Data Mining - Retrieving Information From Data

Data Mining - Retrieving Information From Data

Data mining definition is the process of retrieving information from data. It has become very important now days because data that is processed is usually kept for future reference and mainly for security purposes in a company. Data transforms is processed into information and it is mostly used in different ways depending on what information one is extracting and from where the person is extracting the information.

It is commonly used in marketing, scientific information and research work, fraud detection and surveillance and many more and most of this work is done using a computer. This definition can come in different terms data snooping, data fishing and data dredging all this refer to data mining but it depends in which department one is. One must know data mining definition so that he can be in a position to make data.

The method of data mining has been there for so many centuries and it is used up to date. There were early methods which were used to identify data mining there are mainly two: regression analysis and bayes theorem. These methods are never used now days because a lot of people have advanced and technology has really changed the entire system.

With the coming up or with the introduction of computers and technology, it becomes very fast and easy to save information. Computers have made work easier and one can be able to expand more knowledge about data crawling and learn on how data is stored and processed through computer science.

Computer science is a course that sharpens one skill and expands more about data crawling and the definition of what data mining means. By studying computer science one can be in a position to know: clustering, support vector machines and decision trees there are some of the units that are found on computer science.

It's all about all this and this knowledge must be applied here. Government institutions, small scale business and supermarkets use data.

The main reason most companies use data mining is because data assist in the collection of information and observations that a company goes through in their daily activity. Such information is very vital in any companies profile and needs to be checked and updated for future reference just in case something happens.

Businesses which use data crawling focus mainly on return of investments, and they are able to know whether they are making a profit or a loss within a very short period. If the company or the business is making a profit they can be in a position to give customers an offer on the product in which they are selling so that the business can be a position to make more profit in an organization, this is very vital in human resource departments it helps in identifying the character traits of a person in terms of job performance.

Most people who use this method believe that is ethically neutral. The way it is being used nowadays raises a lot of questions about security and privacy of its members. Data mining needs good data preparation which can be in a position to uncover different types of information especially those that require privacy.

A very common way in this occurs is through data aggregation.

Data aggregation is when information is retrieved from different sources and is usually put together so that one can be in a position to be analyze one by one and this helps information to be very secure. So if one is collecting data it is vital for one to know the following:

    How will one use the data that he is collecting?
    Who will mine the data and use the data.
    Is the data very secure when am out can someone come and access it.
    How can one update the data when information is needed
    If the computer crashes do I have any backup somewhere.

It is important for one to be very careful with documents which deal with company's personal information so that information cannot easily be manipulated.

source : http://ezinearticles.com/?Data-Mining---Retrieving-Information-From-Data&id=5054887

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

Collecting Data With Web Scrapers

Collecting Data With Web Scrapers

There is a large amount of data available only through websites. However, as many people have found out, trying to copy data into a usable database or spreadsheet directly out of a website can be a tiring process. Data entry from internet sources can quickly become cost prohibitive as the required hours add up. Clearly, an automated method for collating information from HTML-based sites can offer huge management cost savings.

Web scrapers are programs that are able to aggregate information from the internet. They are capable of navigating the web, assessing the contents of a site, and then pulling data points and placing them into a structured, working database or spreadsheet. Many companies and services will use programs to web scrape, such as comparing prices, performing online research, or tracking changes to online content.

Let's take a look at how web scrapers can aid data collection and management for a variety of purposes.

Improving On Manual Entry Methods

Using a computer's copy and paste function or simply typing text from a site is extremely inefficient and costly. Web scrapers are able to navigate through a series of websites, make decisions on what is important data, and then copy the info into a structured database, spreadsheet, or other program. Software packages include the ability to record macros by having a user perform a routine once and then have the computer remember and automate those actions. Every user can effectively act as their own programmer to expand the capabilities to process websites. These applications can also interface with databases in order to automatically manage information as it is pulled from a website.

Aggregating Information

There are a number of instances where material stored in websites can be manipulated and stored. For example, a clothing company that is looking to bring their line of apparel to retailers can go online for the contact information of retailers in their area and then present that information to sales personnel to generate leads. Many businesses can perform market research on prices and product availability by analyzing online catalogues.

Data Management

Managing figures and numbers is best done through spreadsheets and databases; however, information on a website formatted with HTML is not readily accessible for such purposes. While websites are excellent for displaying facts and figures, they fall short when they need to be analyzed, sorted, or otherwise manipulated. Ultimately, web scrapers are able to take the output that is intended for display to a person and change it to numbers that can be used by a computer. Furthermore, by automating this process with software applications and macros, entry costs are severely reduced.

This type of data management is also effective at merging different information sources. If a company were to purchase research or statistical information, it could be scraped in order to format the information into a database. This is also highly effective at taking a legacy system's contents and incorporating them into today's systems.

Overall, a web scraper is a cost effective user tool for data manipulation and management.

source: http://ezinearticles.com/?Collecting-Data-With-Web-Scrapers&id=4223877

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

Scrape amazon and price your product the right way – A use case

Scrape amazon and price your product the right way – A use case

So you built a product that you want to sell through Amazon.

How do you price your product? 

Amazon is the world’s largest online retailer. Millions of products are sold through amazon.  a lot of people make their living selling through Amazon. One of the biggest mistake people do in Amazon is that they price their product the wrong way. Sometimes they sell overpriced products, sometimes they sell the underpriced product. Both situations are toxic for the business.

We recently worked with a company that helps small businesses sell the products efficiently through amazon and other marketplaces. One of the key things they are doing is helping people with pricing their product the right way.

What I learned from them is that price is a relative term and a lot of people does not understand it. Pricing is a function of the positioning of  your product in the market.

We need to collect the data using  a technique called web scraping to understand how to position the product. You can get the  data in a CSV file which can be used for analysis.

1) What is the average price of a comparable product?

Understanding the pricing  strategy of your competitors products  is the first step in solving the problem. This can give you a range in which you can price your product. You can get the pricing data by scraping amazon

2) Is this a premium product?

People always pay a premium price for a premium product. What makes a product premium? – A product is considered premium only when the customer believe it is worth the price. Excellent marketing and branding are the ways to position your product as a premium product. You can get the relevant data by scraping amazon.

3) What are the problems with your competitor products?

Your competitor products might be having some defects. Or they might not be addressing a relevant problem. You have every chance of success If you are solving a problem that your competitor doesn’t. You can find these problems by analyzing the product reviews of your competitors. You can get review data by scraping amazon.

By analyzing data you can reach at a point where your profit margin looks healthy and pricing looks sensible. Buyers buy the value, not your product. Differentiate your product and position it as a superior product. Give people a reason to buy and that is the only way to succeed.

Source: http://blog.datahut.co/scrape-amazon-and-price-your-product-the-right-way-a-use-case/

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

How Web Scraping Affects your Revenue Growth

How Web Scraping Affects your Revenue Growth

Web scraping is an indispensable resource when it comes to gaining an edge in the competition with the help of business intelligence. As more and more data gets created on the world wide web, the complexity of extracting it intensifies. Web scraping is a technology that demands an extensive tech stack, high end resources and technically skilled labour. Given this resource hungry nature, many businesses prefer outsourcing it to doing the scraping in-house. Here is a brief walk-through of web scraping so that you can get a grip on the whole process and understand how it could affect your revenue growth as a business.

Business intelligence

The competition among online businesses is at its peak. This has more to do with the ready availability of insightful data. When data acquisition at this scale wasn’t possible in the past, businesses made hit-or-miss decisions upon instincts. Now that every activity can be recorded, extracted as data and analysed to arrive at the best business decisions, companies are making the most of it to boost their revenue. This includes monitoring the activity of competitors on social media, price intelligence, sentiment analysis, gathering data for market research and much more. The use cases of web scraping in business is almost infinite. Business intelligence is extremely helpful for the survival of companies in a market that fluctuates often. Implementing a business intelligence strategy powered by web scraping can definitely give a boost to your revenue growth.
Cost centres involved in in-house Web Scraping

Web scraping, despite being a robust solution for extracting data from the web, is not going to be an easy path if your company is not technically rich already. It involves setting up resources like a tech stack and servers that can run the web crawler by a technically skilled team. Following are the primary cost centres involved in the web scraping process.

1. High end servers

Web scraping is a resource intensive process. Considering the importance of uptime here, the crawlers cannot be run on average performance machines. To have the optimum uptime and avoid crashes, the crawler has to be run on high performing servers located in different parts of the world. The quality of servers is crucial to the consistency of the process. Not to mention, these high end servers makeup for a significant amount of the cost involved in web scraping.

2. Technically skilled labour

Scanning through the source code to identify appropriate tags that hold the required data points and creating a program that can automatically fetch these data points from similar pages’ at large scale requires deep programming skills. It goes without saying that employing skilled people would incur cost that could take a hit on your revenue. Ideally, you will need a team of at least 10 to run a web scraping setup in-house.       

3. An extensive tech stack

Although most of the software being used for web scraping are open source, you will find yourself investing in paid software to make certain things easier or faster. Dealing with open source software might not be as user friendly as the paid ones. In any case, having a tech stack with a lot of options is a necessary aspect of web scraping that would incur additional cost.   

4. Maintenance

Building and running the web scraping setup is only half of the story. Since websites undergo changes often, there is a possibility of the crawler setup breaking from time to time. To avoid or solve this at the earliest, a monitoring system that involves both machines and humans is necessary. Monitoring and maintenance contribute to a considerable cost in the web scraping process.
Data as a service

If data for business is your requirement, a better way to acquire it would be to depend on a company that can deliver it via the data as a service route. Web scraping companies have already set up high-end resources required to run the web crawlers that you can utilize to avail web scraping at a much lower cost than what you would incur by doing it on your own. With this, you can also save yourself from the complications and maintenance headache associated with web scraping. Moreover, with a web scraping service, you can enjoy a much higher return on investment owing to the lowered cost of data acquisition. You can use our ROI calculator to compare between the cost of going with an in-house web scraping setup and a hosted solution.

Source: https://www.promptcloud.com/blog/web-scraping-affects-revenue-growth

How to do data scraping from PDF files using PHP?

How to do data scraping from PDF files using PHP?

Situations arise when you want to scrap data from PDF or want to search PDF files for matching text. Suppose you have website where users uploads PDF files and you want to give search functionality to user which searches all uploaded PDF file content for matching text and show all PDFs that contains matching search keywords.

Or you might have all London real estate properties details in PDF report file and you want to quickly grab scrape data from PDF reports then you might need PDF scraping library.

To integrate such functionality to web application is not similar to normal search functionality that we do with database search.

Here is the straight solution for this problem. This involves PDF Data Scraping to plain text and match search terms. I have written this post for the people who want to do PDF data scraping or want to make their PDF files to be Searchable.

We are going to use class named class.pdf2text.php which converts PDF text to into ASCII text, so the class is known for PDF extraction. This PHP class ignores anything in PDF that is not a text.

Let’s see very basic example (Taken from author’s file):

<?php

include "class.pdf2text.php";

$a = new PDF2Text();
$a->setFilename('web-scraping-service.pdf'); //grab the pdf file reside in folder where PHP files resides.

$a->decodePDF();//converts PDF content to text
echo $a->output();

?>

“Web Scraping is a technique using which programmer can automate the copy paste manual work and save the time. This is PDF w eb scraping using PHP. We at Web Data Scraping offer Web Scraping and Data Scraping Service. Vist our website www.webdata-scraping.com”

For more complex extraction you can apply regular expression on the text you get and can parse text that you want from PDF. But keep in mind this has limitation and do not work with all types of PDF extraction.

But the wonderful use of this class is to make utility that allow user to search inside PDF when they search on web search bar. Last but not least, You can also find many PDF scraping software available in market that can do complex scraping from PDF files.

Source: http://webdata-scraping.com/data-scraping-pdf-files-using-php/

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

How to use Social Media Scraping to be your Competitors’ Nightmare

How to use Social Media Scraping to be your Competitors’ Nightmare

Big data and competitive intelligence have been in the limelight for quite some time now. The almost magical power of big data to help a company make just the right decisions have been talked about a lot. When it comes to big data, the kind of benefits that a business can get totally depends upon the sources they acquire it from. Social media is one of the best sources from where you can get data that helps your business in a multitude of ways. Now that every business is deep rooted on the internet, social media data becomes all the more relevant and crucial. Here is how you can use data scraped from social media sites to get an edge in the competition.

Keeping watch on your competitors

Social media is the best place to watch your competitors’ activity and take counter initiatives to keep up or take over them. If you want to know what your competitors are up to, a social media scraping setup for scraping the posts that mention your competitors’ brand/product names can do the trick. This can also be used to learn a thing or two from their activities on social media so that you can take respective measures to stay ahead of them. For example, you could know if your competitor is running a special promotional offer at the moment and come up with something better than theirs to keep up. This can do wonders if you are in a highly competitive industry like Ecommerce where the competition is intense. If you are not using some help from web scraping technology to keep a close watch on your competitors, you could easily get left over in this fast-paced business scene.

Solving customer issues at the earliest

Customers are vocal about their experience with different products and services on social media sites these days. If you have a customer whose issue was left unsolved, there is a good chance that he/she will take it to the social media to vent the frustration. Watching out for such instances and giving them prompt support should be something you should do if you want to retain these customers and stop them from ruining your brand’s image. By scraping social media sites for posts that mention your product/service, you can easily find out if there are such grievances from customers. This can make sure to an extent that you don’t let unhappy customers stay that way, which eventually hurts your business in the long run. Customers can make or break your company, so using social media scraping to serve the customers better can help you succeed eventually.

Sentiment analysis

Social media data can play a good job at helping you understand user sentiments. With the help of social media scraping, a business can get the big picture about general perception of their brand by their users. This can go a long way since this level of feedback can help you fix unnoticed issues with your company and service quickly. By rectifying them, you can make your brand more appealing to the customers. Sentiment analysis will provide you with the opportunity to transform your business into how customers want it to be. Social media scraping is the one and only way to have access to this user sentiment data which can help you optimize your business for the customers.

Web crawling for social media data

When social media data possess so much value to businesses, it makes sense to look for efficient ways to gather and use this data. Manually scrolling through millions of tweets doesn’t make sense, this is why you should use social media scraping to aggregate the relevant data for your business. Besides, web scraping technologies make it possible to handle huge amounts of data with ease. Since the size of data is huge when it comes to business related requirements, web scraping is the only scalable solution worth considering. To make things even simpler, there are reliable web scraping solutions that offer social media scraping services for brand monitoring.

Bottom line

Since social media has become an integral part of online businesses, the data available on these sites possess immense value to companies in every industry. Social media scraping can be used for brand monitoring and gaining competitive intelligence that can be used to optimize your business model for maximum effectiveness. This will in turn make your company stand out from the competition and the added advantage of insights gained from social media data will help you to take over your competitors.

Source: https://www.promptcloud.com/blog/social-media-scraping-for-competitive-intelligence

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

Difference between Data Mining and KDD

Difference between Data Mining and KDD

Data, in its raw form, is just a collection of things, where little information might be derived. Together with the development of information discovery methods(Data Mining and KDD), the value of the info is significantly improved.

Data mining is one among the steps of Knowledge Discovery in Databases(KDD) as can be shown by the image below.KDD is a multi-step process that encourages the conversion of data to useful information. Data mining is the pattern extraction phase of KDD. Data mining can take on several types, the option influenced by the desired outcomes.

Knowledge Discovery in Databases Steps
Data Selection

KDD isn’t prepared without human interaction. The choice of subset and the data set requires knowledge of the domain from which the data is to be taken. Removing non-related information elements from the dataset reduces the search space during the data mining phase of KDD. The sample size and structure are established during this point, if the dataset can be assessed employing a testing of the info.
Pre-processing

Databases do contain incorrect or missing data. During the pre-processing phase, the information is cleaned. This warrants the removal of “outliers”, if appropriate; choosing approaches for handling missing data fields; accounting for time sequence information, and applicable normalization of data.
Transformation

Within the transformation phase attempts to reduce the variety of data elements can be assessed while preserving the quality of the info. During this stage, information is organized, changed in one type to some other (i.e. changing nominal to numeric) and new or “derived” attributes are defined.
Data mining

Now the info is subjected to one or several data-mining methods such as regression, group, or clustering. The information mining part of KDD usually requires repeated iterative application of particular data mining methods. Different data-mining techniques or models can be used depending on the expected outcome.
Evaluation

The final step is documentation and interpretation of the outcomes from the previous steps. Steps during this period might consist of returning to a previous step up the KDD approach to help refine the acquired knowledge, or converting the knowledge in to a form clear for the user.In this stage the extracted data patterns are visualized for further reviews.
Conclusion

Data mining is a very crucial step of the KDD process.

For further reading aboud KDD and data mining ,please check this link.

Source: http://nocodewebscraping.com/difference-data-mining-kdd/

Data Mining vs Screen-Scraping

Data Mining vs Screen-Scraping

Data mining isn't screen-scraping. I know that some people in the room may disagree with that statement, but they're actually two almost completely different concepts.

In a nutshell, you might state it this way: screen-scraping allows you to get information, where data mining allows you to analyze information. That's a pretty big simplification, so I'll elaborate a bit.

The term "screen-scraping" comes from the old mainframe terminal days where people worked on computers with green and black screens containing only text. Screen-scraping was used to extract characters from the screens so that they could be analyzed. Fast-forwarding to the web world of today, screen-scraping now most commonly refers to extracting information from web sites. That is, computer programs can "crawl" or "spider" through web sites, pulling out data. People often do this to build things like comparison shopping engines, archive web pages, or simply download text to a spreadsheet so that it can be filtered and analyzed.

Data mining, on the other hand, is defined by Wikipedia as the "practice of automatically searching large stores of data for patterns." In other words, you already have the data, and you're now analyzing it to learn useful things about it. Data mining often involves lots of complex algorithms based on statistical methods. It has nothing to do with how you got the data in the first place. In data mining you only care about analyzing what's already there.

The difficulty is that people who don't know the term "screen-scraping" will try Googling for anything that resembles it. We include a number of these terms on our web site to help such folks; for example, we created pages entitled Text Data Mining, Automated Data Collection, Web Site Data Extraction, and even Web Site Ripper (I suppose "scraping" is sort of like "ripping"). So it presents a bit of a problem-we don't necessarily want to perpetuate a misconception (i.e., screen-scraping = data mining), but we also have to use terminology that people will actually use.

Source: http://ezinearticles.com/?Data-Mining-vs-Screen-Scraping&id=146813

Tips for scraping business directories

Tips for scraping business directories

Are you looking to scrape business directories to generate leads?

Here are a few tips for scraping business directories.

Web scraping is not rocket science. But there are good and bad and worst ways of doing it.

Generating sales qualified leads is always a headache. The old school ways are to buy a list from sites like Data.com. But they are quite expensive.

Scraping business directories can help generate sales qualified leads. The following tips can help you scrape data from business directories efficiently.

1) Choose a good framework to write the web scrapers. This can help save a lot of time and trouble. Python Scrapy is our favourite, but there are other non-pythonic frameworks too.

2) The business directories might be having anti-scraping mechanisms. You have to use IP rotating services to do the scrape. Using IP rotating services, crawl with multiple changing IP addresses which can cover your tracks.

3) Some sites really don’t want you to scrape and they will block the bot. In these cases, you may need to disguise your web scraper as a human being. Browser automation tools like selenium can help you do this.

4) Web sites will update their data quite often. The scraper bot should be able to update the data according to the changes. This is a hard task and you need professional services to do that.

One of the easiest ways to generate leads is to scrape from business directories and use enrich them. We made Leadintel for lead research and enrichment.

Source: http://blog.datahut.co/tips-for-scraping-business-directories/

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