Why Outsourcing Data Mining Services?

Why Outsourcing Data Mining Services?

Are huge volumes of raw data waiting to be converted into information that you can use? Your organization's hunt for valuable information ends with valuable data mining, which can help to bring more accuracy and clarity in decision making process.

Nowadays world is information hungry and with Internet offering flexible communication, there is remarkable flow of data. It is significant to make the data available in a readily workable format where it can be of great help to your business. Then filtered data is of considerable use to the organization and efficient this services to increase profits, smooth work flow and ameliorating overall risks.

Data mining is a process that engages sorting through vast amounts of data and seeking out the pertinent information. Most of the instance data mining is conducted by professional, business organizations and financial analysts, although there are many growing fields that are finding the benefits of using in their business.

Data mining is helpful in every decision to make it quick and feasible. The information obtained by it is used for several applications for decision-making relating to direct marketing, e-commerce, customer relationship management, healthcare, scientific tests, telecommunications, financial services and utilities.

Data mining services include:

    Congregation data from websites into excel database
    Searching & collecting contact information from websites
    Using software to extract data from websites
    Extracting and summarizing stories from news sources
    Gathering information about competitors business

In this globalization era, handling your important data is becoming a headache for many business verticals. Then outsourcing is profitable option for your business. Since all projects are customized to suit the exact needs of the customer, huge savings in terms of time, money and infrastructure can be realized.

Advantages of Outsourcing Data Mining Services:

    Skilled and qualified technical staff who are proficient in English
    Improved technology scalability
    Advanced infrastructure resources
    Quick turnaround time
    Cost-effective prices
    Secure Network systems to ensure data safety
    Increased market coverage

Outsourcing will help you to focus on your core business operations and thus improve overall productivity. So data mining outsourcing is become wise choice for business. Outsourcing of this services helps businesses to manage their data effectively, which in turn enable them to achieve higher profits.

Source : http://ezinearticles.com/?Why-Outsourcing-Data-Mining-Services?&id=3066061

Know What the Truth Behind Data Mining Outsourcing Service

Know What the Truth Behind Data Mining Outsourcing Service

We came to that, what we call the information age where industries are like useful data needed for decision-making, the creation of products - among other essential uses for business. Information mining and converting them to useful information is a part of this trend that allows companies to reach their optimum potential. However, many companies that do not meet even one deal with data mining question because they are simply overwhelmed with other important tasks. This is where data mining outsourcing comes in.

There have been many definitions to introduced, but it can be simply explained as a process that involves sorting through large amounts of raw data to extract valuable information needed by industries and enterprises in various fields. In most cases this is done by professionals, professional organizations and financial analysts. He has seen considerable growth in the number of sectors or groups that enter my self.
There are a number of reasons why there is a rapid growth in data mining outsourcing service subscriptions. Some of them are presented below:

A wide range of services

Many companies are turning to information mining outsourcing, because they cover a wide range of services. These services include, but are not limited to data from web applications congregation database, collect contact information from different sites, extract data from websites using the software, the sort of stories from sources news, information and accumulate commercial competitors.

Many companies fall

Many industries benefit because it is fast and realistic. The information extracted by data mining service providers of outsourcing used in crucial decisions in the field of direct marketing, e-commerce, customer relationship management, health, scientific tests and other experimental work, telecommunications, financial services, and a whole lot more.

A lot of advantages

Subscribe data mining outsourcing services it's offers many benefits, as providers assures customers to render services to world standards. They strive to work with improved technologies, scalability, sophisticated infrastructure, resources, timeliness, cost, the system safer for the security of information and increased market coverage.

Outsourcing allows companies to focus their core business and can improve overall productivity. Not surprisingly, information mining outsourcing has been a first choice of many companies - to propel the business to higher profits.

Source:http://ezinearticles.com/?Know-What-the-Truth-Behind-Data-Mining-Outsourcing-Service&id=5303589

Data Extraction Services - A Helpful Hand For Large Organization

Data Extraction Services - A Helpful Hand For Large Organization

The data extraction is the way to extract and to structure data from not structured and semi-structured electronic documents, as found on the web and in various data warehouses. Data extraction is extremely useful for the huge organizations which deal with considerable amounts of data, daily, which must be transformed into significant information and be stored for the use this later on.

Your company with tons of data but it is difficult to control and convert the data into useful information. Without right information at the right time and based on half of accurate information, decision makers with a company waste time by making wrong strategic decisions. In high competing world of businesses, the essential statistics such as information customer, the operational figures of the competitor and the sales figures inter-members play a big role in the manufacture of the strategic decisions. It can help you to take strategic business decisions that can shape your business' goals..

Outsourcing companies provide custom made services to the client's requirements. A few of the areas where it can be used to generate better sales leads, extract and harvest product pricing data, capture financial data, acquire real estate data, conduct market research , survey and analysis, conduct product research and analysis and duplicate an online database..

The different types of Data Extraction Services:

    Database Extraction:
Reorganized data from multiple databases such as statistics about competitor's products, pricing and latest offers and customer opinion and reviews can be extracted and stored as per the requirement of company.

    Web Data Extraction:
Web Data Extraction is also known as data Extraction which is usually referred to the practice of extract or reading text data from a targeted website.

Businesses have now realized about the huge benefits they can get by outsourcing their services. Then outsourcing is profitable option for business. Since all projects are custom based to suit the exact needs of the customer, huge savings in terms of time, money and infrastructure are among the many advantages that outsourcing brings.

Advantages of Outsourcing Data Extraction Services:

    Improved technology scalability
    Skilled and qualified technical staff who are proficient in English
    Advanced infrastructure resources
    Quick turnaround time
    Cost-effective prices
    Secure Network systems to ensure data safety
    Increased market coverage

By outsourcing, you can definitely increase your competitive advantages. Outsourcing of services helps businesses to manage their data effectively, which in turn would enable them to experience an increase in profits.

Outsourcing Web Research offer complete Data Extraction Services and Solutions to quickly collective data and information from multiple Internet sources for your Business needs in a cost efficient manner. For more info please visit us at: http://www.webscrapingexpert.com/ or directly send your requirements at: info@webscrapingexpert.com

Source:http://ezinearticles.com/?Data-Extraction-Services---A-Helpful-Hand-For-Large-Organization&id=2477589

Web Data Extraction

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.

Source: http://ezinearticles.com/?Web-Data-Extraction&id=575212

Web Data Extraction Services and Data Collection Form Website Pages

Web Data Extraction Services and Data Collection Form Website Pages

For any business market research and surveys plays crucial role in strategic decision making. Web scrapping and data extraction techniques help you find relevant information and data for your business or personal use. Most of the time professionals manually copy-paste data from web pages or download a whole website resulting in waste of time and efforts.

Instead, consider using web scraping techniques that crawls through thousands of website pages to extract specific information and simultaneously save this information into a database, CSV file, XML file or any other custom format for future reference.

Examples of web data extraction process include:
• Spider a government portal, extracting names of citizens for a survey
• Crawl competitor websites for product pricing and feature data
• Use web scraping to download images from a stock photography site for website design

Automated Data Collection
Web scraping also allows you to monitor website data changes over stipulated period and collect these data on a scheduled basis automatically. Automated data collection helps you discover market trends, determine user behavior and predict how data will change in near future.

Examples of automated data collection include:
• Monitor price information for select stocks on hourly basis
• Collect mortgage rates from various financial firms on daily basis
• Check whether reports on constant basis as and when required

Using web data extraction services you can mine any data related to your business objective, download them into a spreadsheet so that they can be analyzed and compared with ease.

In this way you get accurate and quicker results saving hundreds of man-hours and money!

With web data extraction services you can easily fetch product pricing information, sales leads, mailing database, competitors data, profile data and many more on a consistent basis.

Source:http://ezinearticles.com/?Web-Data-Extraction-Services-and-Data-Collection-Form-Website-Pages&id=4860417

PDF Scraping: Making Modern File Formats More Accessible

PDF Scraping: Making Modern File Formats More Accessible

Data scraping is the process of automatically sorting through information contained on the internet inside html, PDF or other documents and collecting relevant information to into databases and spreadsheets for later retrieval. On most websites, the text is easily and accessibly written in the source code but an increasing number of businesses are using Adobe PDF format (Portable Document Format: A format which can be viewed by the free Adobe Acrobat software on almost any operating system. See below for a link.). The advantage of PDF format is that the document looks exactly the same no matter which computer you view it from making it ideal for business forms, specification sheets, etc.; the disadvantage is that the text is converted into an image from which you often cannot easily copy and paste. PDF Scraping is the process of data scraping information contained in PDF files. To PDF scrape a PDF document, you must employ a more diverse set of tools.

There are two main types of PDF files: those built from a text file and those built from an image (likely scanned in). Adobe's own software is capable of PDF scraping from text-based PDF files but special tools are needed for PDF scraping text from image-based PDF files. The primary tool for PDF scraping is the OCR program. OCR, or Optical Character Recognition, programs scan a document for small pictures that they can separate into letters. These pictures are then compared to actual letters and if matches are found, the letters are copied into a file. OCR programs can perform PDF scraping of image-based PDF files quite accurately but they are not perfect.

Once the OCR program or Adobe program has finished PDF scraping a document, you can search through the data to find the parts you are most interested in. This information can then be stored into your favorite database or spreadsheet program. Some PDF scraping programs can sort the data into databases and/or spreadsheets automatically making your job that much easier.

Quite often you will not find a PDF scraping program that will obtain exactly the data you want without customization. Surprisingly a search on Google only turned up one business, (the amusingly named ScrapeGoat.com that will create a customized PDF scraping utility for your project. A handful of off the shelf utilities claim to be customizable, but seem to require a bit of programming knowledge and time commitment to use effectively. Obtaining the data yourself with one of these tools may be possible but will likely prove quite tedious and time consuming. It may be advisable to contract a company that specializes in PDF scraping to do it for you quickly and professionally.

Let's explore some real world examples of the uses of PDF scraping technology. A group at Cornell University wanted to improve a database of technical documents in PDF format by taking the old PDF file where the links and references were just images of text and changing the links and references into working clickable links thus making the database easy to navigate and cross-reference. They employed a PDF scraping utility to deconstruct the PDF files and figure out where the links were. They then could create a simple script to re-create the PDF files with working links replacing the old text image.

A computer hardware vendor wanted to display specifications data for his hardware on his website. He hired a company to perform PDF scraping of the hardware documentation on the manufacturers' website and save the PDF scraped data into a database he could use to update his webpage automatically.

PDF Scraping is just collecting information that is available on the public internet. PDF Scraping does not violate copyright laws.

PDF Scraping is a great new technology that can significantly reduce your workload if it involves retrieving information from PDF files. Applications exist that can help you with smaller, easier PDF Scraping projects but companies exist that will create custom applications for larger or more intricate PDF Scraping jobs.

Source: http://ezinearticles.com/?PDF-Scraping:-Making-Modern-File-Formats-More-Accessible&id=193321

How Xpath Plays Vital Role In Web Scraping

How Xpath Plays Vital Role In Web Scraping

XPath is a language for finding information in structured documents like XML or HTML. You can say that XPath is (sort of) SQL for XML or HTML files. XPath is used to navigate through elements and attributes in an XML or HTML document.

To understand XPath we must be clear about elements and nodes which are the building blocks of XML and HTML. Let’s talk about them. Here is an example element in an HTML document:

   <a class=”hyperlink” href=http://www.google.com>google</a>

Copy the above text to a file, name it as sample.html and open it in a browser. This will end up as a text link displaying the words “google” and it will take you to www.google.com. For each element there are three main parts: The type, the attributes, andthe text. They are listed below:

 a                                 Type
class,  href                Attributes
google                       Text

Let’s grab some XPath developer tools. I am on Firebug for Firefox or you can use Chrome’s developer tools. We will now form some XPath expressions to extract data from the above element. We will also verify the XPath by using Firebug Console.

For extracting the text “google”:

   //a[@href]/text()   

   //a[@class=”hyperlink”]/text()
 
For extracting the hyperlink i.e. ”www.google.com” :

   //a/@href
//a[@class=”hyperlink”]/@href

That’s all with a single element but in reality, you need to deal with more complex forms.

Let’s proceed to the idea of nodes, and its familial relationship of HTML elements. Look at this example code:

 <div title=”Section1″>

   <table id=”Search”>

       <tr class=”Yahoo”>Yahoo Search</tr>

       <tr class=”Google”>Google Search</tr>

   </table>

</div>

 Notice the </div> at the bottom? That means the table and tr elements are contained within the div. These other elements are considered descendants of the div. The table is a child, and the tr is a grandchild (and so on and so forth). The two tr elements are considered siblings each other. This is vital, as XPath uses these relationships to find your element.

So suppose you want to find the Google item. Any of the following expressions will work:

   //tr[@class=’Google’]
   //div/table/tr[2]
  //div[@title=”Section1″]//tr

So let’s analyze the expressions. We start at the top element (also known as a node). The // means to search all descendants, / means to just look at the current element’s children. So //div means look through all descendants for a div element. The brackets [] specify something about that element. So we can look for an attribute with the @ symbol, or look for text with the text() function. We can chain as many of these together as we can.

Here is a quick reference:

   //             Search all descendant elements
   /              Search all child elements
   []             The predicate (specifies something about the element you are looking for)
   @           Specifies an element attribute. (For example, @title)
   
   .               Specifies the current node (useful when you want to look for an element’s children in the predicate)
   ..              Specifies the parent node
  text()       Gets the text of the element.
   
In the context of web scraping, XPath is a nice tool to have in your belt, as it allows you to write specifications of document locations more flexibly than CSS selectors.

Please subscribe to our blog to get notified when we publish the next blog post.

Source: http://blog.datahut.co/how-xpath-plays-vital-role-in-web-scraping/

Scraping Yelp Data and How to use?

Scraping Yelp Data and How to use?

We get a lot of requests to scrape data from Yelp. These requests come in on a daily basis, sometimes several times a day. At the same time we have not seen a good business case for a commercial project with scraping Yelp.

We have decided to release a simple example Yelp robot which anyone can run on Chrome inside your computer, tune to your own requirements and collect some data. With this robot you can save business contact information like address, postal code, telephone numbers, website addresses etc.  Robot is placed in our Demo space on Web Robots portal for anyone to use, just sign up, find the robot and use it.

How to use it:

    Sign in to our portal here.
    Download our scraping extension from here.
    Find robot named Yelp_us_demo in the dropdown.
    Modify start URL to the first page of your search results. For example: http://www.yelp.com/search?find_desc=Restaurants&find_loc=Arlington,+VA,+USA
    Click Run.
    Let robot finish it’s job and download data from portal.

Some things to consider:

This robot is placed in our Demo space – therefore it is accessible to anyone. Anyone will be able to modify and run it, anyone will be able to download collected data. Robot’s code may be edited by someone else, but you can always restore it from sample code below. Yelp limits number of search results, so do not expect to scrape more results than you would normally see by search.

In case you want to create your own version of such robot, here it’s full code:

// starting URL above must be the first page of search results.
// Example: http://www.yelp.com/search?find_desc=Restaurants&find_loc=Arlington,+VA,+USA

steps.start = function () {

   var rows = [];

   $(".biz-listing-large").each (function (i,v) {
     if ($("h3 a", v).length > 0)
       {
        var row = {};
        row.company = $(".biz-name", v).text().trim();
        row.reviews =$(".review-count", v).text().trim();
        row.companyLink = $(".biz-name", v)[0].href;
        row.location = $(".secondary-attributes address", v).text().trim();
        row.phone = $(".biz-phone", v).text().trim();
        rows.push (row);
      }
   });

   emit ("yelp", rows);
   if ($(".next").length === 1) {
     next ($(".next")[0].href, "start");
   }
 done();
};

Source: https://webrobots.io/scraping-yelp-data/

How to use Web Content Extractor(WCE) as Email Scraper?

How to use Web Content Extractor(WCE) as Email Scraper?

Web Content Extractor is a great web scraping software developed by Newprosoft Team. The software has easy to use project wizard to create a scraping configuration and scrape data from websites.

One day I came to see the Visual Email Extractor which is also product of Newprosoft and similar to Web Content Extractor but it’s primary use is to scrape email addresses by crawling websites you feed to the scraper. I had noticed that with the little modification in Web Content Extractor project configuration you can use it same as Visual Email Extractor to extract email addresses.

In this post I will show you what configuration makes the Web Content Extractor to extract email addresses. I still recommend Visual Email Extractor as it has lot more features then extracting email using WCE.

Here are the configuration that makes WCE to Extract Emails.

Step 1 : Open Web Content Extractor and Create New Project and Click on Next.

Step 2:  Under Crawling Rules -> Advanced Rules Tab do the following settings

Crawling Level 1 Settings

Follow Links if link text equals:
*contact*; *feedback*; *support*; *about*

for 'Follow Links if link text equals' text box enter following values:
contact; feedback; support; about

for 'Do not Follow links if URL contains' text box enter following values:

google.; yahoo.; bing; msn.; altavista.; myspace.com; youtube.com; googleusercontent.com; =http; .jpg; .gif; .png; .bmp; .exe; .zip; .pdf;

Set 'Maximum Crawling Deapth' to 2

set 'Crawling Order' to Deapth First Crawling

Tick mark below below check boxes:

->Follow all internal links

  Crawling Level 2  Settings

set 'Follow links if link text equals' to below value

*contact*; *feedback*; *support*; *about*

set 'Follow links if url contains' text box to below value

contact; feedback; support; about

set 'DO NOT follow links if url contains' text box to below value

=http

Step 3 After doing above settings now click on Next  -> in Extraction Pattern window -> Click on Define ->  in Web Page Address (URL) give any URL where email is given.  and click on  + sign right of Date Fields to define scraping pattern.

Now inside HTML Structure selects HTML check box or Body check box which means for each page it will take whole page content to parse data.

Now last settings to extract emails from page using regular expression based email extraction function.  Open Predefined Script window and select ‘Extract_Email_Addresses‘ and click on OK. and if you have used page that contains email then in Script Result’ you will be able to see the harvested email.

Hope this will help you to use your Web Content Extractor as a Email Scraper.. Share your view in comment.

Web Scraping – A trending technique in data science!!!

Web Scraping – A trending technique in data science!!!

Web scraping as a market segment is trending to be an emerging technique in data science to become an integral part of many businesses – sometimes whole companies are formed based on web scraping. Web scraping and extraction of relevant data gives businesses an insight into market trends, competition, potential customers, business performance etc.  Now question is that “what is actually web scraping and where is it used???” Let us explore web scraping, web data extraction, web mining/data mining or screen scraping in details.

What is Web Scraping?

Web Data Scraping is a great technique of extracting unstructured data from the websites and transforming that data into structured data that can be stored and analyzed in a database. Web Scraping is also known as web data extraction, web data scraping, web harvesting or screen scraping.

What you can see on the web that can be extracted. Extracting targeted information from websites assists you to take effective decisions in your business.

Web scraping is a form of data mining. The overall goal of the web scraping process is to extract information from a websites and transform it into an understandable structure like spreadsheets, database or csv. Data like item pricing, stock pricing, different reports, market pricing, product details, business leads can be gathered via web scraping efforts.

There are countless uses and potential scenarios, either business oriented or non-profit. Public institutions, companies and organizations, entrepreneurs, professionals etc. generate an enormous amount of information/data every day.

Uses of Web Scraping:

The following are some of the uses of web scraping:

•     Collect data from real estate listing
•     Collecting retailer sites data on daily basis
•     Extracting offers and discounts from a website.
•     Scraping job posting.
•     Price monitoring with competitors.
•     Gathering leads from online business directories – directory scraping
•     Keywords research
•     Gathering targeted emails for email marketing – email scraping
•     And many more.

There are various techniques used for data gathering as listed below:

    Human copy-and-paste – takes lot of time to finish when data is huge
    Programming the Custom Web Scraper as per the needs.
    Using Web Scraping Softwares available in market.

Are you in search of web data scraping expert or specialist. Then you are at right place. We are the team of web scraping experts who could easily extract data from website and further structure the unstructured useful data to uncover patterns, and help businesses for decision making that helps in increasing sales, cover a wide customer base and ultimately it leads to business towards growth and success.

We have got expertise in all the web scraping techniques, scraping data from ajax enabled complex websites, bypassing CAPTCHAs, forming anonymous http request etc in providing web scraping services.

Source: http://webdata-scraping.com/web-scraping-trending-technique-in-data-science/

How to Use Microsoft Excel as a Web Scraping Tool

How to Use Microsoft Excel as a Web Scraping Tool

Microsoft Excel is undoubtedly one of the most powerful tools to manage information in a structured form. The immense popularity of Excel is not without reasons. It is like the Swiss army knife of data with its great features and capabilities. Here is how Excel can be used as a basic web scraping tool to extract web data directly into a worksheet. We will be using Excel web queries to make this happen.

Web queries is a feature of Excel which is basically used to fetch data on a web page into the Excel worksheet easily. It can automatically find tables on the webpage and would let you pick the particular table you need data from. Web queries can also be handy in situations where an ODBC connection is impossible to maintain apart from just extracting data from web pages. Let’s see how web queries work and how you can scrape HTML tables off the web using them.
Getting started

We’ll start with a simple Web query to scrape data from the Yahoo! Finance page. This page is particularly easier to scrape and hence is a good fit for learning the method. The page is also pretty straightforward and doesn’t have important information in the form of links or images. Here is the URL we will be using for the tutorial:

http://finance.yahoo.com/q/hp?s=GOOG

To create a new Web query:

1. Select the cell in which you want the data to appear.
2. Click on Data-> From Web
3. The New Web query box will pop up as shown below.

4. Enter the web page URL you need to extract data from in the Address bar and hit the Go button.
5. Click on the yellow-black buttons next to the table you need to extract data from.

6. After selecting the required tables, click on the Import button and you’re done. Excel will now start downloading the content of the selected tables into your worksheet.

Once you have the data scraped into your Excel worksheet, you can do a host of things like creating charts, sorting, formatting etc. to better understand or present the data in a simpler way.
Customizing the query

Once you have created a web query, you have the option to customize it according to your requirements. To do this, access Web query properties by right clicking on a cell with the extracted data. The page you were querying appears again, click on the Options button to the right of the address bar. A new pop up box will be displayed where you can customize how the web query interacts with the target page. The options here lets you change some of the basic things related to web pages like the formatting and redirections.

Apart from this, you can also alter the data range options by right clicking on a random cell with the query results and selecting Data range properties. The data range properties dialog box will pop up where you can make the required changes. You might want to rename the data range to something you can easily recognize like ‘Stock Prices’.

Auto refresh

Auto-refresh is a feature of web queries worth mentioning, and one which makes our Excel web scraper truly powerful. You can make the extracted data to be auto-refreshing so that your Excel worksheet will update the data whenever the source website changes. You can set how often you need the data to be updated from the source web page in data range options menu. The auto refresh feature can be enabled by ticking the box beside ‘Refresh every’ and setting your preferred time interval for updating the data.
Web scraping at scale

Although extracting data using Excel can be a great way to scrape html tables from the web, it is nowhere close to a real web scraping solution. This can prove to be useful if you are collecting data for your college research paper or you are a hobbyist looking for a cheap way to get your hands on some data. If data for business is your need, you will definitely have to depend on a web scraping provider with expertise in dealing with web scraping at scale. Outsourcing the complicated process that web scraping will also give you more room to deal with other things that need extra attention such as marketing your business.

Source: https://www.promptcloud.com/blog/how-to-use-excel-to-scrape-websites

Why Healthcare Companies should look towards Web Scraping

Why Healthcare Companies should look towards Web Scraping

The internet is a massive storehouse of information which is available in the form of text, media and other formats. To be competitive in this modern world, most businesses need access to this storehouse of information. But, all this information is not freely accessible as several websites do not allow you to save the data. This is where the process of Web Scraping comes in handy.

Web scraping is not new—it has been widely used by financial organizations, for detecting fraud; by marketers, for marketing and cross-selling; and by manufacturers for maintenance scheduling and quality control. Web scraping has endless uses for business and personal users. Every business or individual can have his or her own particular need for collecting data. You might want to access data belonging to a particular category from several websites. The different websites belonging to the particular category display information in non-uniform formats. Even if you are surfing a single website, you may not be able to access all the data at one place.

The data may be distributed across multiple pages under various heads. In a market that is vast and evolving rapidly, strategic decision-making demands accurate and thorough data to be analyzed, and on a periodic basis. The process of web scraping can help you mine data from several websites and store it in a single place so that it becomes convenient for you to a alyze the data and deliver results.

In the context of healthcare, web scraping is gaining foothold gradually but qualitatively. Several factors have led to the use of web scraping in healthcare. The voluminous amount of data produced by healthcare industry is too complex to be analyzed by traditional techniques. Web scraping along with data extraction can improve decision-making by determining trends and patterns in huge amounts of intricate data. Such intensive analyses are becoming progressively vital owing to financial pressures that have increased the need for healthcare organizations to arrive at conclusions based on the analysis of financial and clinical data. Furthermore, increasing cases of medical insurance fraud and abuse are encouraging healthcare insurers to resort to web scraping and data extraction techniques.

Healthcare is no longer a sector relying solely on person to person interaction. Healthcare has gone digital in its own way and different stakeholders of this industry such as doctors, nurses, patients and pharmacists are upping their ante technologically to remain in sync with the changing times. In the existing setup, where all choices are data-centric, web scraping in healthcare can impact lives, educate people, and create awareness. As people no more depend only on doctors and pharmacists, web scraping in healthcare can improve lives by offering rational solutions.

To be successful in the healthcare sector, it is important to come up with ways to gather and present information in innovative and informative ways to patients and customers. Web scraping offers a plethora of solutions for the healthcare industry. With web scraping and data extraction solutions, healthcare companies can monitor and gather information as well as track how their healthcare product is being received, used and implemented in different locales. It offers a safer and comprehensive access to data allowing healthcare experts to take the right decisions which ultimately lead to better clinical experience for the patients.

Web scraping not only gives healthcare professionals access to enterprise-wide information but also simplifies the process of data conversion for predictive analysis and reports. Analyzing user reviews in terms of precautions and symptoms for diseases that are incurable till date and are still undergoing medical research for effective treatments, can mitigate the fear in people. Data analysis can be based on data available with patients and is one way of creating awareness among people.

Hence, web scraping can increase the significance of data collection and help doctors make sense of the raw data. With web scraping and data extraction techniques, healthcare insurers can reduce the attempts of frauds, healthcare organizations can focus on better customer relationship management decisions, doctors can identify effective cure and best practices, and patients can get more affordable and better healthcare services.

Web scraping applications in healthcare can have remarkable utility and potential. However, the triumph of web scraping and data extraction techniques in healthcare sector depends on the accessibility to clean healthcare data. For this, it is imperative that the healthcare industry think about how data can be better recorded, stored, primed, and scraped. For instance, healthcare sector can consider standardizing clinical vocabulary and allow sharing of data across organizations to heighten the benefits from healthcare web scraping practices.

Healthcare sector is one of the top sectors where data is multiplying exponentially with time and requires a planned and structured storage of data. Continuous web scraping and data extraction is necessary to gain useful insights for renewing health insurance policies periodically as well as offer affordable and better public health solutions. Web scraping and data extraction together can process the mammoth mounds of healthcare data and transform it into information useful for decision making.

To reduce the gap between various components of healthcare sector-patients, doctors, pharmacies and hospitals, healthcare organizations and websites will have to tap the technology to collect data in all formats and present in a usable form. The healthcare sector needs to overcome the lag in implementing effective web scraping and data extraction techniques as well as intensify their pace of technology adoption. Web scraping can contribute enormously to the healthcare industry and facilitate organizations to methodically collect data and process it to identify inadequacies and best practices that improve patient care and reduce costs.

Source: https://www.promptcloud.com/blog/why-health-care-companies-should-use-web-scraping

ERP Data Conversions - Best Practices and Steps

ERP Data Conversions - Best Practices and Steps

Every company who has gone through an ERP project has gone through the painful process of getting the data ready for the new system. The process of executing this typically goes through the following steps:

(1) Extract or define

(2) Clean and transform

(3) Load

(4) Validate and verify

This process is typically executed multiple times (2 - 5+ times depending on complexity) through an ERP project to ensure that the good data ends up in the new system. If the data is either incorrect, not well enough cleaned or adjusted or loaded incorrectly in to the new system it can cause serious problems as the new system is launched.

(1) Extract or define

This involves extracting the data from legacy systems, which are to be decommissioned. In some cases the data may not exist in a legacy system, as the old process may be spreadsheet-based and has to be created from scratch. Typically this involves creating some extraction programs or leveraging existing reports to get the data in to a format which can be put in to a spreadsheet or a data management application.

(2) Data cleansing

Once extracted it normally reviewed is for accuracy by the business, supported by the IT team, and/or adjusted if incorrect or in a structure which the new ERP system does not understand. Depending on the level of change and data quality this can represent a significant effort involving many business stakeholders and required to go through multiple cycles.

(3) Load data to new system

As the data gets structured to a format which the receiving ERP system can handle the load programs may also be build to handle certain changes as part of the process of getting the data converted in to the new system. Data is loaded in to interface tables and loaded in to the new system's core master data and transactions tables.

When loading the data in to the new system the inter-dependency of the different data elements is key to consider and validate the cross dependencies. Exceptions are dealt with and go in to lessons learned and to modify extracts, data cleansing or load process in to the next cycle.

(4) Validate and verify

The final phase of the data conversion process is to verify the converted data through extracts, reports or manually to ensure that all the data went in correctly. This may also include both internal and external audit groups and all the key data owners. Part of the testing will also include attempting to transact using the converted data successfully.

The topmost success factors or best practices to execute a successful conversion I would prioritize as follows:

(1) Start the data conversion early enough by assessing the quality of the data. Starting too late can result in either costly project delays or decisions to load garbage and "deal with it later" resulting in an increase in problems as the new system is launched.

(2) Identify and assign data owners and customers (often forgotten) for the different elements. Ensure that not only the data owners sign-off on the data conversions but that also the key users of the data are involved in reviewing the selection criteria's, data cleansing process and load verification.

(3) Run sufficient enough rounds of testing of the data, including not only validating the loads but also transacting with the converted data.

(4) Depending on the complexity, evaluate possible tools beyond spreadsheets and custom programming to help with the data conversion process for cleansing, transformation and load process.

(5) Don't under-estimate the effort in cleansing and validating the converted data.

(6) Define processes and consider other tools to help how the accuracy of the data will be maintained after the system goes live.

Source: http://ezinearticles.com/?ERP-Data-Conversions---Best-Practices-and-Steps&id=7263314

Web Scraping Best Practices

Web Scraping Best Practices

Extracting data from the World Wide Web has several challenges as more webmasters are working day and night to lower cases of scraping and crawling of their data in order to survive in the competitive world. There are various other problems you may face when web scraping and most of them can be avoided by adapting and implementing certain web scraping best practices as discussed in this article.

Have knowledge of the scraping tools

Acquiring adequate knowledge of hurdles that may be encountered during web scraping, you will be able to have a smooth web scraping experience and be on the safe side of the law. Conduct a thorough research on the types of tools you will use for scraping and crawling. Firsthand knowledge on these tools will help you find the data you need without being blocked.

Proper proxy software that acts as the middle party works well when you know how to work around HTTP and HTML protocols. Use tools that can change crawling patterns, URLs and data retrieved even when you are crawling on one domain. This will help you abide to the rules and regulations that come with web scraping activities and escaping any legal issues.
Conduct your scraping activities during off-peak hours

You may opt to extract data during times that less people have access for instance over the weekends, during late night hours, public holidays among others. Visiting a website on several instances to retrieve the same type of data is a waste of bandwidth. It is always advisable to download the entire site content to your computer and thereafter you can access it whenever need arises.
Hide your scrapping activities

There is a thin line between ethical and unethical crawling hence you should completely evade being on the top user list of a particular website. Cover up your track as best as you can by making use of proxy IPs to avoid any legal problems. You may also use multiple IP addresses or VPN services to conceal your scrapping activities and lower chances of landing on a website’s blacklist.

Website owners today are very protective of their data and any other information existing under their unique url. Be keen when going through the terms and conditions indicated by websites as they may consider crawling as an infringement of their privacy. Simple etiquette goes a long way. Your web scraping efforts will be fruitful if the site owner supports the idea of sharing data.
Keep record of your activities

Web scraping involves large amount of data.Due to this you may not always remember each and every piece of information you have acquired, gathering statistics will help you monitor your activities.
Load data in phases

Web scraping demands a lot of patience from you when using the crawlers to get needed information. Take the process in a slow manner by loading data one piece at a time. Several parallel request to the same domain can crush the entire site or retrace the scrapping attempts back to your local machine.

Loading data small bits will save you the hustle of scrapping afresh in case that your activity has been interrupted because you will have already stored part of the data required. You can reduce the loading data on an individual domain through various techniques such as caching pages that you have scrapped to escape redundancy occurrences. Use auto throttling mechanisms to increase the amount of traffic to the website and pause for breaks between requests to prevent getting banned.
Conclusion

Through these few mentioned web scraping best practices you will be able to work around website and gather the data required as per clients’ request without major hurdles along the way. The ultimate goal of every web scraper is to be able to access vital information and at the same time remain on the good side of the law.

Source: http://nocodewebscraping.com/web-scraping-best-practices/

Three Common Methods For Web Data Extraction

Three Common Methods For Web Data Extraction

Probably the most common technique used traditionally to extract data from web pages this is to cook up some regular expressions that match the pieces you want (e.g., URL's and link titles). Our screen-scraper software actually started out as an application written in Perl for this very reason. In addition to regular expressions, you might also use some code written in something like Java or Active Server Pages to parse out larger chunks of text. Using raw regular expressions to pull out the data can be a little intimidating to the uninitiated, and can get a bit messy when a script contains a lot of them. At the same time, if you're already familiar with regular expressions, and your scraping project is relatively small, they can be a great solution.

Other techniques for getting the data out can get very sophisticated as algorithms that make use of artificial intelligence and such are applied to the page. Some programs will actually analyze the semantic content of an HTML page, then intelligently pull out the pieces that are of interest. Still other approaches deal with developing "ontologies", or hierarchical vocabularies intended to represent the content domain.

There are a number of companies (including our own) that offer commercial applications specifically intended to do screen-scraping. The applications vary quite a bit, but for medium to large-sized projects they're often a good solution. Each one will have its own learning curve, so you should plan on taking time to learn the ins and outs of a new application. Especially if you plan on doing a fair amount of screen-scraping it's probably a good idea to at least shop around for a screen-scraping application, as it will likely save you time and money in the long run.

So what's the best approach to data extraction? It really depends on what your needs are, and what resources you have at your disposal. Here are some of the pros and cons of the various approaches, as well as suggestions on when you might use each one:

Raw regular expressions and code

Advantages:

- If you're already familiar with regular expressions and at least one programming language, this can be a quick solution.

- Regular expressions allow for a fair amount of "fuzziness" in the matching such that minor changes to the content won't break them.

- You likely don't need to learn any new languages or tools (again, assuming you're already familiar with regular expressions and a programming language).

- Regular expressions are supported in almost all modern programming languages. Heck, even VBScript has a regular expression engine. It's also nice because the various regular expression implementations don't vary too significantly in their syntax.

Disadvantages:

- They can be complex for those that don't have a lot of experience with them. Learning regular expressions isn't like going from Perl to Java. It's more like going from Perl to XSLT, where you have to wrap your mind around a completely different way of viewing the problem.

- They're often confusing to analyze. Take a look through some of the regular expressions people have created to match something as simple as an email address and you'll see what I mean.

- If the content you're trying to match changes (e.g., they change the web page by adding a new "font" tag) you'll likely need to update your regular expressions to account for the change.

- The data discovery portion of the process (traversing various web pages to get to the page containing the data you want) will still need to be handled, and can get fairly complex if you need to deal with cookies and such.

When to use this approach: You'll most likely use straight regular expressions in screen-scraping when you have a small job you want to get done quickly. Especially if you already know regular expressions, there's no sense in getting into other tools if all you need to do is pull some news headlines off of a site.

Ontologies and artificial intelligence

Advantages:

- You create it once and it can more or less extract the data from any page within the content domain you're targeting.

- The data model is generally built in. For example, if you're extracting data about cars from web sites the extraction engine already knows what the make, model, and price are, so it can easily map them to existing data structures (e.g., insert the data into the correct locations in your database).

- There is relatively little long-term maintenance required. As web sites change you likely will need to do very little to your extraction engine in order to account for the changes.

Disadvantages:

- It's relatively complex to create and work with such an engine. The level of expertise required to even understand an extraction engine that uses artificial intelligence and ontologies is much higher than what is required to deal with regular expressions.

- These types of engines are expensive to build. There are commercial offerings that will give you the basis for doing this type of data extraction, but you still need to configure them to work with the specific content domain you're targeting.

- You still have to deal with the data discovery portion of the process, which may not fit as well with this approach (meaning you may have to create an entirely separate engine to handle data discovery). Data discovery is the process of crawling web sites such that you arrive at the pages where you want to extract data.

When to use this approach: Typically you'll only get into ontologies and artificial intelligence when you're planning on extracting information from a very large number of sources. It also makes sense to do this when the data you're trying to extract is in a very unstructured format (e.g., newspaper classified ads). In cases where the data is very structured (meaning there are clear labels identifying the various data fields), it may make more sense to go with regular expressions or a screen-scraping application.

Screen-scraping software

Advantages:

- Abstracts most of the complicated stuff away. You can do some pretty sophisticated things in most screen-scraping applications without knowing anything about regular expressions, HTTP, or cookies.

- Dramatically reduces the amount of time required to set up a site to be scraped. Once you learn a particular screen-scraping application the amount of time it requires to scrape sites vs. other methods is significantly lowered.

- Support from a commercial company. If you run into trouble while using a commercial screen-scraping application, chances are there are support forums and help lines where you can get assistance.

Disadvantages:

- The learning curve. Each screen-scraping application has its own way of going about things. This may imply learning a new scripting language in addition to familiarizing yourself with how the core application works.

- A potential cost. Most ready-to-go screen-scraping applications are commercial, so you'll likely be paying in dollars as well as time for this solution.

- A proprietary approach. Any time you use a proprietary application to solve a computing problem (and proprietary is obviously a matter of degree) you're locking yourself into using that approach. This may or may not be a big deal, but you should at least consider how well the application you're using will integrate with other software applications you currently have. For example, once the screen-scraping application has extracted the data how easy is it for you to get to that data from your own code?

When to use this approach: Screen-scraping applications vary widely in their ease-of-use, price, and suitability to tackle a broad range of scenarios. Chances are, though, that if you don't mind paying a bit, you can save yourself a significant amount of time by using one. If you're doing a quick scrape of a single page you can use just about any language with regular expressions. If you want to extract data from hundreds of web sites that are all formatted differently you're probably better off investing in a complex system that uses ontologies and/or artificial intelligence. For just about everything else, though, you may want to consider investing in an application specifically designed for screen-scraping.

As an aside, I thought I should also mention a recent project we've been involved with that has actually required a hybrid approach of two of the aforementioned methods. We're currently working on a project that deals with extracting newspaper classified ads. The data in classifieds is about as unstructured as you can get. For example, in a real estate ad the term "number of bedrooms" can be written about 25 different ways. The data extraction portion of the process is one that lends itself well to an ontologies-based approach, which is what we've done. However, we still had to handle the data discovery portion. We decided to use screen-scraper for that, and it's handling it just great. The basic process is that screen-scraper traverses the various pages of the site, pulling out raw chunks of data that constitute the classified ads. These ads then get passed to code we've written that uses ontologies in order to extract out the individual pieces we're after. Once the data has been extracted we then insert it into a database.

Source: http://ezinearticles.com/?Three-Common-Methods-For-Web-Data-Extraction&id=165416

Best Alternative For Linkedin Data Scraping

Best Alternative For Linkedin Data Scraping

When I started my career in sales, one of the things that my VP of sales told me is that ” In sales, assumptions are the mother of all f**k ups “. I know the F word sounds a bit inappropriate, but that is the exact word he used. He was trying to convey the simple point that every prospect is different, so don’t guess, use data to come up with decisions.

I joined Datahut and we are working on a product that helps sales people. I thought I should discuss it with you guys and take your feedback.

Let me tell you how the idea evolved itself. At Datahut, we get to hear a lot of problems customers want to solve. Almost 30 percent of all the inbound leads ask us to help them with lead generation.

Most of them simply ask, “Can you scrape Linkedin for me”?

Every time, we politely refused.

But not anymore, we figured out a way to solve their problem without scraping Linkedin.

This should raise some questions in your mind.

1) What problem is he trying to solve?– Most of the time their sales team does not have the accurate data about the prospects. This leads to a total chaos. It will end up in a waste of both time and money by selling the leads that are not sales qualified.

2) Why do they need data specifically from Linkedin? – LinkedIn is the world’s largest business network. In his view, there is no better place to find leads for his business than Linkedin. It is right in a way.

3) Ok, then what is wrong in scraping Linkedin? – Scraping Linkedin is against its terms and it can lead to legal issues. Linkedin has an excellent anti-scraping mechanism which can make the scraping costly.

4) How severe is the problem? – The problem has a direct impact on the revenues as the productivity of the sales team is too low. Without enough sales, the company is a joke.

5) Is there a better way? – Of course yes. The people with profiles in LinkedIn are in other sites too. eg. Google plus, CrunchBase etc. If we can mine and correlate the data, we can generate leads with rich information. It will have better quality than scraping LinkedIn.

6) What to do when the machine intelligence fails? – We have to use human intelligence. Period!

Datahut is working on a platform that can help you get leads that match your ideal buyer persona. It will be a complete Business intelligence platform powered by machine and human intelligence for an efficient lead research & discovery.We named it Leadintel. We’ve also established some partnerships that help to enrich the data and saves the trouble of lawsuits.

We are opening our platform for beta users. You can request an invitation using the contact form. What do you think about this? What are your suggestions?

Thanks for reading this blog post. Datahut offers affordable data extraction services (DaaS) . If you need help with your web scraping projects let us know and we will be glad to help.

Source:http://blog.datahut.co/best-alternative-for-linkedin-data-scraping/

Extract Data from Multiple Web Pages into Excel using import.io

In this tutorial, i will show you how to extract data from multiple web pages of a website or blog and save the extracted data into Excel spreadsheet for further processing.There are various methods and tools to do that but I found them complicated and I prefer to use import.io to accomplish the task.Import.io doesn’t require you to have programming skills.The platform is quite powerful,user-friendly with a lot of support online and above all FREE to use.

You can use the online version of their data extraction software or a desktop application.The online version will be covered in this tutorial.

Let us get started.

Step 1:Find a web page you want to extract data from.
You can extract data such as prices, images, authors’ names, addresses,dates etc

Step 2:Enter the URL for that web page into the text box here and click “Extract data”.

Then click  “Extract data” Import.io will transform the web page into data in seconds.Data such as authors,images,posts published dates and posts title will be pulled from the web page as shown in the image below.

Import.io extracted only 40 posts or articles from the first page of the blog!.
If you visit bongo5.com you will notice that the web page is having a total of 600+ pages at the time of writing this article and each page has 40 posts or articles on it as can be shown by the image below.
Next step will show you how to extract data from multiple pages of the web page into excel.

Step 3:Extract Data from Multiple Web Pages into Excel

Using the import.io online tool you can extract data from 20 web pages maximum.Go to the bottom right corner of the import.io online tool page and click “Download CSV” to save the extracted data from those 20 pages into Excel.
Note:Using the import.io desktop application you can extract an unlimited number of pages and pin point only the data you want to extract.Check out this tutorial on how to use the desktop application.
Once you click “Download CSV” the following pop up window will appear.You can specify the number of pages you want to get data from up to a maximum of 20 pages then click “Go!”
You will need to Sign up for a free account to download that data as a CSV, or save it as an API.If you save it as an API you can go back to the API later to extract new data if the web page is updated without the need to repeat the steps we have done so far.Also, you can use the API for integration into other platforms.
Below image shows 20 rows out of 800 rows of data extracted from the 20 pages of the web page.

Conclusion

The online tool doesn’t offer much flexibility than the desktop application.For example, you can not extract more than 20 pages and you can not pin point the type of data you want to extract.For a more advanced tutorial on how to use the desktop application, you can check out this tutorial I created earlier.

Source URL : http://nocodewebscraping.com/extract-multiple-web-pages-data-into-excel/

4 Web Scraping Tools To Save You Time On Data Extraction

Either you are working on a product website, struggling to add live data feed to your app or merely need to pull out a huge amount of online data for analysis, an accurate web scraping tool can save you loads of time and keep you sane. Here are four powerful web scraping tools to save you from copy-pasting or spending time on writing your own scripts.

Uipath  specializes in developing various process automation software including web scraping and screen scraping software for desktop and web. Uipath web scraper is perfect for non-coders and easily surpasses most common data extraction challenges including page navigation, digging through flash and even scraping PDF files. All you need to do is open the web scraping wizard and simply highlight the data you need to extract. The tool will scrape all the data following this pattern at all pages you’ve chosen and sort it accordingly. You can add as many items for scraping as you like and have them sorted in respective columns. As a result, you receive a neat Excel or CSV document with all the data eliminated from duplicates.

Moreover, Uipath isn’t just about scraping. This software can be used not only for extracting data, but to manipulate the interface of another app, thus establishing data transfers among the two of them. Basically, this tool could be used to conduct any repetitive task a human could do, yet much faster and with higher accuracy.

Pros: You can automate form filling, clicking buttons, navigation etc. Uipath scraper is impressively accurate, fast and simple to use. It “reads” all types of data on screen (JS, HTML, Silverlight and more), plus you can train the software to emulate human actions of various complexity.

Cons: Premium software runs at a premium price. Uipath is an affordable professional solution, but may be a bit too pricey for personal use.

 Import.io  offers you a free desktop app to help you scrap all the data you need from an unlimited amount of web pages. The service treats each page as a potential data source to generate API from. If the page you’ve submitted has been previously processed, you can access its API and get some of the data. In other case, Import.io will guide you through the process of creating the scraping matrix by building connectors (for navigation) or extractors (to pull out the needed data). Afterwards, you submit a request for extraction and it’s typically processed within 24 hours. All the data is private and you can schedule auto refreshments at any chosen period of time.

Pros: The service is easy-to-use with no tech skills needed. It can  pages with data (those that needed login/pass), plus it’s free. Minimalistic effective design and simple navigation comes along.

Cons: Improt.io has hard times navigating through combinations of javascript/POST and cannot navigate from one page to another (e.g. click next, second page etc).  Sometimes, it takes over 24 hours to receive the report.  Besides, it’s a browser-only app, non-compatible with other applications.

Kimono is a popular web scraper among app developers who prefer to power up their products with live data and no additional code. It saves you tons of time when you need to fill up your app with mashing data. Install Kimono Browser bookmarklet; highlight page elements you need to and provide some positive/negative examples to train the tool. After labeling all the data you can download it in CSV/JSON/a web endpoint format. The APIs created for your pages are stored in the cloud and you can run them on schedule. So far, Kimono is free to use with pro and enterprise solutions to be launched soon.

Pros: The tool works pretty fast and works great with scraping newsfeeds and prices. The data is rather accurate.

Cons: No page navigation available and you need to spend quite a lot of time to train Kimono before it starts to pull out the multi items data accurate enough. In general, I’d say Kimono is more of an app mash-ups creator than a full-scale web scraper.

 Screen Scraper  is pretty neat and tackles a lot of difficult tasks including navigation and precise data extractions, however it requires a bit of programming/tokenization skills if you’d like to run it super smooth. Launch the software, add a proxy, start recording the list of your actions and creating extracting patterns (some coding required). Works great with HTML and Javascript, however you should test it with Citrix and other platforms. Basically, screen scraper helps you writing simple web scraping scripts and lets you download the extracted data in txt/csv/excel format.

Pros: When set correctly, there’s no data extraction tasks Screen scraper fails to handle.
Cons: The tool is pricey and you’ll have to go through documentation and have basic coding skills to use it.

Source URL :  http://tech.co/4-web-scraping-tools-save-time-data-extraction-2015-03

ECJ clarifies Database Directive scope in screen scraping case

EC on the legal protection of databases (Database Directive) in a case concerning the extraction of data from a third party’s website by means of automated systems or software for commercial purposes (so called 'screen scraping').

Flight data extracted

The case, Ryanair Ltd vs. PR Aviation BV, C-30/14, is of interest to a range of companies such as price comparison websites. It stemmed from  Dutch company PR Aviation operation of a website where consumers can search through flight data of low-cost airlines  (including Ryanair), compare prices and, on payment of a commission, book a flight. The relevant flight data is extracted from third-parties’ websites by means of ‘screen scraping’ practices.

Ryanair claimed that PR Aviation’s activity:

• amounted to infringement of copyright (relating to the structure and architecture of the database) and of the so-called sui generis database right (i.e. the right granted to the ‘maker’ of the database where certain investments have been made to obtain, verify, or present the contents of a database) under the Netherlands law implementing the Database Directive;

• constituted breach of contract. In this respect, Ryanair claimed that a contract existed with PR Aviation for the use of its website. Access to the latter requires acceptance, by clicking a box, of the airline’s general terms and conditions which, amongst others, prohibit unauthorized ‘screen scraping’ practices for commercial purposes.

Ryanair asked Dutch courts to prohibit the infringement and order damages. In recent years the company has been engaged in several legal cases against web scrapers across Europe.

The Local Court, Utrecht, and the Court of Appeals of Amsterdam dismissed Ryanair’s claims on different grounds. The Court of Appeals, in particular, cited PR Aviation’s screen scraping of Ryanair’s website as amounting to a “normal use” of said website within the meaning of the lawful user exceptions under Sections 6 and 8 of the Database Directive, which cannot be derogated by contract (Section 15).

Ryanair appealed

Ryanair appealed the decision before the Netherlands Supreme Court (Hoge Raad der Nederlanden), which decided to refer the following question to the ECJ for a preliminary ruling: “Does the application of [Directive 96/9] also extend to online databases which are not protected by copyright on the basis of Chapter II of said directive or by a sui generis right on the basis of Chapter III, in the sense that the freedom to use such databases through the (whether or not analogous) application of Article[s] 6(1) and 8, in conjunction with Article 15 [of Directive 96/9] may not be limited contractually?.”

The ECJ’s ruling

The ECJ (without the need of the opinion of the advocate general) ruled that the Database Directive is not applicable to databases which are not protected either by copyright or by the sui generis database right. Therefore, exceptions to restricted acts set forth by Sections 6 and 8 of the Directive do not prevent the database owner from establishing contractual limitations on its use by third parties. In other words, restrictions to the freedom to contract set forth by the Database Directive do not apply in cases of unprotected databases. Whether Ryanair’s website may be entitled to copyright or sui generis database right protection needs to be determined by the competent national court.

The ECJ’s decision is not particularly striking from a legal standpoint. Yet, it could have a significant impact on the business model of price comparison websites, aggregators, and similar businesses. Owners of databases that could not rely on intellectual property protection may contractually prevent extraction and use (“scraping”) of content from their online databases. Thus, unprotected databases could receive greater protection than the one granted by IP law.

Antitrust implications

However, the lawfulness of contractual restrictions prohibiting access and reuse of data through screen scraping practices should be assessed under an antitrust perspective. In this respect, in 2013 the Court of Milan ruled that Ryanair’s refusal to grant access to its database to the online travel agency Viaggiare S.r.l. amounted to an abuse of dominant position in the downstream market of information and intermediation on flights (decision of June 4, 2013 Viaggiare S.r.l. vs Ryanair Ltd). Indeed, a balance should be struck between the need to compensate the efforts and investments made by the creator of the database with the interest of third parties to be granted with access to information (especially in those cases where the latter are not entitled to copyright protection).

Additionally, web scraping triggers other issues which have not been considered by the ECJ’s ruling. These include, but are not limited to trademark law (i.e., whether the use of a company’s names/logos by the web scraper without consent may amount to trademark infringement), data protection (e.g., in case the scraping involves personal data), or unfair competition.


Source URL :http://yellowpagesdatascraping.blogspot.in/2015/07/ecj-clarifies-database-directive-scope.html

Web scraping in under 60 seconds: the magic of import.io

This post was written by Rubén Moya, School of Data fellow in Mexico, and originally posted on Escuela de Datos.

Import.io is a very powerful and easy-to-use tool for data extraction that has the aim of getting data from any website in a structured way.
It is meant for non-programmers that need data (and for programmers who don’t want to overcomplicate their lives).

I almost forgot!! Apart from everything, it is also a free tool (o_O)

The purpose of this post is to teach you how to scrape a website and make a dataset and/or API in under 60 seconds. Are you ready?

It’s very simple. You just have to go to http://magic.import.io; post the URL of the site you want to scrape, and push the “GET DATA” button.
Yes! It is that simple! No plugins, downloads, previous knowledge or registration are necessary. You can do this from any browser; it even
works on tablets and smartphones.

For example: if we want to have a table with the information on all items related to Chewbacca on MercadoLibre (a Latin American version
of eBay), we just need to go to that site and make a search – then copy and paste the link (http://listado.mercadolibre.com.mx/chewbacca)
on Import.io, and push the “GET DATA” button.

You’ll notice that now you have all the information on a table, and all you need to do is remove the columns you don’t need. To do this, just
place the mouse pointer on top of the column you want to delete, and an “X” will appear.

Finally, it’s enough for you to click on “download” to get it in a csv file.
In our example, we have 373 pages with 48 articles each. So this option will be very useful for us.

Good news for those of us who are a bit more technically-oriented! There is a button that says “GET API” and this one is good to, well,
generate an API that will update the data on each request. For this you need to create an account (which is also free of cost).

As you saw, we can scrape any website in under 60 seconds, even if it includes tons of results pages. This truly is magic, no? For more
complex things that require logins, entering subwebs, automatized searches, et cetera, there is downloadable import.io software… But I’ll
explain that in a different post.

Source : http://schoolofdata.org/2014/12/09/web-scraping-in-under-60-seconds-the-magic-of-import-io/

Web Scraping Service Vs Web Scraping Tool – Choosing The Best

Web scraping is a rapidly emerging technique of extracting data from any web source with the intent to use it for analyzing the market trends. Different business owners adopt this method to enhance their sales and growth. They are open with different tools and services of extracting data from the internet.

Here, the major question that rises is- What is suitable between web scraping services and web scraping tools or software? The feasible answer is web scraping service as it offers comparatively more benefits that any software or tool.

Advantages of web scraping services

A thick of web scraping companies render custom-based support to the businesses in data extraction. Some of the major compelling benefits of preferring web scraping services may include:

    Lowered cost: You can conveniently save your thousands of money and man-power as these services are available at comparatively low prices.

    Accuracy in results: Unlike the data extraction software, these services render premium level of accuracy in terms of results. The leading companies of web services ensure that they deliver exact outcomes to you as per your need through their services.

    Instant outcomes: It only takes maximum time duration of 3 to 4 hours to generate valuable information about any database by acquiring the services of reputed web scraping company. You can avail the advantage of time over market on your competitors.

Drawbacks of using web scraping tools

    Using data extraction software accompanies certain drawbacks with it that may include:
    Difficulty in data extraction from multifaceted websites.
    Difficulty in extracting huge bulk of data.
    It is comparatively a slower process than a service provider.
    Several sites have well-defined policies for screen scraping.

Summary: While making a comparison between web scraping tools and services, you may arrive at the conclusion that the services are much more beneficial, reliable, and efficient than the major tools.
   
 Source : http://www.web-parsing.com/blog/web-scraping-services-vs-web-scraping-tools-choosing-the-best/

Data Extraction is not a Rocket Science: Follow These 4 Tips to Get Exemplary Results!

Data extraction is a skill, the more you master it – more are the chances of having a lucid picture of the volatile market and getting better perceptive of constantly changing trends. Escalating volatility in the market and intensifying competition has been the most contributing factors that have led to the rise of data extraction and data mining.

Data extraction is primarily used by companies (large and small, alike) to collect data from a specific industry, or data related to targeted customers or about their competition in the market. In fact, it has become a primary tool for marketers to plan their moves for branding and promoting particular products or services. It helps a wide plethora of industrial sectors to find and learn about specific data, based on their requirements.

And now with the rise of internet, web scraping has emerged as an important aspect that contributes to your success – the success of your venture or organization. It processes the HTML of a Web page to obtain data and convert it into to another format (i.e. HTML to XML).

Various extraction tools form an integral part of data extraction and data scrapping. Following offers a brief outline of some of these tools:

Email Extraction – An email extractor tool is used to acquire the email ids from any dependable sources automatically

Screen Scrapping – Screen scraping is a practice of reading text information from a screen and collecting visual data, rather than analyzing data as done in web scraping.

Data Mining as name suggests is a process of gathering patterns from information. It basically transforms the information into formats like CSV, MS excels, HTML and so and so forth, depending to your requirements. Web Spider – A Web spider is a computer program which browses internet in a systematic, automated manner. It is used by many search engines in order to provide up-to-date data.

It is often seen that while extracting data; many get lost into the labyrinth of confusion, data overabundance, along with a lot of weird and not-so-familiar terms. Proper handling of these may sound easy, however; when not executed with appropriate procedure and processes; it may bring in disastrous results.

This no way means that data mining is a rocket science which only a few gifted and skilled people can take up. All it requires is undivided attention, keen preparation, and training, so brace up yourself for an overview of some practical tips that can help in successful data extraction and give a boost to your business.

Identify your Business Goals!:

Get a clear perspective in mind as to what are your business goals.

Data extraction can be bifurcated into various branches; and one needs to choose it wisely, depending on the business goals. E.g. your primary requirement is to get email ids of potential clients to conduct an email campaign; and for that you certainly need an email extractor. Use of this tool assists in extracting the email ids from trustworthy sources automatically. It essentially collects business contacts from various web pages, text files, HTML files, or any other format without duplicating the email ids. So, if you are not sure what you want; even applying the best tools will be of no use!

A crystal clear mindset helps in better understanding of market scenario and thus helps in formulation of powerful and effective strategies to get desired outcomes. E.g., people dealing in real estate business, should have a vision for it and which area they want to target specifically. With a clear vision they can clearly spell out what you want and where it should be.

Set Realistic Expectations:

Upon identifying your business goals, make sure to check out that they are realistic and attainable! Unrealistic and unachievable targets are the real cause for the obstacles and frustrations in the future.

Since, there are various tools that are and can be employed to extract data; vague or unclear goals make it difficult to determine which tool can be applied.

This crystal clear mindset; will help you give that insight about the direction your business is headed to.

Moreover, you can determine which method can be used to get excellent results. You can get a lucid picture of the past and present of your competitors and therefore helps in setting targets based on the others’ experiences. It is usually a wise move to set expectations that you have not achieved before.

Appoint Skilled Data Miner:

Skilled data miner with excellent data mining skills will reduce the painstaking and tiresome process of planning, devising and preparation.

For fresh start-ups, you can go ahead with the standard procedure however; if you have ample professionals at your disposal, pick up the right one who is not only knowledgeable but also reliable and sincere towards the task.

Prevent Data Deposits:

Being dead-sure of what you really want will help you avoid unnecessary data deposition.

Data mining just like real mining is a skill to know where the real treasure lies and being able to get it in the most efficient and effective way.

Being able to spot on authenticated & reliable resources, well researched information is what gives a short cut to locate the right and exact data.

If you are aimlessly opening every website; the results are bound to be ambiguous and would ultimately be a waste of time and effort.

Source : http://www.habiledata.com/blog/data-extraction-is-not-a-rocket-science-follow-these-4-tips-to-get-exemplary-results