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 to scrape search results from search engines like Google, Bing and Yahoo

How to scrape search results from search engines like Google, Bing and Yahoo

Search giants like Google, Yahoo and Bing made their empire on scraping others content. However, they don’t want you to scrape them. How ironic, isn’t it?

Search engine performance is a very important metric all digital marketers want to measure and improve. I’m sure you will be using some great SEO tools to check how your keywords perform. All great SEO tool comes with a search keyword ranking feature. The tools will tell you how your keywords are performing in google, yahoo bing etc.

 How will you get data from search engines If you want to build a keyword ranking app?

 These search engines have API’s but the daily query limit is very low and not useful for the commercial purpose. The only solution is to scrape search results. Search engine giants obviously know this :). Once they know that you are scraping, they will  block your IP, Period!

 How do Search engines detect bots?

 Here are the common methods of detection of bots.

* IP address: Search engines can detect if there are too many requests coming from a single IP. If a high amount of traffic is detected, they will throw a captcha.

 * Search patterns: Search engines match traffic patterns to an existing set of patterns and if there is huge variation, they will classify this as a bot.

 If you don’t have access to sophisticated technology, it is impossible to scrape search engines like google, Bing or Yahoo.

 How to avoid detection

There are some things you can do to  avoid detection.

    Scrape slowly and don’t try to squeeze everything at once.
    Switch user agents between queries
    Scrape randomly and don’t follow the same pattern
    Use intelligent IP rotations
    Clear Cookies after each IP change or disable them completely

Thanks for reading this blog post.

Source: http://blog.datahut.co/how-to-scrape-search-results-from-search-engines-like-google-bing-and-yahoo/

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

Web Scraping with Python: A Beginner’s Guide

Web Scraping with Python: A Beginner’s Guide

In the Big Data world, Web Scraping or Data extraction services are the primary requisites for Big Data Analytics. Pulling up data from the web has become almost inevitable for companies to stay in business. Next question that comes up is how to go about web scraping as a beginner.

Data can be extracted or scraped from a web source using a number of methods. Popular websites like Google, Facebook, or Twitter offer APIs to view and extract the available data in a structured manner.  This prevents the use of other methods that may not be preferred by the API provider. However, the demand to scrape a website arises when the information is not readily offered by the website. Python, an open source programming language is often used for Web Scraping due to its simple and rich ecosystem. It contains a library called “BeautifulSoup” which carries on this task. Let’s take a deeper look into web scraping using python.

Setting up a Python Environment:

To carry out web scraping using Python, you will first have to install the Python Environment, which enables to run code written in the python language. The libraries perform data scraping;

Beautiful Soup is a convenient-to-use python library. It is one of the finest tools for extracting information from a webpage. Professionals can scrape information from web pages in the form of tables, lists, or paragraphs. Urllib2 is another library that can be used in combination with the BeautifulSoup library for fetching the web pages. Filters can be added to extract specific information from web pages. Urllib2 is a Python module that can fetch URLs.

For MAC OSX :

To install Python libraries on MAC OSX, users need to open a terminal win and type in the following commands, single command at a time:

sudoeasy_install pip

pip install BeautifulSoup4

pip install lxml

For Windows 7 & 8 users:

Windows 7 & 8 users need to ensure that the python environment gets installed first. Once, the environment is installed, open the command prompt and find the way to root C:/ directory and type in the following commands:

easy_install BeautifulSoup4

easy_installlxml

Once the libraries are installed, it is time to write data scraping code.

Running Python:

Data scraping must be done for a distinct objective such as to scrape current stock of a retail store. First, a web browser is required to navigate the website that contains this data. After identifying the table, right click anywhere on it and then select inspect element from the dropdown menu list. This will cause a window to pop-up on the bottom or side of your screen displaying the website’s html code. The rankings appear in a table. You might need to scan through the HTML data until you find the line of code that highlights the table on the webpage.

Python offers some other alternatives for HTML scraping apart from BeautifulSoup. They include:

    Scrapy
    Scrapemark
    Mechanize

 Web scraping converts unstructured data from HTML code into structured form such as tabular data in an Excel worksheet. Web scraping can be done in many ways ranging from the use of Google Docs to programming languages. For people who do not have any programming knowledge or technical competencies, it is possible to acquire web data by using web scraping services that provide ready to use data from websites of your preference.

HTML Tags:

To perform web scraping, users must have a sound knowledge of HTML tags. It might help a lot to know that HTML links are defined using anchor tag i.e. <a> tag, “<a href=“http://…”>The link needs to be here </a>”. An HTML list comprises <ul> (unordered) and <ol> (ordered) list. The item of list starts with <li>.

HTML tables are defined with<Table>, row as <tr> and columns are divided into data as <td>;

    <!DOCTYPE html> : A HTML document starts with a document type declaration
    The main part of the HTML document in unformatted, plain text is defined by <body> and </body> tags
    The headings in HTML are defined using the heading tags from <h1> to <h5>
    Paragraphs are defined with the <p> tag in HTML
    An entire HTML document is contained between <html> and </html>

Using BeautifulSoup in Scraping:

While scraping a webpage using BeautifulSoup, the main concern is to identify the final objective. For instance, if you would like to extract a list from webpage, a step wise approach is required:

    First and foremost step is to import the required libraries:

 #import the library used to query a website

import urllib2

#specify the url wiki = “https://”

#Query the website and return the html to the variable ‘page’

page = urllib2.urlopen(wiki)

#import the Beautiful soup functions to parse the data returned from the website

from bs4 import BeautifulSoup

#Parse the html in the ‘page’ variable, and store it in Beautiful Soup format

soup = BeautifulSoup(page)

    Use function “prettify” to visualize nested structure of HTML page
    Working with Soup tags:

Soup<tag> is used for returning content between opening and closing tag including tag.

    In[30]:soup.title

 Out[30]:<title>List of Presidents in India till 2010 – Wikipedia, the free encyclopedia</title>

    soup.<tag>.string: Return string within given tag
    In [38]:soup.title.string
    Out[38]:u ‘List of Presidents in India and Brazil till 2010 in India – Wikipedia, the free encyclopedia’
    Find all the links within page’s <a> tags: Tag a link using tag “<a>”. So, go with option soup.a and it should return the links available in the web page. Let’s do it.
    In [40]:soup.a

Out[40]:<a id=”top”></a>

    Find the right table:

As a table to pull up information about Presidents in India and Brazil till 2010 is being searched for, identifying the right table first is important. Here’s a command to scrape information enclosed in all table tags.

all_tables= soup.find_all(‘table’)

Identify the right table by using attribute “class” of table needs to filter the right table. Thereafter, inspect the class name by right clicking on the required table of web page as follows:

    Inspect element
    Copy the class name or find the class name of right table from the last command’s output.

 right_table=soup.find(‘table’, class_=’wikitable sortable plainrowheaders’)

right_table

That’s how we can identify the right table.

    Extract the information to DataFrame: There is a need to iterate through each row (tr) and then assign each element of tr (td) to a variable and add it to a list. Let’s analyse the Table’s HTML structure of the table. (extract information for table heading <th>)

To access value of each element, there is a need to use “find(text=True)” option with each element.  Finally, there is data in dataframe.

There are various other ways to scrape data using “BeautifulSoup” that reduce manual efforts to collect data from web pages. Code written in BeautifulSoup is considered to be more robust than the regular expressions. The web scraping method we discussed use “BeautifulSoup” and “urllib2” libraries in Python. That was a brief beginner’s guide to start using Python for web scraping.

Source: https://www.promptcloud.com/blog/web-scraping-python-guide

Powerful Web Scraping Software – Content Grabber Review

Powerful Web Scraping Software – Content Grabber Review

There are many web scraping software and cloud based web scraping services available in the market for extracting data from the websites. They vary widely in cost and features. In this article, I am going to introduce one such advanced web scraping tool “Content Grabber”, which is widely used and the best web scraping software in the market.

Content Grabber is used for web extraction, web scraping and web automation. It can extract content from complex websites and export it as structured data in a variety of formats like Excel Spreadsheets, XML, CSV and databases. Content Grabber can also extract data from highly dynamic websites. It can extract from AJAX-enabled websites, submit forms repeatedly to cover all possible input values, and manage website logins.

Content Grabber is designed to be reliable, scalable and customizable. It is specifically designed for users with a critical reliance on web scraping and web data extraction. It also enables you to make standalone web scraping agents which you can market and sell as your own royalty free web scraping software.

Applications of Content Grabber:

The following are the few applications of Content Grabber:

•     Data aggregation – for example news aggregation.
•     Competitive pricing and monitoring e.g. monitor dealers for price compliance.
•     Financial and Market Research e.g. Make proactive buying and selling decisions by continuously receiving corporate operational data.
•     Content Integration i.e. integration of data from various sources at one place.
•     Business Directory Scraping – for example: yellow pages scraping, yelp scraping, superpages scraping etc.
•     Extracting company data from yellow pages for scraping common data fields like Business Name, Address, Telephone, Fax, Email, Website and Category of Business.
•     Extracting eBay auction data like: eBay Product Name, Store Information, Buy it Now prices, Product Price, List Price, Seller Price and many more.
•     Extracting Amazon product data: Information such as Product title, cost, description, details, availability, shipping info, ASIN, rating, rank, etc can be extracted.

Content Grabber Features:

The following section highlights some of the key features of Content Grabber:

1. Point and Click Interface

The Content Grabber editor has an easy to use point and click interface that provides easy point and click configuration. One simply needs to click on web elements to configure website navigation and content capture.

2. Easy to Use

The Content Grabber point and click interface is so simple to use that it can easily be used by beginners and non-programmers. There is certain built in facilities that automatically detect and configure all commands. It will automatically create a list of links, lists of content, manage pagination, handle web pages, download or upload files and capture any action you perform on a web page. You can also manually configure the agent commands, so Content Grabber gives you both simplicity and control.

3. Reliable and Scalable

Content Grabber’s powerful features like testing and debugging, solid error handling and error recovery, allows agent to run in the most difficult scenarios. It easily handles and scrapes dynamic websites built with JavaScript and AJAX. Content Grabber’s Intelligent agents don’t break with most site structure changes. These features enable us to build reliable web scraping agents. There are various configurations and performance tuning options that makes Content Grabber scalable. You can build as many web scraping agents as you want with Content Grabber.

4. High Performance

Multi-threading is used to increase the performance in Content Grabber. Content Grabber uses optimized web browsers. It uses static browsers for static web pages and dynamic browsers for dynamic web pages. It has an ultra-fast HTML5 parser for ultra-fast web scraping. One can use many web browsers concurrently to boost performance.

5. Debugging, Logging and Error Handling

Content Grabber has robust support for debugging, error handling and logging. Using a debugger, you can test and debug the web scraping agents which helps you to build reliable and error free web scraping solutions because most of the issues are addressed at design time. Content Grabber allows agent logging with three detail levels: Log URLs, Log raw HTML, Log to database or file. Logs can be useful to identify problems that occurred during execution of a web scraping agent. Content Grabber supports automatic error handling and custom error handling through scripting. Error status reports can also be mailed to administrators.

6. Scripting

Content Grabber comes with a built in script editor with IntelliSense that one can use in case of some unusual requirements or to fine tune some process. Scripting can be used to control agent behaviour, content transformation, customize data export and delivery and to generate data inputs for agent.

7. Unlimited Web Scraping Agents

Content Grabber allows building an unlimited number of Self-Contained Web Scraping Agents. Self-Contained agents are a standalone executable that can be run independently, branded as your own and distributed royalty free. Content Grabber provides an easy to use and effective GUI to manage all the agents. One can view status and logs of all the agents or run and schedule the agents in one centralized location.

8. Automation

Require data on a schedule? Weekly? Everyday? Each hour? Content Grabber allows automating and publishing extracted data. Configure Content Grabber by telling what data you want once, and then schedule it to run automatically.

And much more

There are too many features that Content Grabber provides, but here are a few more that may be useful and interest you.

•     Schedule agents
•     Manage proxies
•     Custom notification criteria and messages
•     Email notifications
•     Handle websites logins
•     Capture Screenshots of web elements or entire web page or save as PDF.
•     Capture hidden content on web page.
•     Crawl entire website
•     Input data from almost any data source.
•     Auto scroll to load dynamic data
•     Handle complex JAVASCRIPT and AJAX actions
•     XPATH support
•     Convert Images to Text
•     CAPTCHA handling
•     Extract data from non-HTML documents like PDF and Word Documents
•     Multi-threading and multiple web browsers
•     Run agent from command line.

The above features come with the Professional edition license. Content Grabber’s Premium edition license is available with the following extra features:

1. Visual Studio 2013 integration

One can integrate Content Grabber to Visual Studio and take advantages of extra powerful script editing, debugging, and unit testing.

2. Remove Content Grabber branding

One can remove Content Grabber branding from the Content Grabber agents and distribute the executable.

3. Custom Design Templates

One can customize the Content Grabber agent user interface design with custom HTML templates – e.g. add your own company branding.

4. Royalty free distribution

One can distribute the Content Grabber agent to anybody without paying royalty fees and can run agents from the command line anywhere.

5. Programming Interface

Programming interfaces like Desktop API, Web API and windows service for building and editing agents.

6. Custom Web Scraping Application Development:

Content Grabber provides API and Visual Studio Integration which developer can use to build custom web scraping applications. It provides full control of the user interface and export functionality. One can develop both Desktop as well as Web based custom web scraping applications using the Content Grabber programming interface. It is a great tool and provides opportunity for developers to build general web scraping applications and sell those to generate revenue.

Are you looking for web scraping services? Do you need any assistance related to Content Grabber? We can probably help you to achieve your scraping-based project goals. We would be more than happy to hear from you.

Source: http://webdata-scraping.com/powerful-web-scraping-software-content-grabber/

Calculate your ROI on Web Scraping using our ROI Calculator

Calculate your ROI on Web Scraping using our ROI Calculator

Staying atop the competition is a vital thing for the survival and growth of businesses these days. Ever since big data came into the picture, web scraping has become something businesses from every industry has to invest in. If your company is not in a technically advanced industry, web scraping could even be a nightmare to start with. Wondering if going with in-house web scraping is right for you? In house or outsourcing, in the end it’s all about the returns on investment.

ROI Calculator

Considering the numerous factors that determine how much web scraping can cost you, it’s not easy to calculate the ROI on your in-house web scraping.

In house web scraping is certainly a challenging process. If you plan on going down this way, here is a brief list of prerequisites.

Engineers

Technically skilled labour is an essential requirement for web scraping. Since, web scraping techniques are complicated, it needs good programming skills to write, run and maintain the scraping bots. The cost of labour can be one of the drawbacks with doing in house web scraping.

Hardware Resources

Web scraping is a resource hungry process which requires high end servers and lots of bandwidth. Without the adequate resources, you might end up losing important data. The cost of quality servers could easily make you want to reconsider doing web scraping on your own. Not to mention the doubling up of these resources in order to keep the data intact, espcially if you’re looking at large scale.

Maintainability and ukeep of your tech stack

Once you have your servers and other technical components setup, the real deal only starts. You have to ensure availability of your servers, data backups, restoring previous states, failovers, among many other complications associated with managing servers and fixing them up when something goes wrong. You need to allocate resources (both people and hardware) to take care of the above.

Time

Time is something that we cannot really include in the equation when it comes to calculating the returns. But it is definitely a factor that defines if web scraping in house is worth it. Although web scraping is the fastest way to acquire data, the initial setup and maintenance are time consuming and complicated. This could easily lead to conflicts when you have to distribute your time between web scraping and other business activities that are crucial for your company.

Try the ROI Calculator

We came up with an ROI calculator to easily calculate your returns on investment with our web scraping services. Using this, you could easily compare the cost of in house web scraping with PromptCloud’s dedicated web scraping services. Find out how much you can save by going the PromptCloud way.

Source: https://www.promptcloud.com/blog/calculate-roi-on-web-scraping

How Web Scraping can Help you Detect Weak spots in your Business

How Web Scraping can Help you Detect Weak spots in your Business

Business intelligence is not a new term. Businesses have always been employing experts for analysing the progress, market and industry trends to keep their growth graph going up. Now that we have big data and the tool to gather this data – Web scraping, business intelligence has become even more fruitful. In fact, business intelligence has become a necessary thing to survive now that the competition is fierce in every industry. This is the reason why most enterprises depend on web scraping solutions to gather the data relevant to their businesses. This data is highly insightful and dependable enough to make critical business decisions. Business intelligence from web scraping is definitely a game changer for companies as it can supply relevant and actionable data with minimal effort.

Most businesses have weak spots that are being overlooked or hidden from the plain sight. These weak spots, if left unnoticed can gradually result in the downfall of your company. Here is how you can use data acquired through web scraping to detect weak spots in your business and strengthen them.

Competitor analysis

Many a times, you can find out the flaws in your business by keeping a close watch on your competitors. Competitor analysis is something that we owe to web scraping as the level of competitive intelligence that you can derive from web scraping has never been achievable in the past. With crawling forums and social media sites where your target audience is, you can easily find out if your competitor is leveraging something you have overlooked. Competitor analysis is all about staying updated to each and every action by your competitors, so that you can always be prepared for their next strategic move. If your competitors are doing better than you, this data can be used to make a comparison between your business and theirs which would give you insights on where you lack.

Brand monitoring on Social media

With social media platforms acting like platforms where businesses and customers can interact with each other, the data available on these sites are increasingly becoming relevant to businesses. Any issues in your business operations will also reflect on your customer sentiments. Social media is a goldmine of sentiment data that can help you detect issues within your company. By analysing the posts that mention your brand or product on social media sites, you can identify what department of your company is functioning well and what isn’t.

For example, if you are an Ecommerce portal and many users are complaining about delivery issues from your company on social media, you might want to switch to a better logistics partner who does a better job. The ability to identify such issues at the earliest is extremely important and that’s where web scraping becomes a life saver. With social media scraping, monitoring your brand on social media is easy like never before and the chances of minor issues escalating to bigger ones is almost non-existent. Brand monitoring is extremely crucial if you are a business operating in the online space. Social media scraping solutions are provided by many leading web scraping companies, which totally eliminates the technical complications associated with the process for you.

Finding untapped opportunities

There are always new and untapped markets and opportunities that are relevant to your business. Finding them is not going to be an easy task with manual and outdated methods of research. Web scraping can fill this gap and help you find opportunities that your company can make use of to leverage your reach and progress. Sometimes, targeting the right audience makes all the difference that you’ve been trying to make. By using web crawling to find mentions of your relevant keywords on the web, you can easily stay updated on your niche and fill in to any new untapped markets. Web crawling for keywords is better explained in our previous blog.

Bottom line

It is not a cakewalk to stay ahead in the competition considering how competitive every industry has become in this digital age. It is crucial to find the weak spots and untapped opportunities of your business before someone else does. Of course, you can always use some help from the technology when you need it. Web scraping is clearly the best way to find and gather data that would help you figure these out. With web crawling solutions that can completely take care of this niche process, nothing is stopping you from using the data and insights that the web has in stock for your business.

Source: https://www.promptcloud.com/blog/web-scraping-detect-weak-spots-business

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

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/

Data Discovery vs. Data Extraction

Data Discovery vs. Data Extraction

Looking at screen-scraping at a simplified level, there are two primary stages involved: data discovery and data extraction. Data discovery deals with navigating a web site to arrive at the pages containing the data you want, and data extraction deals with actually pulling that data off of those pages. Generally when people think of screen-scraping they focus on the data extraction portion of the process, but my experience has been that data discovery is often the more difficult of the two.

The data discovery step in screen-scraping might be as simple as requesting a single URL. For example, you might just need to go to the home page of a site and extract out the latest news headlines. On the other side of the spectrum, data discovery may involve logging in to a web site, traversing a series of pages in order to get needed cookies, submitting a POST request on a search form, traversing through search results pages, and finally following all of the "details" links within the search results pages to get to the data you're actually after. In cases of the former a simple Perl script would often work just fine. For anything much more complex than that, though, a commercial screen-scraping tool can be an incredible time-saver. Especially for sites that require logging in, writing code to handle screen-scraping can be a nightmare when it comes to dealing with cookies and such.

In the data extraction phase you've already arrived at the page containing the data you're interested in, and you now need to pull it out of the HTML. Traditionally this has typically involved creating a series of regular expressions that match the pieces of the page you want (e.g., URL's and link titles). Regular expressions can be a bit complex to deal with, so most screen-scraping applications will hide these details from you, even though they may use regular expressions behind the scenes.

As an addendum, I should probably mention a third phase that is often ignored, and that is, what do you do with the data once you've extracted it? Common examples include writing the data to a CSV or XML file, or saving it to a database. In the case of a live web site you might even scrape the information and display it in the user's web browser in real-time. When shopping around for a screen-scraping tool you should make sure that it gives you the flexibility you need to work with the data once it's been extracted.

Source: http://ezinearticles.com/?Data-Discovery-vs.-Data-Extraction&id=165396