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.


Article Source: http://EzineArticles.com/5906957

Google Sheets vs Web Scraping Services

Google Sheets vs Web Scraping Services

Ever since the data on the web started multiplying in terms of quantity and quality, people have sought out ways to scrape or extract this data for a wide range of applications. Since the scope of extraction was limited back then, the extraction methods mostly comprised of manual methods like copy-pasting text into a local document.

As businesses realized the importance of web scraping as a big data acquisition channel, new technologies and tools surfaced with advanced capabilities to make web scraping easier and efficient.

Today, there are various solutions catering to the web data extraction requirements of companies; DIY tools to managed web scraping services are out there and you can choose one that suits your requirements the best.

Scraping using Google sheets

As we mentioned earlier, there are so many different ways to extract data from the web although not all of these would make sense from a business point of view. You can even use Google docs to extract data from a simple HTML page if you are looking to understand the basics of web scraping. You could check out our guide on using google sheets to scrape a website if you want to learn something that might come handy.

However, Google docs and other web data extraction tools come with their own limitations. For starters, tools aren’t meant for large-scale extraction which is what most businesses will require. Unless you are a hobbyist looking to extract a few web pages for tinkering with a new data visualization tool, you should steer clear from web scraping tools. Scraping tools cannot cater to the requirements of a business as it could be well out of their capabilities.

Enterprise-grade web data extraction

Web scraping is only a common term for the process of saving data from a web page to a local storage or cloud. However, if we consider the practical applications of the data, it’s obvious that there’s a clear distinction between mere web scraping and enterprise-grade web data extraction.

The latter is more inclined towards the extraction of data from the web for real-world applications and hence requires advanced solutions that are built for the same. Following are some of the qualities that an enterprise-grade web scraping solution should have:

- High-end customization options
- Complete automation
- Post-processing options to make the data machine-ready
- Technology to handle dynamic websites
- Capability of handling large-scale extraction

Why DaaS is the best solution for enterprise-grade web scraping

When it comes to extracting data for business use cases, there should be a stark difference in the way things are done. The speed and efficiency matters more in the business world and this demands a managed web scraping solution that takes the complexities and pain points out of the process to provide companies with just the data they need, the way they need it.

Data as a Service is exactly what businesses that are looking to extract web data without losing focus on their core business operations need. Web crawling companies like PromptCloud, that work on the DaaS model does all the heavy lifting associated with extracting web data and deliver only the needed data to the companies in a ready-to-use format.

Source:-https://www.promptcloud.com/blog/google-sheets-vs-web-scraping-services

Scraping Dynamic Websites: How We Tackle the Problem

Scraping Dynamic Websites: How We Tackle the Problem

Acquiring data from the web for business applications has already gained popularity if we look at the sheer number of use cases. Companies have realized the value addition provided by data and are looking for better and efficient ways of data extraction. However, web scraping is a niche technical process that takes years to master given the dynamic nature of the web. Since every website is different and custom coded, it’s not possible to write a single program that can handle multiple websites. The web scraping setup should be coded separately for each target site and this needs a team of skilled programmers.

Web scraping is without doubt a complex trade; however if the target site in question employs dynamic coding practices, this complexity is further multiplied. Over the years, we have understood the technical nuances of web scraping and perfected our modus operandi to to scrape dynamic websites with high accuracy and efficiency. Here are some ways how we tackle the challenge of scraping dynamic websites.

1. Proxies

Some websites have different Geo/Device/OS/browser specific versions that they serve depending on the variables. This could give a great deal of confusion to the crawlers especially while figuring out how to extract the right version. This will need some manual work in terms of finding the different versions provided by the site and configuring proxies to fetch the right version as per the requirement. For geo-specific versions, the crawler is simply deployed on a server from where the required version of the site is accessible.

2. Browser automation

When it comes to websites that use very complex and dynamic code, it’s better have all the page content rendered using a browser first. Selenium can be used for browser automation which will help us do the scraping. It is essentially a handy toolkit that can drive the browser from your favorite programming language. Although it’s primarily used for testing, it can be used for scraping dynamic web pages. It can be used to control a web browser, which is how scraping using selenium is typically done. In this case, the browser first renders the page which will help overcome the problem of reverse engineering JavaScript code to fetch the page content. Once the page content is rendered, it is saved locally to scrape the required data points later. Although this is comparatively easy, there is a high chance of encountering errors while scraping using the browser automation method.

3. Handling POST requests

Many web pages will only display the data that we need after receiving a certain input from the user. Let’s say you are looking for used cars data from a particular geo-location on a classified site. The website would first require you to enter the ZIP code of the location from where you need listings from. This ZIP code must be sent to the website as a post request while scraping. We craft the post request using the appropriate parameters so as to reach the target page that contains all the data points to be scraped.

4. Manufacturing the JSON URL

There are dynamic web pages that use AJAX calls to load and refresh the page content. These are particularly difficult to scrape and extract data from as the triggers that make up the JSON file is difficult to trace. This requires a lot of manual inspection and testing, but once the appropriate parameters are identified, a JSON file that would fetch the target page which includes the desired data points can be manufactured. This JSON file is often tweaked automatically for navigation or fetching varying data points. Manufacturing the JSON URL with apt parameters is the primary pain point with web pages that use AJAX calls.
Bottom-line

Scraping dynamic web pages is extremely complicated and demands deep expertise in the field of web scraping. It also demands an extensive tech stack and well-built infrastructure that can handle the complexities associated with web data extraction. With our years of expertise and well-evolved web scraping infrastructure, we cater to data requirements where dynamic web pages are involved on a daily basis.

Source:https://www.promptcloud.com/blog/scraping-dynamic-websites-web-scraping

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/

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

Tips For Data Scrapping in PDF File

Tips For Data Scrapping in PDF File

What is the Data Scrapping?

End data, a method or a procedure in which material is extracted from the text refers to a document. A person using this process can remove material from a PDF file format.

Those involved in commercial activities may fall short on data disposal. It is a process in which data or information can be extracted from the Portable Document Format file. They have tools that automatically format data that different provisions may be found on the Internet are easy to use. These advanced tools to the needs of users can gather information. Users do just words or phrases and all related equipment, Portable Document Format file that will extract the necessary information available to enter. It is widely used to collect information from an editable format.

Portable Document Format files are a major asset to protect the originality of the documents you convert from Word to PDF data. Algorithms the image file compression file sizes are due to heavy graphics or content are less. A portable Data Scrapping document format or to fix any software, hardware independent. File encryption enhances the security of its content allows.

How data from a PDF file, you can scrap?

A portable document format that an application for exchange or transfer data over the content or the platform can be used. Part of storing large amounts of data as a simple tool can use this program. Easy and rapid application materials in a portable document format can handle. The computer program that more or stored in a Portable Document Format file is a variety of data extracted.

Valuable content in a particular file can remove a non-editable. An application containing a PDF document can make large amounts of valuable information. This technique of sampling equipment reports, theses, presentations, projects, manuals and other documents those are useful to prepare.

Information out to eliminate important data in the format support. Easily extracted from a person can keep the formatting of the data intact and secure. You and PDF documents on a variety of subjects to make a number of Word may be for information purposes. A scene from a non-editable file can delete content or images. Therefore, with text and graphics can be extracted.

A Portable Document Format is an application that is used for a variety of reasons. A personal password, certificates and digital signatures can encrypt files using. It is portable and compatible format that allows you to transfer your files in Portable Document Format is applied. The request to use the information for a variety of reports can be prepared properly.

Source:http://www.sooperarticles.com/business-articles/outsourcing-articles/tips-data-scrapping-pdf-file-492673.html#ixzz4hmydaqhY