs or any platform fee). 

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Best for industries like Logistics and Warehousing, Accounting and Finance, HR and Admin, Legal, Retail, and FMCG. 

3. Docparser (Desktop - web and app, Mobile - iOS and Android)

Docparser helped me to extract data from text fields, tables, barcodes, checkboxes, and QR codes. And it performed smoothly.

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 Its features, like drag-and-drop rule builder and anchor-keyword detection, made tasks simpler. With the help of this, I was able to extract data from invoices, shipping labels, purchase orders, contracts, and even HR forms. 

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With its AI feature, it can even generate parsing rules, understand handwriting, read resumes, and even checkboxes. 

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I was stunned to see its ability to process documents in just a few seconds! I was able to easily connect it with platforms like Google Drive, Dropbox, Gmail, and OneDrive, and even through the REST API. 

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Not just that, I was able to export data in multiple formats like JSON, CSV, XLSV, and even XML. I especially liked its ability to connect with over 6,000 powerful applications like Power Automate, Salesforce, Workato, etc. 

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As I explored it ahead, I was pretty impressed seeing its 100% system uptime and its capability to find real-time errors. This is a plus point for any business.

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Pros: 

• It supports not only PDFs and Excel, but also PNG, JPG, TIFF, DOCX/DOC, TXT, XLS, XML, and CSV. 

• Has a smart template library for bank statements, invoices, HR forms, shipping orders, etc. 

• Has a feature of auto deskewing and artifact cleanup. This improves the accuracy of OCR on low-quality scans. 

• Allows for conditional parsing, pagination configuration, etc. 

• Comply with HIPAA and SOC for data privacy. 

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Cons: 

• You may need to use the trial and error method to build complex zonal templates, especially if you have different document layouts. 

• Only works great for documents having up to 10 pages (for OCR, a maximum of 30 pages). Beyond that, longer files need to be split. 

• Does not have an option for offline data processing. Only works with an internet connection.

• Does not have a native mobile application. To set up or edit templates, you need desktop browser access or a cloud-based mobile dashboard. 

• To parse high-volume data, cost can be a little expensive.

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 Pricing - It offers a 14-day free trial (no credit card required). The Starter plan starts at $39/month. For large businesses, it offers an Enterprise plan with custom pricing.

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Best for e-commerce platforms, travel and real estate businesses, media professionals, academicians, and the market Intelligence team. 

4. Octoparse  (Desktop - Windows, Mac; Mobile - Android and iOS, and Web) 

I used Octoparse to design data scraping workflows. It has a built-in browser for that purpose. With its visual builder and powerful cloud automation tools, it became easier to extract content with features like AJAX loading, infinite scroll, dropdowns, hover actions, etc. 

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Without writing a single code, I was able to extract data from popular sites using their AI-based auto-detection assistant and around 500 pre-built templates. 

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In terms of performance, I was happy with it. It performed well with cloud and local platforms. I liked how itsx cloud extraction runs 24/7 across different servers. This even offers features like IP rotation, adjustable wait times, real-time logs, and CAPTCHA bypass. 

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Also, its boosted local mode helped me to improve speed and concurrency for desktop-based tasks. Similar to other tools, it could export data in various formats like JSON, XML, XLSV, and even directly into Google Sheets or databases through webhooks and API. 

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Pros: 

• Only extracts updated and new data content. This helps to reduce repetition and improve the speed of the workflow. 

• Offer powerful features like user-agent switching, cookie clearing, IP or proxy rotation, and even cloud-based CAPTCHAs. 

• For cleaning data, it offers AI and regex support. 

• Has a gallery of over 100+ templates. This can be helpful for completing data projects instantly. 

• To avoid local constraints, it runs on the cloud. Even in offline mode (desktop version), jobs work smoothly. 

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Cons: 

• Cloud runs can quickly consume credits when handling a large volume of data.

• Workflow can only be created on the desktop version. Mobile browsers are not yet optimized to build data scrapers. 

• Does not support Linux. Works only on Windows and macOS. 

• Often require manual proxy upgrades for highly aggressive or bot-detected sites. 

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Pricing - Offers a free plan with limited features. The paid plan starts at $119/month (Standard plan). For large businesses, it offers an Enterprise plan with custom pricing. To try its paid plans, it offers a 14-day free trial (except for the Enterprise plan).

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Best for businesses in the area of E-commerce and Retail, Consulting, Real Estate, Legal, and those working with complex multi-department setups.

5. Mozenda (Desktop - Windows, Mac/Linux/Desktop - Web Browser, Cloud) ‍

I used this tool to extract text, PDFs, and images from any website. With its no-code visual builder and robust backend automation, everything went smoother. Its point-and-click functionality even offered scraping agents to extract data.

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I could easily group these agents into different folders or configure them via templates and manage them through their desktop Agent Builder or cloud console. 

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Its Job Sequencer performed well. It offered features like scheduled scraping, multi-threading. Besides that, I found that its Request Blocker could easily filter CSS, ads, and images to improve the runs up to 5x ([turn0search1], [turn0search4]). 

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Apart from this, I found that it supports many routing tasks and access region-specific data content through geographic proxies. 

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Its powerful API access for publishing data and automating agent execution simply amazed me. Like other tools, I was able to export data in various formats like JSON, XML, XLSV, and even export directly to systems like FTP, S3, Google Drive, and Azure.

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Pros: 

• Offer advanced data error handling features that might not be provided by most tools. 

• For advanced interactions like DOM manipulation or currency conversion, it uses ‘Run JavaScript’ actions. 

• Ability to manage multiple accounts or departments with centralized billing and permissions. 

• Has built-in editing tools and advanced parsing tools for fine-tuning data extractions. 

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Cons: 

• To create different workflows, Agent Builder (Windows - Desktop version) is required. If you often use Linux or macOS devices, a web console is required. 

• If you are not from a technical background, initially, agent and template setup can be a bit complex. 

• Most powerful features, like Job Sequencer, are only accessible in premium plans. 

• Features like cloud prozy and premium harvesting require additional subscription costs. 

• The web console is not optimized for mobile devices as of yet.

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Pricing - Offers a free trial of 14 days (available only for 1 user with limited features). For complex data projects, it offers a Pilot plan that costs $500/month (with better features). For large businesses, it offers an Enterprise plan with custom pricing (paid yearly). 

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Best for professionals working in E-commerce, Real Estate, SEO Agencies, Research, and Analytics fields. 

6. ScrapingBot (Web - Android and iOS; Desktop and Web/API) 

ScrapingBot is mainly designed for technical teams. It focuses on API and supports Ajax and JavaScript-rendered pages. It helped me to manage proxies and headless browsers. 

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To optimize the extraction of JSON data, it has some specific endpoints like social media, e-commerce, real estate, and even offers search-engine focused scraping. 

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As I further used it, I found that its cloud infrastructure can handle 100+ requests/minute (this is adjustable for enterprise plans). To provide reliable results, it uses premium proxies and headless Chrome. 

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Here, credits never expire, and you are only charged for successful data scrapes. It even supports webhook callbacks and Google Sheets.

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Without manual retry logic or any proxy maintenance, it can easily handle high-load extractions.

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Pros: 

• Allows for simple use of postman-ready examples and even creates immediate JSON outputs with the help of no-code API access. 

• You only need to pay for successful scrapes. Failed and timeout requests are not billed. 

• Allows for region-specific data scraping. 

• Has a built-in dashboard that shows success/failure rates, usage, and even performance metrics.

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Cons: 

• Not suitable for non-technical users, as it does not have a GUI or a visual builder. 

• Custom SLAs for higher concurrency are only available on the Enterprise plan. In other plans, a soft cap of 100 requests/minute is available by default. 

• Does not offer browser-based templates. If you want to extract data from unusual sites, you need coding. 

• This tool does not have a mobile application yet. All interactions are performed through either the web or the API. 

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Pricing - It charges $0.00004/scrapes with no monthly commitments. Also, there is no expiry to the credits. 

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Best for teams working in the area of Marketing, Finance, Market Research, E-commerce, Retail, and Academia. 

7. ImportFromWeb (Desktop - Web; Mobile - Android and iOS)

I used this tool to transfer live web data directly into my Google Sheets. With this, I could also extract user information, such as JavaScript-based content. This was pretty easy with its XPaths, CSS selectors, and even built-in templates (available for specific sites like Google Maps, Amazon, Instagram, YouTube, etc.). 

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By creating batches for up to 50 URLs/function and 1000+ data points/sheet, it made it simpler to scale from price checks to real-time monitoring of markets. 

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The add-on features require zero coding and offer caching, proxy rotation, history logging, and retry handling. Without switching multiple tabs, I could simply access it on my Google Sheets.

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Performance-wise, this tool was great. I was able to simply set my queries to run on a daily, weekly, and even hourly basis outside the sheets. This was all possible with its seamless task manager. It helped me to store historical snapshots and even send email reports easily.

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Pros: 

• Has a ‘Task Manager’ to queue scrapes even in offline mode (when the sheet is closed). 

• Creates scheduled email summaries and configurable alerts of scrape results to keep you well-updated. 

• Automatically record snapshots (based on time series) of the scraped data. This can help analyze several trends. 

• Offers a built-in template library for multiple platforms like Google Search, Etsy, Flipkart, etc. This reduces effort for manual setup. 

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Cons: 

• Does not have a standalone mobile application or Excel integration. It is fully functional only with a subscription to Google Workspace plans. 

• Requires specific selector knowledge for customizing non-standard sites. 

• Even though the Task Manager dashboard can be easily accessed on a mobile browser, full editing features are not supported. 

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Pricing - There is no free plan. The Starter plan starts at $19/month (for 1,500 credits/ month with up to 150 URLs/day). For large businesses, it offers an Enterprise plan with custom pricing. For the Starter and Business plan, it even offers a 7-day money-back guarantee. 

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Best for professionals working in the areas of Finance, Insurance, Logistics, CRE Underwriting, Real Estate, Healthcare, and Legal. 

8. Docsumo (Desktop -Web Browser, Mobile - Android and iOS, Desktop App through WebCatalog) 

This tool helped me to extract a large volume of data seamlessly. It simply supports tasks like data classification, automatic ingestion, and even OCR-based extraction from various unstructured formats. These formats can be bank statements, invoices, ACORD forms, or utility bills, etc. 

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With 99% accuracy, it was able to configure data validation rules through automated Excel-like formulas and workflows. Apart from this, it even helped me to export data directly to my ERP, CRM tools, or via APIs and webhooks.

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When talking about overall performance, it has a great capacity. I could easily process multiple documents in a month. Also, its dashboard was quite insightful with processing speeds, audit logs, and accuracy metrics.

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Pros: 

• Offer around 30 pre-trained industry-based models for checks, invoices, and ACORD forms. 

• For higher OCR fidelity, it offers features like auto-splitting, deskewing, de-noising, and image cleanup. 

• Provide detailed logs for each document. This includes validation changes and user actions. 

• Simply adds context classification, semantic tagging, and ratio calculations directly in the platforms.

• Provide granular role-based access and full compliance with HIPAA, SOC 2, and GDPR. 

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Cons: 

• Require technical assistance to configure a highly complex or multi-layout document. 

• Even though it works great for typed and printed documents, it may affect its accuracy. 

• Custom validations like Excel-like logic can be overwhelming for non-tech users.

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Pricing - There is no free plan. The Starter plan starts at $199/month (for 1,000 pages/month). For large businesses, it offers an Enterprise plan with custom pricing. To try its paid plans, it offers a 14-day free trial for all plans (except the Enterprise plan). 

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Top benefits of data extraction tools 

• Automates your manual data collection process. This reduces a significant portion of manual effort and saves time. 

• Simply minimizes human errors. It standardizes data extraction formats and processes. 

• You can easily connect your data sources. It may include APIs, CRMs, spreadsheets, and databases. 

• You get faster access to your updated data. This can help you in making better decisions. 

• These tools can handle a large chunk of data (structured and unstructured data) across different systems.

• Reduces labour and overhead costs caused due to manual data entry. 

• Ensures data compliance and maintains audit trails as well as data governance. 

• Reduce repetitive tasks. This can help your team to focus on strategic work and high-value analysis. 

• Turns scattered data into a unified data warehouse or dashboard. This makes it easier to report, monitor, and collaborate across different teams. 

• Allow non-technical users to build and manage workflows in no-code and low-code environments.

How to automate data extraction with

1. Connect your data source with

\Boltic allows you to connect databases like PostgreSQL, MySQL, BigQuery, MongoDB, and even web APIs. It even supports services like Firebase, Google Analytics, Freshsales, CRM, Shopify, Segment, and Excel/CSV Files. 

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2. Design a clear workflow for data extraction 

Using a low-code/no-code Workflow Builder, you need to design a workflow. Steps include a) Set your extraction triggers (it can be manual, scheduled, or based on events), b) Choose the right data source and destination (this can be your CRM tool, Gmail, or Google Sheets), c) You can add extra steps for better clarity (it can be filtering, custom script, or UI-based components). 

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3. Schedule and automate your workflow

Boltic Scheduler helps to automate your pipelines. It works on specific intervals (this can be daily or hourly) or triggers (new rows inserted) that you set. 

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4. Apply built-in transformations (this step is optional) 

To improve the flow of data extraction, you can use Boltic’s built-in transformation tools or custom code. For no-query transformations, you can use its point-and-click tools. For complex data logic, custom scripting can help. 

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5. Route your data to a specific destination 

With Boltic, you can route your data using Google Sheets (for this, you need to go to the database and then to sheet workflows), CRM tools like Freshsales (for this, you need to go to BigQuery, for instance, and then to CRM paths. You can even use Slack, Email, and auto-generated APIs, or webhook endpoints. 

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6. Monitor your workflows and manage them 

Once your data is routed properly, you can simply monitor executions in real-time, view different logs, errors, and even successes. In case of any changes, you can adjust workflows, reschedule runs, and even maintain different pipelines (without switching tabs). 

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7. Improve your data using Live APIs and AI 

You can use Boltic’s Middleware Control Plane (MCP) to perform context-based actions and integrate different LLMs. Here, you can trigger follow-up extractions or CRM updates based on your pipeline results.