7 Best Web Scraping Software tools to Acquire Data Without Coding

Ever since the world wide web started growing in terms of data size and quality, businesses and data enthusiasts have been looking for methods to extract this data from the web. Today, there are various ways to acquire data from websites of your preference. Some are meant for hobbyists and some are suitable for enterprises. DIY web scraping software belong the former category. If you need data from a few websites of your choice for a quick research or project, these tools are more than enough. DIY web scraping tools are much easier to use in comparison to programming your own web scraping setup. Here are some of the best web scraping software available in the market right now.

best web scraping software

1. Outwit Hub
Outwit hub is a Firefox extension that can be easily downloaded from the Firefox add-ons store. Once installed and activated, it gives web scraping capabilities to your browser. Out of the box, it has data points recognition features that can make your scraping job easier. Extracting data from sites using Outwit hub doesn’t demand programming skills. The set up is fairly easy to learn. You can refer to our guide on using Outwit hub to get started with web scraping using the tool. As it is free of cost, it makes for a great option if you need to scrape some data from the web quickly.

2. Web Scraper Chrome Extension
Web scraper is a great alternative to Outwit hub which is available for Google Chrome that can be used for web scraping. It lets you set up a sitemap (plan) on how a website should be navigated and what data should to be extracted. It can scrape multiple pages simultaneously and even has dynamic data extraction capabilities. Web scraper can also handle pages with JavaScript and Ajax, which makes it all the more powerful. The tool lets you export the extracted data to a CSV file. The only downside to web scraper extension is that it doesn’t have many automation features built in. Learn how to use web scraper to extract data from the web.

3. Spinn3r
Spinn3r is a great choice for scraping entire data from blogs, news sites, social media and RSS feeds. Spinn3r uses firehose API that manages 95% of the crawling and indexing work. It gives you the option to filter the data that it scrapes using keywords, which helps in weeding out irrelevant content. The indexing system of Spinn3r is similar to Google and saves the extracted data in JSON format. Spinn3r works by continuously scanning the web and updating their data sets. It has an admin console packed with features that lets you perform searches on the raw data. Spinn3r is an ideal solution if your data requirements are limited to media websites.

4. Fminer
Fminer is one of the easiest to use web scraping tools out there that combines top-in-class features. Its visual dashboard makes extracting data from websites as simple and intuitive as possible. Whether you want to scrape data from simple web pages or carry out complex data fetching projects that require proxy server lists, ajax handling and multi-layered crawls, Fminer can do it all. If your web scraping project is fairly complex, Fminer is the software you need.

5. Dexi.io
Dexi.io is a web based scraping application that doesn’t require any download. It is a browser based tool that lets you set up crawlers and fetch data in real-time. Dexi.io also has features that will let you save the scraped data directly to Box.net and Google drive or export it as JSON or CSV files. It also supports scraping the data anonymously using proxy servers. The data you scrape will be hosted on their servers for up to 2 weeks before it’s archived.

6. ParseHub
Parsehub is a web scraping software that supports complicated data extraction from sites that use AJAX, JavaScript, redirects and cookies. It is equipped with machine learning technology that can read and analyse documents on the web to output relevant data. Parsehub is available as a desktop client for windows, mac and linux and there is also a web app that you can use within the browser. You can have up to 5 crawl projects with the free plan from Parsehub.


7. Octoparse
Octoparse is a visual web scraping tool that is easy to configure. The point and click user interface lets you teach the scraper how to navigate and extract fields from a website. The software mimics a human user while visiting and scraping data from target websites. Octoparse gives the option to run your extraction on the cloud and on your own local machine. You can export the scraped data in TXT, CSV, HTML or Excel formats.

Tools vs Hosted Services
Although web scraping tools can handle simple to moderate data extraction requirements, these are not a recommended solution if you are a business trying to acquire data for competitive intelligence or market research. When the requirement is large-scale and/or complicated, web scraping tools fail to live up to the expectations. DIY tools can be the right choice if your data requirements are limited and the sites you are looking to scrape are not complicated. If you need enterprise-grade data, outsourcing the requirement to a DaaS (Data-as-a-Service) provider would be the ideal option. Dedicated web scraping services will take care of end-to-end data acquisition and will deliver the required data, the way you need it.

If your data requirement demands a custom built set up, a DIY tool cannot cover it. For example, if you need product data of the best selling products from Amazon at a predefined frequency, you will have to consult a web scraping provider instead of using a software. With a software, the customization options are limited and automation is almost non-existent. Tools also come with the downside of maintenance, which can be a daunting task. A scraping service provider will set up monitoring for the target websites and make sure that the scraping setup is well maintained. The flow of data will be smooth and consistent with a hosted solution.

Source url :-https://www.promptcloud.com/blog/best-web-scraping-software-tools-extract-data

Data Scraping Doesn’t Have to Be Hard

All You Need Is the Right Data Scraping Partner

Odds are your business needs web data scraping. Data scraping is the act of using software to harvest desired data from target websites. So, instead of you spending every second scouring the internet and copying and pasting from the screen, the software (called “spiders”) does it for you, saving you precious time and resources.

Departments across an organization will profit from data scraping practices.

Data scraping will save countless hours and headaches by doing the following:

- Monitoring competitors’ prices, locations and service offerings
- Harvesting directory and list data from the web, significantly improving your lead generation
- Acquiring customer and product marketing insight from forums, blogs and review sites
- Extracting website data for research and competitive analysis
- Social media scraping for trend and customer analysis
- Collecting regular or even real time updates of exchange rates, insurance rates, interest rates, -mortgage rates, real estate, stock prices and travel prices

It is a no-brainer, really. Businesses of all sizes are integrating data scraping into their business initiatives. Make sure you stay ahead of the competition by effectively data scraping.

Now for the hard part

The “why should you data scrape?” is the easy part. The “how” gets a bit more difficult. Are you savvy in Python and HTML? What about JavaScript and AJAX? Do you know how to utilize a proxy server? As your data collection grows, do you have the cloud-based infrastructure in place to handle the load? If you or someone at your organization can answer yes to these questions, do they have the time to take on all the web data scraping tasks? More importantly, is it a cost-effective use of your valuable staffing resources for them to do this? With constantly changing websites, resulting in broken code and websites automatically blacklisting your attempts, it could be more of a resource drain than anticipated.

Instead of focusing on all the issues above, business users should be concerned with essential questions such as:

- What data do I need to grow my business?
- Can I get the data I need, when I want it and in a format I can use?
- Can the data be easily stored for future analysis?
- Can I maximize my staffing resources and get this data without any programming knowledge or IT assistance?
- Can I start now?
- Can I cost-effectively collect the data needed to grow my business?

A web data scraping partner is standing by to help you!

This is where purchasing innovative web scraping services can be a game changer. The right partner can harness the value of the web for you. They will go into the weeds so you can spend your precious time growing your business.

Hold on a second! Before you run off to purchase data scraping services, you need to make sure you are looking for the solution that best fits your organisational needs. Don’t get overwhelmed. We know that relinquishing control of a critical business asset can be a little nerve-wracking. To help, we have come up with our steps and best practices for choosing the right data scraping company for your organisation.

1) Know Your Priorities

We have brought this up before, but when going through a purchasing decision process we like to turn to Project Management 101: The Project Management Triangle. For this example, we think a Euler diagram version of the triangle fits best.
Data Scraping and the Project Management Triangle

In this example, the constraints show up as Fast (time), Good (quality) and Cheap (cost). This diagram displays the interconnection of all three elements of the project. When using this diagram, you are only able to pick two priorities. Only two elements may change at the expense of the third:

- We can do the project quickly with high quality, but it will be costly
- We can do the project quickly at a reduced cost, but quality will suffer
- We can do a high-quality project at a reduced cost, but it will take much longer
Using this framework can help you shape your priorities and budget. This really, in turn, helps you search for and negotiate with a data scraping company.

2) Know your budget/resources.

This one is so important it is on here twice. Knowing your budget and staffing resources before reaching out to data scraping companies is key. This will make your search much more efficient and help you manage the entire process.

3) Have a plan going in.

Once again, you should know your priorities, budget, business objectives and have a high-level data scraping plan before choosing a data scraping company. Here are a few plan guidelines to get you started:

- Know what data points to collect: contact information, demographics, prices, dates, etc.
- Determine where the data points can most likely be found on the internet: your social media and review sites, your competitors’ sites, chambers of commerce and government sites, e-commerce sites your products/competitors’ products are sold, etc.
- What frequency do you need this data and what is the best way to receive it? Make sure you can get the data you need and in the correct format. Determine whether you can perform a full upload each time or just the changes from the previous dataset. Think about whether you want the data delivered via email, direct download or automatically to your Amazon S3 account.
- Who should have access to the data and how will it be stored once it is harvested?
- Finally, the plan should include what you are going to do with all this newly acquired data and who is receiving the final analysis.

4) Be willing to change your plan.

This one may seem counterintuitive after so much focus on having a game plan. However, remember to be flexible. The whole point of hiring experts is that they are the experts. A plan will make discussions much more productive, but the experts will probably offer insight you hadn’t thought of. Be willing to integrate their advice into your plan.

5) Have a list of questions ready for the company.

Having a list of questions ready for the data scraping company will help keep you in charge of the discussions and negotiations. Here are some points that you should know before choosing a data scraping partner:
- Can they start helping you immediately? Make sure they have the infrastructure and staff to get - you off the ground in a matter of weeks, not months.
- Make sure you can access them via email and phone. Also make sure you have access to those -actually performing the data scraping, not just a call center.
- Can they tailor their processes to fit with your requirements and organisational systems?
- Can they scrape more than plain text? Make sure they can harvest complex and dynamic sites -with JavaScript and AJAX. If a website’s content can be viewed on a browser, they should be-- able to get it for you.
- Make sure they have monitoring systems in place that can detect changes, breakdowns, and -quality issues. This will ensure you have access to a persistent and reliable flow of data, even - when the targeted websites change formats.
- As your data grows, can they easily keep up? Make sure they have scalable solutions that could - handle all that unstructured web data.
- Will they protect your company? Make sure they know discretion is important and that they will not advertise you as a client unless you give permission. Also, check to see how they disguise their scrapers so that the data harvesting cannot be traced back to your business.

6) Check their reviews.

Do a bit of your own manual data scraping to see what others business are saying about the companies you are researching.

7) Make sure the plan the company offers is cost-effective.

Here are a few questions to ask to make sure you get a full view of the costs and fees in the estimate:
- Is there a setup fee?
- What are the fixed costs associated with this project?
- What are the variable costs and how are they calculated?
- Are there any other taxes, fees or things that I could be charged for that are not listed on this -quote?
- What are the payment terms?

Source Url :-http://www.data-scraping.com.au/data-scraping-doesnt-have-to-be-hard/

How We Maintain Data Quality While Handling Large Scale Extraction

How We Maintain Data Quality While Handling Large Scale Extraction

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

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

Manual QA process

1. Crawler review

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

2. Data review

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

Automated monitoring

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

1. Data validation errors

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

2. Volume based inconsistencies

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

3. Site changes

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

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

Data cleansing

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

Structuring

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

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

How Data Scraping Help Businesses?

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

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

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

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


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

Applications of Web Data Extraction in Ecommerce

web data mining ecommerceWe all know the importance of data generated by an organisation and its application in improvement of product strategy, customer retention, marketing, business development and more. With the advent of digital age and increase in storage capacity, we have come to a point where the internal data generated by an organisation has become synonymous with Big Data. But, we must understand that by focusing only on the internal data, we are losing out another another crucial source – the web data.

Pricing Strategy

This is one of the most common use cases in Ecommerce. It’s important to correctly price the products in order to get the best margins and that requires continuous evaluation and remodeling of pricing strategy. The very first approach takes into account market condition, consumer behavior, inventory and a lot more. It’s highly probable that you’re already implementing such type of pricing strategy by leveraging your organisational data. That said, it’s also equally important to consider the pricing set by the competitors for similar products as consumers can be price sensitive.

We provide data feeds consisting of product name, type, variant, pricing and more from Ecommerce websites. You can get this structured data according to your preferred format (CSV/XML/JSON) from your competitors’s websites to perform further analysis. Just feed the data into the analytics tool and you are ready to factor in the competitors’ pricing into your pricing strategy. This will answer some the important questions such as: Which product can attract premium price? Where can we give discount without incurring loss? You can also go one step further by using our live crawling solution to implement a robust dynamic (real-time) pricing strategy. Apart from this, you can use the data feed to understand and monitor competitors’ product catalog.

Reseller management

There are many manufacturers who sell via resellers and generally there are terms that restrict the resellers from selling the products on the same set of Ecommerce sites. This ensures that the seller is not competing with others to sell own product. But, it’s practically impossible to manually search the sites to find the resellers who are infringing the terms. Apart from that, there might be some unauthorized sellers selling your product on various sites.
Web data extraction services can automate the data collection process so that you’ll be able to search products and their sellers with less time and efficiently. After that your legal department can take the further action according to the situation.

Demand analysis

Demand analysis is a crucial component for planning and shipping products. It answers important questions such as: Which product will move fast? Which one will be slower? To start off, e-commerce stores can analyze own sales figures to estimate the demand, but it’s always recommended that planning must be done much before the launch. That way you won’t be planning after the customers land on your site; you’d be ready with right number of products to meet the demand.
One great place to get a solid idea of demand is online classified site. Web crawling can be deployed to monitor the most in-demand products, categories and the listing rate. You can also look at the pattern according to different geographical locations. Finally, this data can be used to prioritize the sales of products in different categories as per region-specific demand.

Search Ranking on marketplaces

Many Ecommerce players sell their product on their own website along with marketplaces like Amazon and eBay. These popular marketplaces attract a huge number of consumers and sellers. The sheer volume of sellers on these platforms makes it difficult to compete and rank high for particular search performed on these sites. Search ranking in these marketplaces depends on multiple factors (title, description, brand, images, conversion rate, etc.) and needs continuous optimization. Hence, monitoring ranking for preferred keywords for the specific products via web data extraction can be helpful in measuring the result of optimization efforts.

Campaign monitoring

Many brands are engaging with consumers via different platforms such as YouTube and Twitter. Consumers are also increasingly turning towards various forums to express their views. It has become imperative for businesses to monitor, listen and act on what consumers say. You need to move beyond number of retweets, likes, views, etc. and look at how exactly consumers perceived your messages.
This can be done by crawling forums and sites like YouTube and Twitter to extract all the comments related to your brand and your competitors’ brand. Further analysis can be done by performing sentiment analysis. This will give you additional idea for future campaigns and help you optimize product strategy along with customer support strategy.

Takeaway

We covered some of the practical use cases of web data mining in the e-commerce domain. Now it’s up to you to leverage the web data to ensure growth of your retail store. That said, crawling and extracting data from the web can be technically challenging and resource intensive. You need a strong tech team with domain expertise, data infrastructure and monitoring setup (in case of website structure changes) to ensure steady flow of data. At this point it won’t be out of context to mention that some of our clients had tried to do this in-house and came to us when the results didn’t meet expectation. Hence, it is recommended that you should go with a dedicated Data as a Service provider who can deliver data from any number of sites according to pre-specified format at desired frequency. PromptCloud takes care of end to end data acquisition pipeline and ensures high quality data delivery without interruption. Check out our detailed post of on things to consider when evaluating options for web data extraction.

Source Url:-https://www.promptcloud.com/blog/applications-of-web-data-extraction-in-ecommerce/

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.

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