Web Data Extraction

The Internet as we know today is a repository of information that can be accessed across geographical societies. In just over two decades, the Web has moved from a university curiosity to a fundamental research, marketing and communications vehicle that impinges upon the everyday life of most people in all over the world. It is accessed by over 16% of the population of the world spanning over 233 countries.

As the amount of information on the Web grows, that information becomes ever harder to keep track of and use. Compounding the matter is this information is spread over billions of Web pages, each with its own independent structure and format. So how do you find the information you're looking for in a useful format - and do it quickly and easily without breaking the bank?

Search Isn't Enough

Search engines are a big help, but they can do only part of the work, and they are hard-pressed to keep up with daily changes. For all the power of Google and its kin, all that search engines can do is locate information and point to it. They go only two or three levels deep into a Web site to find information and then return URLs. Search Engines cannot retrieve information from deep-web, information that is available only after filling in some sort of registration form and logging, and store it in a desirable format. In order to save the information in a desirable format or a particular application, after using the search engine to locate data, you still have to do the following tasks to capture the information you need:

· Scan the content until you find the information.

· Mark the information (usually by highlighting with a mouse).

· Switch to another application (such as a spreadsheet, database or word processor).

· Paste the information into that application.

Its not all copy and paste

Consider the scenario of a company is looking to build up an email marketing list of over 100,000 thousand names and email addresses from a public group. It will take up over 28 man-hours if the person manages to copy and paste the Name and Email in 1 second, translating to over $500 in wages only, not to mention the other costs associated with it. Time involved in copying a record is directly proportion to the number of fields of data that has to copy/pasted.

Is there any Alternative to copy-paste?

A better solution, especially for companies that are aiming to exploit a broad swath of data about markets or competitors available on the Internet, lies with usage of custom Web harvesting software and tools.

Web harvesting software automatically extracts information from the Web and picks up where search engines leave off, doing the work the search engine can't. Extraction tools automate the reading, the copying and pasting necessary to collect information for further use. The software mimics the human interaction with the website and gathers data in a manner as if the website is being browsed. Web Harvesting software only navigate the website to locate, filter and copy the required data at much higher speeds that is humanly possible. Advanced software even able to browse the website and gather data silently without leaving the footprints of access.

The next article of this series will give more details about how such softwares and uncover some myths on web harvesting.


Article Source: http://EzineArticles.com/expert/Thomas_Tuke/5484

Data Collection, Just Another Way To Gather Information

Data collection just does not help the companies to launch new products or know about the public reaction to a specific issue, it is a very useful tool for statistical inferences, once the collected data is compiled. The process of data collection is the third step of the six step market research processes. Data collection can be done in two ways involving various technicalities. In this article, we shall give a brief overview of the same.

Data collection can be done in two ways - secondary data and primary data. Secondary data collection involves is the information available in books, journals, previous researches or studies and the Internet. It basically involves making use of the data already present to build or substantiate a concept.

On the other hand, primary data collection is the process of data collection through questionnaire by directly asking respondents of their opinions. Forming the right questionnaire is the most important aspect of data collection. The researcher conducting the data collection just has to be aware of the process. He should have a clear idea about the information sought by the concerned party.

Besides, the data collection officer should be able to construct the questionnaire in such a way so as to elicit the responses needed. Having constructed the questionnaire the researcher should identify the target sample. To illustrate the point clearly, we shall look into the following example.

Suppose, data collection is aimed from an area A, then, if all the residents of the data are given the questionnaire, it is called a census or in other words data collection is done from all the individuals of the specified area. One of the most common examples of data collection done by the government is census. For example the population census conducted by the US Census Bureau every ten years. On the other hand, if only twenty or thirty percent of the population living in area A are given the questionnaire, the mode of data collection would be called sampling.

The data collected from the target sample with a well-defined questionnaire will project the response of the entire population living in the area. Data collected from a sample helps to control the cost and time spent on collecting data from the population. Sample is a part of population.

Data collection just gets easier from the target sample with the help of a pretested questionnaire, which is later analyzed using statistical tests like ANOVA, Chi Square test and so on. These tests help the researcher to infer the result obtained from the data collection.

Market research/data collection is a fast growing and lucrative career option now days. One has to undertake a course in marketing, statistics and research before starting out. It is indeed very important to have a through understanding of various concepts and the theories related. Some basic terminologies related to data collection are: census, incidence, sample, population, parameters, sampling frames and so on.

Source: http://ezinearticles.com/?Data-Collection,-Just-Another-Way-To-Gather-Information&id=853158

Google Sheets vs Web Scraping Services

Google Sheets vs Web Scraping Services

Ever since the data on the web started multiplying in terms of quantity and quality, people have sought out ways to scrape or extract this data for a wide range of applications. Since the scope of extraction was limited back then, the extraction methods mostly comprised of manual methods like copy-pasting text into a local document.

As businesses realized the importance of web scraping as a big data acquisition channel, new technologies and tools surfaced with advanced capabilities to make web scraping easier and efficient.

Today, there are various solutions catering to the web data extraction requirements of companies; DIY tools to managed web scraping services are out there and you can choose one that suits your requirements the best.

Scraping using Google sheets

As we mentioned earlier, there are so many different ways to extract data from the web although not all of these would make sense from a business point of view. You can even use Google docs to extract data from a simple HTML page if you are looking to understand the basics of web scraping. You could check out our guide on using google sheets to scrape a website if you want to learn something that might come handy.

However, Google docs and other web data extraction tools come with their own limitations. For starters, tools aren’t meant for large-scale extraction which is what most businesses will require. Unless you are a hobbyist looking to extract a few web pages for tinkering with a new data visualization tool, you should steer clear from web scraping tools. Scraping tools cannot cater to the requirements of a business as it could be well out of their capabilities.

Enterprise-grade web data extraction

Web scraping is only a common term for the process of saving data from a web page to a local storage or cloud. However, if we consider the practical applications of the data, it’s obvious that there’s a clear distinction between mere web scraping and enterprise-grade web data extraction.

The latter is more inclined towards the extraction of data from the web for real-world applications and hence requires advanced solutions that are built for the same. Following are some of the qualities that an enterprise-grade web scraping solution should have:

- High-end customization options
- Complete automation
- Post-processing options to make the data machine-ready
- Technology to handle dynamic websites
- Capability of handling large-scale extraction

Why DaaS is the best solution for enterprise-grade web scraping

When it comes to extracting data for business use cases, there should be a stark difference in the way things are done. The speed and efficiency matters more in the business world and this demands a managed web scraping solution that takes the complexities and pain points out of the process to provide companies with just the data they need, the way they need it.

Data as a Service is exactly what businesses that are looking to extract web data without losing focus on their core business operations need. Web crawling companies like PromptCloud, that work on the DaaS model does all the heavy lifting associated with extracting web data and deliver only the needed data to the companies in a ready-to-use format.

Source:-https://www.promptcloud.com/blog/google-sheets-vs-web-scraping-services

Web Scraping using Chrome Scraper Extension

chrome scraper extension
Do you want to get data from a web page or website to CSV or Excel Spreadsheet? The answer is web scraping. There are number of web scraping software and services available in the market like Visual Web Ripper, Mozenda, Kimono Labs, Outwit Hub, ScraperWiki and Automation Anywhere etc. for web data extraction. These all tools and services are paid and not easy to use for non-technical persons. Now I am going to discuss another method of doing web scraping that is easy to use and free.  There are various Google Chrome browser extensions available at Google Web Store (https://chrome.google.com/webstore/category/apps) using that we can do screen scraping/web scraping.

1. Web scraper
Official Website: http://www.webscraper.io

Install it by visiting following link:

https://chrome.google.com/webstore/detail/scraper/mbigbapnjcgaffohmbkdlecaccepngjd

Web Scraper is a chrome extension for scraping data out of web pages to Excel Spreadsheet or database. It allows you to create a plan/sitemap. According to that plan/sitemap a website is traversed and the data is extracted. The extracted data can be exported to CSV or stored in CouchDB. It also supports scraping from multiple pages with pagination. You can use Web Scraper for scraping multiple types of data like text, tables, images, links and more. It also supports web data extraction from dynamic web pages built up with modern web technologies like JavaScript and AJAX.

2. Data Miner
Install DataMiner by visiting following link:

https://chrome.google.com/webstore/detail/dataminer/nndknepjnldbdbepjfgmncbggmopgden

DataMiner is a standalone chrome browser plugin for extracting data from the websites. Later on extracted data can be exported to Microsoft Excel spreadsheets or Google Sheets.

Using DataMiner extension, you can scrape data from tables and lists on the websites and easily export them into CSV file or Microsoft Excel. It also supports XPath selectors. You can use it for scraping emails, Google search results, HTML tables etc.



3. Screen Scraper:
Install it by visiting following link:

https://chrome.google.com/webstore/detail/screenscraper/pfegffhjcgkneoemnlniggnhkfioidjg

Screen Scraper is another chrome scraper as it name suggest is a Chrome browser extension/plugin for screen scraping. Screen scraping is the process of automatically scraping/extracting information from websites. Later on, Scraped information can be downloaded as a CSV file or JSON file. It supports Element Selectors and Xpath Selectors method.

4. iMacro
Official Website of iMacro: http://imacros.net/

Install iMacro it by visiting following link:

https://chrome.google.com/webstore/detail/imacros-for-chrome/cplklnmnlbnpmjogncfgfijoopmnlemp?hl=en

iMacro is a macro recorder for your Google Chrome browser. Macro recorder is a piece of tool that records user actions. It allows users to record repetitious tasks on the web and replay it at later time. It is useful tool for web automation, data extraction and web testing. Using iMacros you can remember passwords, fill out web forms, download files and possibilities are endless. iMacros is useful to Web developers for web regression testing, performance testing and web transaction monitoring. To use iMacros you just need to record the task once and save it in your machine next time when you need to perform the same task you need not repeat the same task again and again. iMacro plugin comes for Chrome, Firefox and Internet Explorer too.

Source url :-http://webdata-scraping.com/web-scraping-using-chrome-scraper-extension/

Scraping Dynamic Websites: How We Tackle the Problem

Scraping Dynamic Websites: How We Tackle the Problem

Acquiring data from the web for business applications has already gained popularity if we look at the sheer number of use cases. Companies have realized the value addition provided by data and are looking for better and efficient ways of data extraction. However, web scraping is a niche technical process that takes years to master given the dynamic nature of the web. Since every website is different and custom coded, it’s not possible to write a single program that can handle multiple websites. The web scraping setup should be coded separately for each target site and this needs a team of skilled programmers.

Web scraping is without doubt a complex trade; however if the target site in question employs dynamic coding practices, this complexity is further multiplied. Over the years, we have understood the technical nuances of web scraping and perfected our modus operandi to to scrape dynamic websites with high accuracy and efficiency. Here are some ways how we tackle the challenge of scraping dynamic websites.

1. Proxies

Some websites have different Geo/Device/OS/browser specific versions that they serve depending on the variables. This could give a great deal of confusion to the crawlers especially while figuring out how to extract the right version. This will need some manual work in terms of finding the different versions provided by the site and configuring proxies to fetch the right version as per the requirement. For geo-specific versions, the crawler is simply deployed on a server from where the required version of the site is accessible.

2. Browser automation

When it comes to websites that use very complex and dynamic code, it’s better have all the page content rendered using a browser first. Selenium can be used for browser automation which will help us do the scraping. It is essentially a handy toolkit that can drive the browser from your favorite programming language. Although it’s primarily used for testing, it can be used for scraping dynamic web pages. It can be used to control a web browser, which is how scraping using selenium is typically done. In this case, the browser first renders the page which will help overcome the problem of reverse engineering JavaScript code to fetch the page content. Once the page content is rendered, it is saved locally to scrape the required data points later. Although this is comparatively easy, there is a high chance of encountering errors while scraping using the browser automation method.

3. Handling POST requests

Many web pages will only display the data that we need after receiving a certain input from the user. Let’s say you are looking for used cars data from a particular geo-location on a classified site. The website would first require you to enter the ZIP code of the location from where you need listings from. This ZIP code must be sent to the website as a post request while scraping. We craft the post request using the appropriate parameters so as to reach the target page that contains all the data points to be scraped.

4. Manufacturing the JSON URL

There are dynamic web pages that use AJAX calls to load and refresh the page content. These are particularly difficult to scrape and extract data from as the triggers that make up the JSON file is difficult to trace. This requires a lot of manual inspection and testing, but once the appropriate parameters are identified, a JSON file that would fetch the target page which includes the desired data points can be manufactured. This JSON file is often tweaked automatically for navigation or fetching varying data points. Manufacturing the JSON URL with apt parameters is the primary pain point with web pages that use AJAX calls.
Bottom-line

Scraping dynamic web pages is extremely complicated and demands deep expertise in the field of web scraping. It also demands an extensive tech stack and well-built infrastructure that can handle the complexities associated with web data extraction. With our years of expertise and well-evolved web scraping infrastructure, we cater to data requirements where dynamic web pages are involved on a daily basis.

Source:https://www.promptcloud.com/blog/scraping-dynamic-websites-web-scraping

How Data Scraping Help Businesses?

Gathering data from diverse internet sources like website and others, the process is called as data scraping. Around the globe such and many describe data scraping as web scraping, data harvesting. Now days the competition is very high in every business and for that the companies required to collect more useful data for their business. 

Research market trends and extracting different types of data is necessary today’s. Data scraping is one of the latest technology that collect diverse data from internet source and make use in the analysis.

By using data scraping any one can quickly classify the any kind of information and also make decision and marketing strategies. Reducing risk and also improving business profit are other advantages of data scraping. Scraping data from website by manually and also using data scraper, website scraper and website data scraper tools.

Now you want to get data scraping solutions for your business?The company offers lowest industry rate data scraping, web data scraping and website data scraping services as the need of clients with never compromise on quality and fast turn around time.
For further details about the company send query at info@www.web-scraping-services.com.


Source Url : -http://3idatascraping.weebly.com/blog/how-data-scraping-help-businesses

How We Maintain Data Quality While Handling Large Scale Extraction

How We Maintain Data Quality While Handling Large Scale Extraction

The demand for high quality data is increasing along with the rise in products and services that require data to run. Although the information available on the web is increasing in terms of quantity and quality, extracting it in a clean, usable format remains challenging to most businesses. Having been in the web data extraction business for long enough, we have come to identify the best practices and tactics that would ensure high quality data from the web.

At PromptCloud, we not only make sure data is accessible to everyone, we make sure it’s of high quality, clean and delivered in a structured format. Here is how we maintain the quality while handling zettabytes of data for hundreds of clients from across the world.

Manual QA process

1. Crawler review

Every web data extraction project starts with the crawler setup. Here, the quality of the crawler code and its stability is of high priority as this will have a direct impact on the data quality. The crawlers are programmed by our tech team members who have high technical acumen and experience. Once the crawler is made, two peers review the code to make sure that the optimal approach is used for extraction and to ensure there are no inherent issues with the code. Once this is done, the crawler is deployed on our dedicated servers.

2. Data review

The initial set of data starts coming in when the crawler is run for the first time. This data is manually inspected, first by the tech team and then by one of our business representatives before the setup is finalized. This manual layer of quality check is thorough and weeds out any possible issues with the crawler or the interaction between the crawler and website. If issues are found, the crawler is tweaked to eliminate them completely before the setup is marked complete.

Automated monitoring

Websites get updated over time, quite frequently than you’d imagine. Some of these changes could break the crawler or cause it to start extracting the wrong data. This is why we have developed a fully automated monitoring system to watch over all the crawling jobs happening on our servers. This monitoring system continuously checks the incoming data for inconsistencies and errors. There are three types of issues it can look for:

1. Data validation errors

Every data point has a defined value type. For example, the data point ‘Price’ will always have a numerical value and not text. In cases of website changes, there can be class name mismatches that might cause the crawler to extract wrong data for a certain field. The monitoring system will check if all the data points are in line with their respective value types. If an inconsistency is found, the system immediately sends out a notification to the team members handling that project and the issue is fixed promptly.

2. Volume based inconsistencies

There can be cases where the volume count for records significantly drop or increase in an irregular fashion. This is a red sign as far as web crawling goes. The monitoring system will already have the expected record count for different projects. If inconsistencies are spotted in the data volumes, the system sends out a prompt notification.

3. Site changes

Structural changes happening to the target websites is the main reason why crawlers break. This is monitored by our dedicated monitoring system, quite aggressively. The tool performs frequent checks on the target site to make sure nothing has changed since the previous crawl. If changes are found, it sends out notifications for the same.
High end servers

It is understood that web crawling is a resource-intensive process that needs high performance servers. The quality of servers will determine how smooth the crawling happens and this in turn has an impact on the quality of data. Having firsthand experience in this, we use high-end servers to deploy and run our crawlers. This helps us avoid instances where crawlers fail due to the heavy load on servers.

Data cleansing

The initially crawled data might have unnecessary elements like HTML tags. In that sense, this data can be called crude. Our cleansing system does an exceptionally good job at eliminating these elements and cleaning up the data thoroughly. The output is clean data without any of the unwanted elements.

Structuring

Structuring is what makes the data compatible with databases and analytics systems by giving it a proper, machine readable syntax. This is the final process before delivering the data to the clients. With structuring done, the data is ready to be consumed either by importing it to a database or plugging to an analytics system. We deliver the data in multiple formats – XML, JSON and CSV which also adds to the convenience of handling it.

Source:https://www.promptcloud.com/blog/how-we-maintain-data-quality-web-data-extraction