Usefulness of Web Scraping Services

For any business or organization, surveys and market research play important roles in the strategic decision-making process. Data extraction and web scraping techniques are important tools that find relevant data and information for your personal or business use. Many companies employ people to copy-paste data manually from the web pages. This process is very reliable but very costly as it results to time wastage and effort. This is so because the data collected is less compared to the resources spent and time taken to gather such data.

Nowadays, various data mining companies have developed effective web scraping techniques that can crawl over thousands of websites and their pages to harvest particular information. The information extracted is then stored into a CSV file, database, XML file, or any other source with the required format. After the data has been collected and stored, data mining process can be used to extract the hidden patterns and trends contained in the data. By understanding the correlations and patterns in the data; policies can be formulated and thereby aiding the decision-making process. The information can also be stored for future reference.

The following are some of the common examples of data extraction process:

• Scrap through a government portal in order to extract the names of the citizens who are reliable for a given survey.

• Scraping competitor websites for feature data and product pricing

• Using web scraping to download videos and images for stock photography site or for website design

Automated Data Collection

It is important to note that web scraping process allows a company to monitor the website data changes over a given time frame. It also collects the data on a routine basis regularly. Automated data collection techniques are quite important as they help companies to discover customer trends and market trends. By determining market trends, it is possible to understand the customer behavior and predict the likelihood of how the data will change.

The following are some of the examples of the automated data collection:

• Monitoring price information for the particular stocks on hourly basis

• Collecting mortgage rates from the various financial institutions on the daily basis

• Checking on weather reports on regular basis as required

By using web scraping services it is possible to extract any data that is related to your business. The data can then be downloaded into a spreadsheet or a database for it to be analyzed and compared. Storing the data in a database or in a required format makes it easier for interpretation and understanding of the correlations and for identification of the hidden patterns.

Through web scraping it is possible to get quicker and accurate results and thus saving many resources in terms of money and time. With data extraction services, it is possible to fetch information about pricing, mailing, database, profile data, and competitors data on a consistent basis. With the emergence of professional data mining companies outsourcing your services will greatly reduce your costs and at the same time you are assured of high quality services.

Source:http://ezinearticles.com/?Usefulness-of-Web-Scraping-Services&id=7181014

Internet marking is the finest method of increment of popularity in commerce

In today’s world key to any business is right kind of marketing strategy that needs to be implemented for the success of any entrepreneurial project. One of the fastest growing ways is to get the listing of your company in top search engines. SEO is one of the ways which can help in increasing or diverting the traffic on any website. People should understand the search result of their website is displayed on the World Wide Web. Different search engines work in different ways by providing different ranking to websites according to the search of the people.

This is why same website has different ranks on different search engines. Basically, website owner provides the keywords to the SEO providers which are appropriate to their business. Business SEO providers make sure the owners are charged low and also providing correct information to search engines. Providing better SEO in Ottawa is the basic feature that service providers aim at, their main motive is to make these services available to all the common people so that they can benefit there business in a better way. A good SEO mostly uses popular sites like Google, Bing, Yahoo, Yellow pages etc.

These SEO companies make sure that the listing of their clients is upgraded by repeated updating and also there ranking reaches top on search engines. Consultations with SEO service provider can be availed for free by the website owners. SEO companies carefully chooses keyword for their clients because it has to be unique and commonly used to make them reach at the top .They do so by carefully analyzing the owners website and competitors website and then the strategy is made to determine the perfect keyword for their clients.

Owner should make sure that the prices charged to him are competitive according to market. Consultation and Analysis are important because the keyword formation is directly dependent on these two parameters if the SEO service provider fails to submit the proper keyword it would result in failure of whole SEO services for the owner.

SEO provider can re create and also modify the keywords for any website. If anyone specifically looking to create a new SEO website for him then the Looking internet marketing company in ottawa specialists can help them in determining a new domain that could be related to the business of the owner. Secondly, good hosting service is provided by them which help a website fast to access by any user. The biggest task for Internet marketing specialist is Link building because it represents more than 80% result of SEO. For any website owner good SEO link building can be good in this competitive world because it attracts the people.

A good SEO developer plays a pivotal role in developing a perfect keyword for the company. Ottawa SEO companies are very famous to deliver their services to the customers at very reasonable prices. SEO services are available online one can visit their websites see the list of services offered by them, read the testimonials of the existing and choose from them pay online and get started.

For further detail about Business seo service in Ottawa please visit the website.

Source:http://blogs.siliconindia.com/businessseo/Business/Internet-marking-is-the-finest-method-of-increment-of-popularity-in-commerce-bid-cf9206bx84461691.html

Bitcoin Mining Company CoinTerra Enters Cloud Mining

Amid rapid changes in the bitcoin mining industry, another bitcoin miner is going into the cloud.

CoinTerra on Monday announced that it will begin offering cloud-based mining services to its customers, becoming the second big miner this month to make the move. As the price of bitcoin has tumbled, it has become increasingly difficult to profitably mine bitcoin, a problem for the miners and the companies catering to them.

As more miners come aboard, the bitcoin algorithm automatically adjusts its difficultly higher. This has sparked an arms race, with miners deploying increasingly powerful computers to stay on top. That has led to a rising spiral of costs. It’s reached the point where it’s become cost-prohibitive for people to mine on their own. Cloud mining, where miners buy contracts from companies like CoinTerra and PeerNova, is emerging as a cheaper option.

CoinTerra, founded nearly a year ago,  will be selling one- and two-year contracts for a range of mining power, from 200 gigahash (small) up to one petahash (big), as well as continuing to sell mining rigs. “We’re catering to basically the entire spectrum out there,” CEO Ravi Iyengar told BitBeat. Through the mining rigs it sells, CoinTerra comprises about 15% of the total mining output, the company said, and it expects to maintain that market share.

As bitcoin has grown, the”hash rate,” a measurement of mining power, has skyrocketed. In September 2013, the entire mining network reached the 1 petahash/second rate, a multiple of 40 times higher than in January 2013. Now CoinTerra will be selling 1 petahash contracts. It’s gotten so big, it’s harder to mine profitably on anything but a very large scale. CoinTerra itself saw sales drop 30% in April. Thus the move into cloud mining.

In the early days of the cryptocurrency, it was possible to mine using desktop computers. As it grew, CPUs gave way to graphics cards, which gave way to generic chips modified for mining, which gave way to chips programmed for a single task called ASICs. It now takes machines with multiple dedicated chips to mine profitably, and increasingly even that kind of computing power doesn’t provide a sufficient return on the investment, given the falling price of bitcoins, the increasing size of the mining community, and the concurrent increasing energy demands, which has emerged as a major roadblock. “Space and power is a big issue,” Mr. Iyengar told BitBeat. “The power required is unlike any other server industry.”

CoinTerra is leasing space at several data centers in the U.S., he said, and has some plans to build its own data center.

The upheaval has resulted in a string of problems for the industry, from bankruptcies to delivery delays to lawsuits. KnCMiner has had problems with deliveries, and branched out into selling rigs that mine for altcoins rather than bitcoin. Butterfly Labs is involved in several lawsuits, and a startup called HashFast Technologies (which is also involved in a lawsuit) on Monday announced that it laid off 50% of its staff. Washington-based Alydian simply went bankrupt as the cloud-based mining business it built couldn’t keep up with the increasing power demands.

“A lot of people got into this space in the mad gold rush,” Mr. Iyengar said, “here you’re trying to combine hardware and software and the whole supply chain associated with a server market.” He likened it to trying to combine Intel, Microsoft, and Dell.

The total computing power is rising at such an exponential rate, that machines have a short productive lifespan. Even a delay of a month or two between the time a customer places an order and the time the machine arrives can severely cut into profits.

Thus the move into the cloud. CoinTerra joins the recently formed PeerNova in offering cloud services.

Source:http://blogs.wsj.com/moneybeat/2014/05/12/bitcoin-mining-company-cointerra-enters-cloud-mining/

Data scraping tool for non-coding journalists launches

A tool which helps non-coding journalists scrape data from websites has launched in public beta today.

Import.io lets you extract data from any website into a spreadsheet simply by mousing over a few rows of information.

Until now import.io, which we reported on back in April, has been available in private developer preview and has been Windows only. It is now also available for Mac and is open to all.

Although import.io plans to charge for some services at a later date, there will always be a free option.

The London-based start-up is trying to solve the problem of the fact that there is "lots of data on the web, but it's difficult to get at", Andrew Fogg, founder of import.io, said in a webinar last week.

Those with the know-how can write a scraper or use an API to get at data, Fogg said. "But imagine if you could turn any website into a spreadsheet or API."

Uses for journalists

Journalists can find stories in data. For example, if I wanted to do a story on the type of journalism jobs being advertised and the salaries offered, I could research this by looking at various websites which advertise journalism jobs.

If I were to gather the data from four different jobs boards and enter the information manually into a spreadsheet it would take would take hours if not days; if I were to write a screen scraper for each of the sites it would require knowledge and would probably take a couple of hours. Using import.io I can create a single dataset from multiple sources in a few minutes.

I can then search and sort the dataset and find out different facts, such as how many unpaid internships are advertised, or how many editors are currently being sought.

How it works

When you download the import.io application you see a web browser. This browser allows you to enter a URL for any site you want to scrape data from.

To take the example of the jobs board, this is structured data, with the job role, description and salaries displayed.

The first step is to set up 'connectors' and to do this you need to teach the system where the data is on the page. This is done by hitting a 'record' button on the right of the browser window and mousing over a few examples, in this case advertised jobs. You then click 'train rows'.

It takes between two and five examples to teach import.io where all of the rows are, Fogg explained in the webinar.

The next step is to declare the type of data and add column names. For example there may be columns for 'job title', 'job description' and 'salary'. Data is then extracted into the table below the browser window.

Data from different websites can then be "mixed" into a single searchable database.

In the example used in the webinar, Fogg demonstrated how import.io could take data relating to rucksacks for sale on a shopping website. The tool can learn the "extraction pattern", Fogg explained, and apply that to to another product. So rather than mousing over the different rows of sleeping bags advertised, for example, import.io was automatically able to detect where the price and product details were on the page as it had learnt the structure from how the rucksacks were organised. The really smart bit is that the data from all products can then be automatically scraped and pulled into the spreadsheet. You can then search 'shoes' and find the data has already been pulled into your database.

When a site changes its code a screen scraper would become ineffective. Import.io has a "resilience to change", Fogg said. It runs tests twice a day and users get notified of any changes and can retrain a connector.

It is worth noting that a site that has been scraped will be able to detect that import.io has extracted the data as it will appear in the source site's web logs.

Case studies

A few organisations have already used import.io for data extraction. Fogg outlined three.

    British Red Cross

The British Red Cross wanted to create an iPhone app with data from the NHS Choices website. The NHS wanted the charity to use the data but the health site does not have an API.

By using import.io, data was scraped from the NHS site. The app is now in the iTunes store and users can use it to enter a postcode to find hospital information based on the data from the NHS site.

"It allowed them to build an API for a website where there wasn't one," Fogg said.

    Hewlett Packard

Fogg explained that Hewlett Packard wanted to monitor the prices of its laptops on retailers' websites.

They used import.io to scrape the data from the various sites and were able monitor the prices at which the laptops were being sold in real-time.

    Recruitment site

A US recruitment firm wanted to set up a system so that when any job vacancy appeared on a competitor's website, they could extract the details and push that into their Salesforce software. The initial solution was to write scrapers, Fogg said, but this was costly and in the end they gave up. Instead they used import.io to scrape the sites and collate the data.


Source: http://www.journalism.co.uk/news/data-scraping-tool-for-non-coding-journalists-launches/s2/a554002/

ScraperWiki lets anyone scrape Twitter data without coding

The Obama administration’s open data mandate announced on Thursday was made all the better by the unveiling of the new ScraperWiki service on Friday. If you’re not familiar with ScraperWiki, it’s a web-scraping service that has been around for a while but has primarily focused on users with some coding chops or data journalists willing to pay to have someone scrape data sets for them. Its new service, though, currently in beta, also makes it possible for anyone to scrape Twitter to create a custom data set without having to write a single line of code.

Taken alone, ScraperWiki isn’t that big of a deal, but it’s part of a huge revolution that has been called the democratization of data. More data is becoming available all the time — whether from the government, corportations or even our own lives — only it’s not of much use unless you’re able to do something with it. ScraperWiki is now one of a growing list of tools dedicated to helping everyone, not just expert data analysts or coders, analyze — and, in its case, generate — the data that matters to them.

After noticing a particularly large numbers of tweets in my stream about flight delays yesterday, I thought I’d test out ScraperWiki’s new Twitter search function by gathering a bunch of tweets directed to @United. The results — from 1,697 tweets dating back to May 3 — are pretty fun to play with, if not that surprising. (Also, I have no idea how far back the tweet search will go or how long it will take using the free account, which is limited to 30 minutes of compute time a day. I just stopped at some point so I could start digging in.)

First things first, I ran my query. Here’s what the data looks like viewed in a table in the ScraperWiki app.

Next, it’s a matter of analyzing it. ScraperWiki lets you view it in a table (like above), export it to Excel or query it using SQL, and will also summarize it for you. This being Twitter data, the natural thing to do seemed to be analyzing it for sentiment. One simple way to do this right inside the ScraperWiki table is to search for a particular term that might suggest joy or anger. I chose a certain four-letter word that begins with f.

Surprisingly, I only found eight instances. Here’s my favorite: “Your Customer Service is better than a hooker. I paid a bunch of money and you’re still…” (You probably get the idea.)

But if you read my “data for dummies” post from January, you know that we mere mortals have tools at our disposal for dealing with text data in a more refined way. IBM’s Many Eyes service won’t let me score tweets for sentiment, but I can get a pretty good idea overall by looking at how words are used. For this job, though, a simple word cloud won’t work, even after filtering out common words, @united and other obvious terms. Think of how “thanks” can be used sarcastically and you can see why.

Using the customized word tree, you can see that “thanks” sometimes means “thanks.” Other times, not so much. I know it’s easy to dwell on the negative, but consider this: “worst” had 28 hits while “best” had 15. One of those was referring to Tito’s vodka and at least three were referring to skyline views. (Click here to access it and search by whatever word you want.)

Here’s a phrase net filtering the results by phrases where the word “for” connects two words.

Anyhow, this was just a fast, simple and fairly crude example of what ScraperWiki now allows users to do, and how that resulting data can be combined with other tools to analyze and visualize it. Obviously, it’s more powerful if you can code, but new tools are supposedly on the way (remember, this is just a beta version) that should make it easier to scrape data from even more sources.

In the long term, though, services like ScraperWiki should become a lot more valuable as tools for helping us generate and analyze data rather than just believe what we’re told. Want to improve your small business, put your life in context or perhaps just write the best book report your teacher has ever seen? It’s getting easier every day.


Source: http://gigaom.com/2013/05/10/scraperwiki-lets-anyone-scrape-twitter-data-without-coding/

What is data scraping and how can I stop it?

Data scraping (also called web scraping) is the process of extracting information from websites. Data scraping focuses on transforming unstructured website content (usually HTML) into structured data which can be stored in a database or spreadsheet.

The way data is scraped from a website is similar to that used by search bots – human web browsing is simulated by using programs (bots) which extract (scrape) the data from a website.

Unfortunately, there is no efficient way to fully protect your website from data scraping. This is so because data scraping programs (also called data scrapers or web scrapers) obtain the same information as your regular web visitors.

Even if you block the IP address of a data scraper, this will not prevent it from accessing your website. Most data scraping bots use large IP address pools and automatically switch the IP address in case one IP gets blocked. And if you block too many IPs, you will most probably block many of your legitimate visitors.

One of the best ways to protect globally accessible data on a website is through copyright protection. This way you can legally protect the intellectual ownership of your website content.

Another way to protect your site content is to password protect it. This way your website data will be available only to people who can authenticate with the correct username and password.


Source: http://kb.siteground.com/what_is_data_scraping_and_how_can_i_stop_it/

A Guide to Web Scraping Tools

This post is ghost written by one of my bloggers, I outsource 95% of my life.  The author’s views below are entirely his or her own and may not reflect the views of  Gareth James aka SEO Doctor

Web Scrapers are tools designed to extract / gather data in a website via crawling engine usually made in Java, Python, Ruby and other programming languages.Web Scrapers are also called as Web Data Extractor, Data Harvester , Crawler and so on which most of them are web-based or can be installed in local desktops.

Its main purpose is to enable webmasters, bloggers, journalist and virtual assistants to harvest data from a certain website whether text, numbers, contact details and images in a structured way which cannot be done easily thru manual copy and paste method. Typically, it transforms the unstructured data on the web, from HTML format into a structured data stored in a local database or spreadsheet or automates web human browsing.


Source: http://www.garethjames.net/a-guide-to-web-scrapping-tools/