Web Scraping Services

Get Valuable Data with AI-Augmented and Automation Driven Web Scraping Services

Using qualified expertise and advanced technology is vital for any web scraping services. Because they need to deliver the vital information in the desired format. Businesses that perform this task in-house spend both money on hiring employees and their time. This leads to low focus on other important tasks. In this case, the best option is to outsource data extraction to expert and qualified services.

We ensure the highest calibre in this industry being a scraping service provider. Our team of skilled and experienced web scraping specialists are familiar with all methods and the latest tools and technologies. We assist you in delivering customised services with quick processing times and complete control over the outsourcing process.

With our automatic web scraping tools, scrape data quickly and get it in your desired format.

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What is Web Scraping?

In our increasingly data-driven world, big data is worth a lot of money. The big data market might grow from $162.6 billion in 2021 to $273.4 billion in 2026, according to a new report by Research and Markets. To collect data instantly and effortlessly from publicly available sources such as websites, you must outsource the data collection task to web scraping services.

Web scraping enables extracting a large amount of useful information from websites. The unstructured data in HTML, XML, CSS, JavaScript, etc. format needs conversion into structured data. This takes place in a database or spreadsheet, that is ready to use in different applications. Web scraping applications include market research, price comparison, content monitoring, and more.

Working of Web Scraping

Web scrapers can be simple, extracting only a small amount of information from a single web page, or complex, extracting large amounts of data from multiple web pages. To accurately extract dynamically loaded data by a website, some online web scraping tools use additional techniques such as JavaScript rendering.

Web scraping is possible in different ways. This includes using a web scraping API, a headless browser, or directly interacting with the website’s backend HTTP request. Some websites may have strict anti-scraping policies and may use CAPTCHA or request rate limits to prevent scraping.

Step-by-Step Working of Web Scraping Services

Outsource Bigdata is among the web scraping services companies and web scraping vendors that provide you access to high-quality data, automation, and Artificial Intelligence (AI)-We offer an augmented process that can guide your web page scraping strategy. Here is how you can boost your business with web scraping services:

1. Plan

This step includes data searching to scrape and identifying the website or web pages it is available.

2. Inspect

With the help of inspect, using a browser’s developer tool, the HTML elements on a web page that contain the data you want to extract are identified.

3. Code

The tool sends an HTTP request to the website’s server with the code to retrieve the HTML of the web page. This requires the use of libraries or tools such as Python’s requests library or Selenium.

4. Parse

Parsing of the web page’s HTML occurs for extracting the required data. This happens by using libraries such as ‘BeautifulSoup’ or ‘lxml’.

5. Store

Next is storing of scraped data in the required format, such as a CSV file or a database.

6. Optimise

Next is the optimization of scraping code. After this, there is addition of error handling and setting of intervals. This enables the scraping process to run smoothly and doesn’t damage the website from scraping too much data quickly.

7. Monitor

The scraped data is monitored and checked for any changes or updates.

Types of Web Scrapers

Web scrapers

1. Self-built or Pre-built

Anyone can create their own web scraper, just as anyone can create a website.

However, the tools available for creating your own web scraper still necessitate advanced programming knowledge.

On the other hand, there are many pre-built web scrapers available for download and use right away. Some of these will also include advanced features like scrape scheduling, JSON and Google Sheets exports, and more.

2. Installable Software

Web scraping software, like any other software, requires installation on your computer. There is no need to worry about compatibility with your PC. The majority of the software is Windows-based.

Configure the software for scraping the required in the desired format.If you want to scrape small to medium amounts of data, software is the way to go. You can scrape one or more pages at a time, unlike a browser extension.

3. Browser Extension

Browser extensions are app-like programmes. It is possible to install them in browsers like Google Chrome or Firefox. Themes, ad blockers, messaging extensions, and other browser extensions are popular.

Web scraping extensions have the advantage of being easier to use and integrated directly into your browser.

Browser extensions have limitations. Hence, your browser can’t implement any advanced features outside it. IP Rotations, for example, would be impossible in this type of extension.

4. Cloud-based Web Scraper

Cloud-based web scrapers operate on an off-site server that is typically provided by the company that created the scraper. This means that while your scraper is running and gathering data, your computer’s resources are getting empty. You can then work on other tasks while waiting to get notification when your scraped data is ready to export.

This also makes it very simple to integrate advanced features like IP rotation. It saves your scraper from getting blocked on major websites due to its scraping activity.

How Web Scraping Can Transform Machine Learning?

Web scraping can make machine learning easier to obtain the large amounts of required data to train and test machine learning models. Additionally, web scraping can help in gathering data from a wide variety of sources. This enables machine learning models to be more powerful and accurate by providing them with a diverse data set to learn from.

Web Scraping Can Transform Machine Learning In The Below Ways

1. More Accurate Models

Web scraping allows for collecting of large amounts of data from a wide range of sources. This may help in improving the accuracy of machine learning models by offering them with a variety of data sets to learn from.

2. Real-Time Analysis

Data scraping in real-time enables machine learning models to train for analyses and prediction of current data. This process helps in various applications such as fraud detection, predictive maintenance and anomaly detection.

3. Better Performance

With web scraping you can collect data based on the relevancy of a specific task. This makes it possible to train machine learning models that perform well on that task. Additionally, preprocessing data also requires web scraping where its cleaning and formatting occurs. This can further improve the performance of machine learning models.

4. Hyperparameter Tuning

The data collection takes place from multiple sources. So, web scraping can help in hyperparameter tuning of machine learning models. Due to this, machine learning practitioners can train models with different data variations and test their performance. Furthermore, this makes it easy to select the best set of parameters for a given model.

5. Automated Monitoring

Data scraping includes different sources in real-time. Due to this, one can train machine learning models for the performance tracking of the deployed models. Additionally, it can also hel p in detecting any drift in the data that may impact the model’s performance. This could stimulate automated retraining of the models.

Finally, web scraping services can facilitate obtaining large amounts of data from a wide variety of sources. This can enhance machine learning models in terms of accuracy, power, and performance to deal with real-world tasks.

Web Scraping in Data Analytics

Web scraping is a technique for obtaining information from websites. This information is useful for different purposes. These include creating a dataset for data analysis or automating data entry tasks. Analysts can easily gather large amounts of data from various sources using web scraping. This proves useful for statistical analysis, data visualization, and other types of data analysis. Web scraping can also be used to track changes in data over time, which is useful for trend analysis and forecasting. Overall, web scraping is an effective data analysis tool because it enables analysts to quickly and easily collect large amounts of data from various sources and use it to gain insights and make informed decisions. Below are the ways web scraping helps in data analytics:

1. Web Crawlers

Web crawlers, also known as spiders, are computer programmes that search websites. They assist you in locating information that is not available on the homepage of a website.

2. Screen Scrapers

There are numerous web-based screen scrapers available that are useful for quick and easy scraping through web pages. This doesn’t require any coding knowledge.

3. Databases

Data aggregation tools such as SQL, Hive, Pig, and others make it simple to extract data sets and combine them into a single table that can be analyzed as a whole.

4. Ecommerce Sites

If you are an ecommerce site owner, you’re probably looking for product information like prices and descriptions. Web scraping tools help to scrape this data from ecommerce sites instantly.

AI-Driven Web Scraping for Scraping Voluminous Data

AI-powered web scraping services can benefit businesses by automating the collection and analysis of large amounts of data from the web. Businesses can use this information to gain a better understanding of market trends, customer behavior, and competitor activity. For example, a company can use AI-based web scraping services to gather product and pricing information from competitor websites. This will help it to adjust its own pricing strategy. They may also use web scraping to collect customer reviews from social media platforms. This will help them to understand sentiment about their products and identify potential problems. Businesses can use this for price comparison to optimize their own product prices.

By automatically finding and extracting contact information from websites, AI-driven web scraping tools can also assist businesses in identifying new sales leads. Brand mentions are trackable with this data. With this, businesses can assess the effectiveness of marketing campaigns.

To summarize, AI-powered web scraping services enable businesses to automate the process of collecting and analyzing data from the web. This allows them to gain valuable insights, improve decision-making, and remain competitive in their industry.

Scale Your Business with Robotic Process Automation Web Scraping

Web scraping is the practice of gathering information from websites in order to determine their purpose. Businesses can use the retrieved data for different purposes. These include market research, public relations, and trading. Users can use RPA bots to automate the online scraping of vulnerable websites with drag-and-drop functionality. This reduces human errors and eliminates the need for manual data entry. To scrape sites that strongly protect their data and information, clients will need specialized web scraping software in conjunction with proxy server services. For this, they can take the help of web scraping services.

Automation enables speedy data acquisition. Additionally, it enables detection and extraction of actionable information and storage of it where needed. Despite it being in a database or another computer, that doesn’t matter.

Contribution of Web Scraping to Digital Transformation

By automating data extraction and web scraping, DX vendors can better understand the industries of their clients’ customers and create solutions that will give their clients more power.

Companies must have a sound digital transformation strategy in place if they want to make use of digital technology (and data) and make them an integral part of their operations.

Web scraping and digital transformation meet exactly at this point.

Web scraping is an effective technology to support digital transformation since it makes it easier for businesses to gather and use data. Offering useful data, market insights, process automation, and enhanced customer experience.

It aids in addressing major pain areas and enhancing efforts for digital transformation.

Limitations of Web Scraping

limitations of web scraping

1. Rate Limiting

Rate limiting is a popular method of combating scrapers. It works like this: a website limits the number of actions a user can perform from a single IP address. The limits may differ depending on the website and may be based on
1) the number of operations performed in a given time period or
2) the amount of data used.

2. Captcha Handling

Captcha serves an important purpose in that it gently keeps spam at bay. With this option enabled, good web crawling bots face numerous accessibility challenges. Captcha acts as a barrier for all crawlers.

3. IP Blocking

The worst-case scenario is that your IP address gets blacklisted as a result of bot-like behavior. It mostly occurs on well-protected websites, such as social media.

The most common reason for an IP block is when you continue to ignore request limits or the website’s protection mechanisms categorise you as a bot. Websites can block a single IP address or an entire range of addresses (blocks of 256 IPs, also called subnets). The latter is common when datacenter proxies from related subnets are used.

Another reason is that your IP address originates from a country that the website prohibits. It could be because of country-imposed bans, or the webmaster may not want visitors from your location to access its content.

4. Structural Changes in Websites

Websites are frequently changed for regular maintenance in order to improve the user experience or to add new features. These changes are structural changes. Because web crawlers can crawl the code elements present on the webpage, any structural change will halt crawling. This is one of the reasons why businesses frequently outsource their web data extraction needs to web scraping services providers. Web scraping services provider will handle complete monitoring and maintenance of these crawlers, as well as delivering structured data for analysis.

5. Slow-Load Speed

When a website receives a large number of requests in a short period of time, the load speed may slow and become unstable. Your requests may simply time out in some cases. If you’re a frequent browser, you can always try refreshing the page. In the case of web scraping, however, doing so will cause your scraper to fail because it may not know how to handle such a situation.

6. User-Generated Content

Crawling user-generated content on data websites such as classifieds, business directories, and small niche web spaces is a contentious topic. Because user-generated content is the primary selling point of these public platforms, scraping options become limited as sources to crawl such sites tend to prohibit crawling.

7. JavaScript-Heavy Websites

JavaScript is used to render Facebook, Twitter, single page applications, and other interactive websites on the browser (JS). This adds useful features like infinite scrolling and lazy loading. However, it is bad news for web scrapers because content appears only after the JavaScript code is executed. Regular HTML extraction tools, such as Python’s Requests library, lack the ability to deal with dynamic pages.

Outsourcing your data extraction needs to web scraping services surely helps in overcoming these limitations.

Future of Web Scraping

There are currently about 2 billion active websites on the internet. In actuality, the last two years have seen the creation of 90% of the material on the internet. With 50 billion linked devices, there are around 4.2 billion active people online. A significant portion of the everyday online content generation is driven by social media alone.

There are now data scraping AI on the market that can use machine learning to improve their recognition of inputs that only humans have traditionally been able to interpret, such as images.

How Can A Chief Data Officer (CDO) Leverage Scraping Service?

Web scraping can be used by a Chief Data Officer (CDO) to collect large amounts of data from the internet that can be used to inform business decisions. Data on competitors, market trends, consumer sentiment, and other factors that can help a company gain a competitive advantage can be included in this data.

A CDO, for example, can use web scraping to collect pricing and product offerings from a company’s competitors, which can then be used to inform pricing and product development strategies. Web scraping services can also be used to collect data on consumer sentiment and reviews, which can then be used to improve customer service and marketing efforts.

Additionally, web scraping can also be used to collect unstructured data, such as news articles and social media posts, which can then be analyzed to gain insights into industry trends and public opinion.

Overall, CDOs can use web scraping to collect data from various sources and make data-driven decisions to improve their company’s operations.

What the Future Holds?

Scraping regulations will undoubtedly become more stringent as data harvesting becomes more popular. Web scraping services provide many benefits to businesses and individuals in terms of taking control of whatever they do. When it comes to monopolizing the market or creating a huge gap between companies, the government can be very strict. Especially, if it is accomplished by gaining access to data and information that does not directly belong to the scraper. As a result, it’s not surprising that privacy concerns and the legality of web crawling will be a challenge in the future of data scraping.

Due to higher prices, web data extraction may become a luxury that only a few companies can afford.

With the expansion of the internet and the increasing reliance of businesses on data and information, the future of web scraping promises to be full of new adventures and challenges. The brighter the future, the more challenges that may lie ahead. So, no obstacles should make the future of big data any less promising. The future of data scraping is undoubtedly bright and shiny, full of exciting new opportunities for businesses and corporations.

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Why Choose Outsource Bigdata Over Other
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COST SAVING 40% TO 70%

We leverage AI-Augmented & Automation driven process that will provide a great value for your money. Our pricing is straight-forward – zero hidden cost. Choose suitable engagement model – project based, resource-based– full-time, hourly based, outcome based. All cost can be directly converted to outcome.

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We are ISO 9001-2015 & ISO/IEC 27001:2013 accredited company which shows our commitment to providing high-quality services to our clients and our approach to continual improvement. We provide utmost importance to the process quality and data security of our deliverables; and our professionals are trained to follow the process and quality standards

AVAILABLE 24 X 7

ANY TIME ZONE

Outsource Big Data Automation Team is available for your specific time zone that syncs with your in-house Team. This is to assure that you could work with programmers as a part of your extended office.

CUSTOM TRAINING

UP-SKILLING ON DEMAND

Based on your needs and requirements, we could leverage our training academy for building Custom training & upskill candidates. In discussion with your team, we could prepare custom training curriculum and mock sample projects. Typically, it takes 2 weeks to 6 weeks’ time.

FREE PROJECT MANAGER

FOR 10 FULL TIME TEAM

We deploy Project Manager for your project requirement – absolutely free. The objective is to ensure that your project delivery is smooth as per your delivery plan and prepare programmers for the same – especially in the initial days. This offer changes from project to project

Case Studies

AI-Augmented Data Processing

AI-driven automation helps fintech start-up to save go-to-market time & saves substantial cost

Image Data Processing

Process automation saved substantial cost and increased efficiency of periodical image data processing

Semi Automated IT

Semi-Automated web application increases employee experience, reduces attrition and saves substantial cost

E-Commerce Marketplace

1.2 Million lab equipment’s data integration saved $25000 per year & Increased operational efficiency.

Management Consulting

Process automation and web data mining together reduced substantial time and cost.

Financing Company

Web data scraping automation, data warehousing system and Google map based self-serving dashboard with intuitive user interface.

Real Estate

Automation Lead New Process Lowers Operating Costs, Increases Efficiency & Data Quality, and Improves Speed to Market.

Energy Data Provider

Energy product data provider company with a broad vision for automation turns to AIMLEAP to reduce cost & increase efficiency.

Realty Aggregator

Properties made available in near real time after they appear on the source websites and detects inactive listing faster.

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  • Web Data Scraping Data Mining

  • Dedicated Resource (160 hrs)
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  • IT Application Development

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