Wednesday 27 September 2017

Web Data Extraction Services and Data Collection Form Website Pages

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

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

Examples of web data extraction process include:

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

Automated Data Collection

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

Examples of automated data collection include:

• Monitor price information for select stocks on hourly basis
• Collect mortgage rates from various financial firms on daily basis
• Check whether reports on constant basis as and when required

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

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

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

Article Source: http://EzineArticles.com/4860417

Thursday 21 September 2017

Various Methods of Data Collection

Professionals in all the business industries widely use research, whether it is education, medical, or manufacturing, etc. In order to perform a thorough research, you need to follow few suitable steps regarding data collection. Data collection services play an important role in performing research. Here data is gathered with appropriate medium.

Types of Data

Research could be divided in two basic techniques of collecting data, namely: Qualitative collection of data and quantitative collection. Qualitative data is descriptive in nature and it does not include statistics or numbers. Quantitative data is numerical and includes a lot of figures and numbers. They are classified depending on the methods of its collection and its characteristics.

Data collected primarily by the researcher without depending on pre-researched data is called primary data. Interviews as well as questionnaires are generally found primary data/information collection techniques. Data collected from other means, other than by the researcher is secondary data. Company surveys and government census are examples of secondary collection of information.

Let us understand in detail the methods of qualitative data collection techniques in research.

Internet Data: Here there is a huge collection of data where one gets a huge amount of information for research. Researchers remember that they depend on reliable sources on the web for precise information.

Books and Guides: This traditional technique is authentically used in today's research.

Observational data: Data is gathered using observational skills. Here the data is collected by visiting the place and noting down details of all that the researcher observes which is needed for essential for his research.

Personal Interviews: Increases authenticity of data as it helps to collect first hand information. It does not serve fruitful when a big number of people are to be interviewed.

Questionnaires: Serves best when questioning a particular class. A questionnaire is prepared by the researcher as per the need of data-collection and forwarded to responders.

Group Discussions: A technique of collecting data where the researcher notes down details of what people in a group has to think. He comes to a conclusion depending on the group discussion that involves debate on topics of research.

Use of experiments: To obtain the complete understanding researchers conduct real experiments in the field used mainly in manufacturing and science. It is used to obtain an in-depth understanding of the researching subject.

Data collection services use many techniques including the above mentioned for collection. These techniques are helpful to the researcher in drawing conceptual and statistical conclusions. In order to obtain precise data researchers combine two or more of the data collection techniques.

Source:http://ezinearticles.com/?Various-Methods-of-Data-Collection&id=5906957

Friday 28 July 2017

How We Optimized Our Web Crawling Pipeline for Faster and Efficient Data Extraction

How We Optimized Our Web Crawling Pipeline for Faster and Efficient Data Extraction

Big data is now an essential component of business intelligence, competitor monitoring and customer experience enhancement practices in most organizations. Internal data available in organizations is limited by its scope, which makes companies turn towards the web to meet their data requirements. The web being a vast ocean of data, the possibilities it opens to the business world are endless. However, extracting this data in a way that will make sense for business applications remains a challenging process.

The need for efficient web data extraction

Web crawling and data extraction is something that can be carried out through more than one route. In fact, there are so many different technologies, tools and methodologies you can use when it comes to web scraping. However, not all of these deliver the same results. While using browser automation tools to control a web browser is one of the easier ways of scraping, it’s significantly slower since rendering takes  a considerable amount of time.

There are DIY tools and libraries that can be readily incorporated into the web scraping pipeline. Apart from this, there is always the option of building most of it from scratch to ensure maximum efficiency and flexibility. Since this offers far more customization options which is vital for a dynamic process like web scraping, we have a custom built infrastructure to crawl and scrape the web.

How we cater to the rising and complex requirements

Every web scraping requirement that we receive each day is one of a kind. The websites that we scrape on a constant basis are different in terms of the backend technology, coding practices and navigation structure. Despite all the complexities involved, eliminating the pain points associated with web scraping and delivering ready-to-use data to the clients is our priority.

Some applications of web data demand the data to be scraped in low latency. This means, the data should be extracted as and when it’s updated in the target website with minimal delay. Price comparison, for example requires data in low latency. The optimal method of crawler setup is chosen depending on the application of the data. We ensure that the data delivered actually helps your application, in all of its entirety.

How we tuned our pipeline for highly efficient web scraping

We constantly tweak and tune our web scraping infrastructure to push the limits and improve its performance including the turnaround time and data quality. Here are some of the performance enhancing improvements that we recently made.

1. Optimized DB query for improved time complexity of the whole system

All the crawl stats metadata is stored in a database and together, this piles up to become a considerable amount of data to manage. Our crawlers have to make queries to this database to fetch the details that would direct them to the next scrape task to be done. This usually takes a few seconds as the meta data is fetched from the database. We recently optimized this database query which essentially reduced the fetch time to merely a fraction of seconds from about 4 seconds. This has made the crawling process significantly faster and smoother than before.

2. Purely distributed approach with servers running on various geographies

Instead of using a single server to scrape millions of records, we deploy the crawler across multiple servers located in different geographies. Since multiple machines are performing the extraction, the load on each server will be significantly lower which in turn helps speed up the extraction process. Another advantage is that certain sites that can only be accessed from a particular geography can be scraped while using the distributed approach. Since there is a significant boost in the speed while going with the distributed server approach, our clients can enjoy a faster turnaround time.

3. Bulk indexing for faster deduplication

Duplicate records is never a trait associated with a good data set. This is why we have a data processing system that identifies and eliminates duplicate records from the data before delivering it to the clients. A NoSQL database is dedicated to this deduplication task. We recently updated this system to perform bulk indexing of the records which will give a substantial boost to the data processing time which again ultimately reduces the overall time taken between crawling and data delivery.

Bottom line

As web data has become an inevitable resource for businesses operating across various industries, the demand for efficient and streamlined web scraping has gone up. We strive hard to make this possible by experimenting, fine tuning and learning from every project that we embark upon. This helps us maintain a consistent supply of clean, structured data that’s ready to use to our clients in record time.

Source:https://www.promptcloud.com/blog/how-we-optimized-web-scraping-setup-for-efficiency

Thursday 29 June 2017

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

Saturday 24 June 2017

Things to Factor in while Choosing a Data Extraction Solution

Things to Factor in while Choosing a Data Extraction Solution

Customization options

You should consider how flexible the solution is when it comes to changing the data points or schema as and when required. This is to make sure that the solution you choose is future-proof in case your requirements vary depending on the focus of your business. If you go with a rigid solution, you might feel stuck when it doesn’t serve your purpose anymore. Choosing a data extraction solution that’s flexible enough should be given priority in this fast-changing market.

Cost

If you are on a tight budget, you might want to evaluate what option really does the trick for you at a reasonable cost. While some costlier solutions are definitely better in terms of service and flexibility, they might not be suitable for you from a cost perspective. While going with an in-house setup or a DIY tool might look less costly from a distance, these can incur unexpected costs associated with maintenance. Cost can be associated with IT overheads, infrastructure, paid software and subscription to the data provider. If you are going with an in-house solution, there can be additional costs associated with hiring and retaining a dedicated team.

Data delivery speed

Depending on the solution you choose, the speed of data delivery might vary hugely. If your business or industry demands faster access to data for the survival, you must choose a managed service that can meet your speed expectations. Price intelligence, for example is a use case where speed of delivery is of utmost importance.

Dedicated solution

Are you depending on a service provider whose sole focus is data extraction? There are companies that venture into anything and everything to try their luck. For example, if your data provider is also into web designing, you are better off staying away from them.

Reliability

When going with a data extraction solution to serve your business intelligence needs, it’s critical to evaluate the reliability of the solution you are going with. Since low quality data and lack of consistency can take a toll on your data project, it’s important to make sure you choose a reliable data extraction solution. It’s also good to evaluate if it can serve your long-term data requirements.

Scalability

If your data requirements are likely to increase over time, you should find a solution that’s made to handle large scale requirements. A DaaS provider is the best option when you want a solution that’s salable depending on your increasing data needs.

When evaluating options for data extraction, it’s best keep these points in mind and choose one that will cover your requirements end-to-end. Since web data is crucial to the success and growth of businesses in this era, compromising on the quality can be fatal to your organisation which again stresses on the importance of choosing carefully.

Source:https://www.promptcloud.com/blog/choosing-a-data-extraction-service-provider

Things to Factor in while Choosing a Data Extraction Solution

Things to Factor in while Choosing a Data Extraction Solution

Customization options

You should consider how flexible the solution is when it comes to changing the data points or schema as and when required. This is to make sure that the solution you choose is future-proof in case your requirements vary depending on the focus of your business. If you go with a rigid solution, you might feel stuck when it doesn’t serve your purpose anymore. Choosing a data extraction solution that’s flexible enough should be given priority in this fast-changing market.

Cost

If you are on a tight budget, you might want to evaluate what option really does the trick for you at a reasonable cost. While some costlier solutions are definitely better in terms of service and flexibility, they might not be suitable for you from a cost perspective. While going with an in-house setup or a DIY tool might look less costly from a distance, these can incur unexpected costs associated with maintenance. Cost can be associated with IT overheads, infrastructure, paid software and subscription to the data provider. If you are going with an in-house solution, there can be additional costs associated with hiring and retaining a dedicated team.

Data delivery speed

Depending on the solution you choose, the speed of data delivery might vary hugely. If your business or industry demands faster access to data for the survival, you must choose a managed service that can meet your speed expectations. Price intelligence, for example is a use case where speed of delivery is of utmost importance.

Dedicated solution

Are you depending on a service provider whose sole focus is data extraction? There are companies that venture into anything and everything to try their luck. For example, if your data provider is also into web designing, you are better off staying away from them.

Reliability

When going with a data extraction solution to serve your business intelligence needs, it’s critical to evaluate the reliability of the solution you are going with. Since low quality data and lack of consistency can take a toll on your data project, it’s important to make sure you choose a reliable data extraction solution. It’s also good to evaluate if it can serve your long-term data requirements.

Scalability

If your data requirements are likely to increase over time, you should find a solution that’s made to handle large scale requirements. A DaaS provider is the best option when you want a solution that’s salable depending on your increasing data needs.

When evaluating options for data extraction, it’s best keep these points in mind and choose one that will cover your requirements end-to-end. Since web data is crucial to the success and growth of businesses in this era, compromising on the quality can be fatal to your organisation which again stresses on the importance of choosing carefully.

Source:https://www.promptcloud.com/blog/choosing-a-data-extraction-service-provider

Monday 19 June 2017

How Data Mining Has Shaped The Future Of Different Realms

The work process of data mining is not exactly what its name suggests. In contrast to mere data extraction, it's a concept of data analysis and extracting out important and subject centred knowledge from the given data. Huge amounts of data is currently available on every local and wide area network. Though it might not appear, but parts of this data can be very crucial in certain respects. Data mining can aid one in moldings one's strategies effectively, therefore enhancing an organisation's work culture, leading it towards appreciable growth.

Below are some points that describe how data mining has revolutionised some major realms.

Increase in biomedical researches

There has been a speedy growth in biomedical researches leading to the study of human genetic structure, DNA patterns, improvement in cancer therapies along with the disclosure of factors behind the occurrence of certain fatal diseases. This has been, to an appreciable extent. Data scraping led to the close examination of existing data and pick out the loopholes and weak points in the past researches, so that the existing situation can be rectified.

Enhanced finance services

The data related to finance oriented firms such as banks is very much complete, reliable and accurate. Also, the data handling in such firms is a very sensitive task. Faults and frauds might also occur in such cases. Thus, scraping data proves helpful in countering any sort of fraud and so is a valuable practice in critical situations.

Improved retail services

Retail industries make a large scale and wide use of web scraping. The industry has to manage abundant data based on sales, shopping history of customers, input and supply of goods and other retail services. Also, the pricing of goods is a vital task. Data mining holds huge work at this place. A study of degree of sales of various products, customer behaviour monitoring, the trends and variations in the market, proves handy in setting up prices for different products, bringing up the varieties as per customers' preferences and so on. Data scraping refers to such study and can shape future customer oriented strategies, thereby ensuring overall growth of the industry.

Expansion of telecommunication industry

The telecom industry is expanding day by day and includes services like voicemail, fax, SMS, cellphone, e- mail, etc. The industry has gone beyond the territorial foundations, including services in other countries too. In this case, scraping helps in examining the existing data, analyses the telecommunication patterns, detect and counter frauds and make better use of available resources. Scraping services generally aims to improve the quality of service, being provided to the users.

Improved functionality of educational institutes

Educational institutes are one of the busiest places especially the colleges providing higher education. There's a lot of work regarding enrolment of students in various courses, keeping record of the alumni, etc and a large amount of data has to be handled. What scraping does here is that it helps the authorities locate the patterns in data so that the students can be addressed in a better way and the data can be presented in a tidy manner in future.

Article Source: https://ezinearticles.com/?How-Data-Mining-Has-Shaped-The-Future-Of-Different-Realms&id=9647823