Thursday, 28 September 2017

Internet Data Mining - How Does it Help Businesses?

Internet has become an indispensable medium for people to conduct different types of businesses and transactions too. This has given rise to the employment of different internet data mining tools and strategies so that they could better their main purpose of existence on the internet platform and also increase their customer base manifold.

Internet data-mining encompasses various processes of collecting and summarizing different data from various websites or webpage contents or make use of different login procedures so that they could identify various patterns. With the help of internet data-mining it becomes extremely easy to spot a potential competitor, pep up the customer support service on the website and make it more customers oriented.

There are different types of internet data_mining techniques which include content, usage and structure mining. Content mining focuses more on the subject matter that is present on a website which includes the video, audio, images and text. Usage mining focuses on a process where the servers report the aspects accessed by users through the server access logs. This data helps in creating an effective and an efficient website structure. Structure mining focuses on the nature of connection of the websites. This is effective in finding out the similarities between various websites.

Also known as web data_mining, with the aid of the tools and the techniques, one can predict the potential growth in a selective market regarding a specific product. Data gathering has never been so easy and one could make use of a variety of tools to gather data and that too in simpler methods. With the help of the data mining tools, screen scraping, web harvesting and web crawling have become very easy and requisite data can be put readily into a usable style and format. Gathering data from anywhere in the web has become as simple as saying 1-2-3. Internet data-mining tools therefore are effective predictors of the future trends that the business might take.


Article Source: http://EzineArticles.com/3860679

Friday, 22 September 2017

Data Collection, Just Another Way To Gather Information

Data collection just does not help the companies to launch new products or know about the public reaction to a specific issue, it is a very useful tool for statistical inferences, once the collected data is compiled. The process of data collection is the third step of the six step market research processes. Data collection can be done in two ways involving various technicalities. In this article, we shall give a brief overview of the same.

Data collection can be done in two ways - secondary data and primary data. Secondary data collection involves is the information available in books, journals, previous researches or studies and the Internet. It basically involves making use of the data already present to build or substantiate a concept.

On the other hand, primary data collection is the process of data collection through questionnaire by directly asking respondents of their opinions. Forming the right questionnaire is the most important aspect of data collection. The researcher conducting the data collection just has to be aware of the process. He should have a clear idea about the information sought by the concerned party.

Besides, the data collection officer should be able to construct the questionnaire in such a way so as to elicit the responses needed. Having constructed the questionnaire the researcher should identify the target sample. To illustrate the point clearly, we shall look into the following example.

Suppose, data collection is aimed from an area A, then, if all the residents of the data are given the questionnaire, it is called a census or in other words data collection is done from all the individuals of the specified area. One of the most common examples of data collection done by the government is census. For example the population census conducted by the US Census Bureau every ten years. On the other hand, if only twenty or thirty percent of the population living in area A are given the questionnaire, the mode of data collection would be called sampling.

The data collected from the target sample with a well-defined questionnaire will project the response of the entire population living in the area. Data collected from a sample helps to control the cost and time spent on collecting data from the population. Sample is a part of population.

Data collection just gets easier from the target sample with the help of a pretested questionnaire, which is later analyzed using statistical tests like ANOVA, Chi Square test and so on. These tests help the researcher to infer the result obtained from the data collection.

Market research/data collection is a fast growing and lucrative career option now days. One has to undertake a course in marketing, statistics and research before starting out. It is indeed very important to have a through understanding of various concepts and the theories related. Some basic terminologies related to data collection are: census, incidence, sample, population, parameters, sampling frames and so on.

Source: http://ezinearticles.com/?Data-Collection,-Just-Another-Way-To-Gather-Information&id=853158

Tuesday, 1 August 2017

How Easily Can You Extract Data From Web

How Easily Can You Extract Data From Web

With tech advancements taking the entire world by a storm, every sector is undergoing massive transformations. As far as the business arena is concerned, the rise of big data and data analytic is playing a crucial part in operations. Big data and data analysis is the best way to identify customer interests. Businesses can gain crystal clear insights into consumers’ preferences, choices, and purchase behaviours, and that’s what leads to unmatched business success. So, it’s here that we come across a crucial question. How do enterprises and organizations leverage data to gain crucial insights into consumer preferences? Well, data extraction and mining are the two significant processes in this context. Let’s take a look at what data extraction means as a process.

Decoding data extraction

Businesses across the globe are trying their best to retrieve crucial data. But, what is it that’s helping them do that? It’s here that the concept of data extraction comes into the picture. Let’s begin with a functional definition of this concept. According to formal definitions, ‘data extraction’ refers to the retrieval of crucial information through crawling and indexing. The sources of this extraction are mostly poorly-structured or unstructured data sets. Data extraction can prove to be highly beneficial if done in the right way. With the increasing shift towards online operations, extracting data from the web has become highly important.

The emergence of ‘scraping’

The act of information or data retrieval gets a unique name, and that’s what we call ‘data scraping.’ You might have already decided to pull data from 3rd party websites. If that’s what it is, then it’s high time to embark on the project. Most of the extractors will begin by checking the presence of APIs. However, they might be unaware of a crucial and unique option in this context.

Automatic data support

Every website lends virtual support to a structured data source, and that too by default. You can pull out or retrieve highly relevant data directly from the HTML. The process is termed as ‘web scraping’ and can ensure numerous benefits for you. Let’s check out how web scraping is useful and awesome.

Any content you view is ready for scraping

All of us download various stuff throughout the day. Whether it is music, important documents or images, downloads seem to be regular affairs. When you are successful in downloading any particular content of a page, it means the website offers unrestricted access to your browser. It won’t take long for you to understand that the content is programmatically accessible too. On that note, it’s high time to work out effective reasons that define the importance of web scraping. Before opting for RSS feeds, APIs, or other conventional data extraction methods, you should assess the benefits of web scraping. Here’s what you need to know in this context.

Website vs. APIs: Who’s the winner?

Site owners are more concerned about their public-facing or official websites than the structured data feeds. APIs can change, and feeds can shift without prior notifications. The breakdown of Twitter’s developer ecosystem is a crucial example for this.

So, what are the reasons for this downfall?

At times, these errors are deliberate. However, the crucial reasons are something else. Most of the enterprises are completely unaware of their structured data and information. Even if the data gets damaged, altered, or mangled, there’s no one to care about it.

However, that isn’t what happens with the website. When an official website stops functioning or delivers poor performance, the consequences are direct and in-your-face. Quite naturally, developers and site owners decide to fix it almost instantaneously.

Zero-rate limiting

Rate-limiting doesn’t exist for public websites. Although it’s imperative to build defences against access automation, most of the enterprises don’t care to do that. It’s only done if there are captchas on signups. If you aren’t making repeated requests, there are no possibilities of you being considered as a DDOS attack.

In-your-face data

Web scraping is perhaps the best way to gain access to crucial data. The desired data sets are already there, and you won’t have to rely on APIs or other data sources for gaining access. All you need to do is browse the site and find out the most appropriate data. Identifying and figuring out the basic data patterns will help you to a great extent.

Unknown and Anonymous access

You might want to gather information or collect data secretly. Simply put, you might wish to keep the entire process highly confidential. APIs will demand registrations and give you a key, which is the most important part of sending requests. With HTTP requests, you can stay secure and keep the process confidential, as the only aspects exposed are your site cookies and IP address. These are some of the reasons explaining the benefits of web scraping. Once you are through with these points, it’s high time to master the art of scraping.

Getting started with data extraction

If you are already eager to grab data, it’s high time you work on the blueprints for the project. Surprised? Well, data scraping or rather web data scraping requires in-depth analysis along with a bit of upfront work. While documentations are available with APIs, that’s not the case with HTTP requests. Be patient and innovative, as that will help you throughout the project.

2. Data fetching

Begin the process by looking for the URL and knowing the endpoints. Here are some of the pointers worth considering:

- Organized information: You must have an idea of the kind of information you want. If you wish to have it in an organized manner, rely on the navigation offered by the site. Track the changes in the site URL while you click through sections and sub-sections.
- Search functionality: Websites with search functionality will make your job easier than ever. You can keep on typing some of the useful terms or keywords based on your search. While doing so, keep track of URL changes.
- Removing unnecessary parameters: When it comes to looking for crucial information, the GET parameter plays a vital role. Try looking for unnecessary and undesired GET parameters in the URL, and removing them from the URL. Keep the ones that’ll help you load the data.

2. Pagination comes next

While looking for data, you might have to scroll down and move to subsequent pages. Once you click to Page 2, ‘offset=parameter’ gets added to the selected URL. Now, what is this function all about? The ‘offset=parameter’ function can represent either the number of features on the page or the page-numbering itself. The function will help you perform multiple iterations until you attain the “end of data” status.

Trying out AJAX

Most of the people nurture certain misconceptions about data scraping. While they think that AJAX makes their job tougher than ever, it’s actually the opposite. Sites utilising AJAX for data-loading ensures smooth data scraping. The time isn’t far away when AJAX will return along with JavaScript. Pulling up the ‘Network’ tab in Firebug or Web Inspector will be the best thing to do in this context. With these tips in mind, you will have the opportunity to get crucial data or information from the server. You need to extract the information and get it out of the page markup, which is the most difficult or tricky part of the process.

Unstructured data issues

When it comes to dealing with unstructured data, you will need to keep certain crucial aspects in mind. As stated earlier, pulling out the data from page markups is a highly critical task. Here’s how you can do it:

1. Utilising the CSS hooks

According to numerous web designers, the CSS hooks happen to be the best resources for puling data. Since it doesn’t involve numerous classes, CSS hooks offer straightforward data scraping.

2. Good HTML Parsing

Having a good HTML library will help you in ways more than one. With the help of a functional and dynamic HTML parsing library, you can create several iterations as and when you wish to.
Knowing the loopholes

Web scraping won’t be an easy affair. However, it won’t be a hard nut to crack either. While knowing the crucial web scraping tips is necessary, it’s also imperative to get an idea of the traps. If you have been thinking about it, we have something for you!

- Login contents: Contents that require you to login might prove to be potential traps. It reveals your identity and wreaks havoc on your project’s confidentiality.

- Rate limiting: Rate limiting can affect your scraping needs both positively and negatively, and that entirely depends on the application you are working on.

Source:-https://www.promptcloud.com/blog/how-easy-is-data-extraction

Friday, 21 July 2017

How Hedge Funds Can Use Web Scraping

How Hedge Funds Can Use Web Scraping

Web scraping or data extraction is the need of the hour to make sense of the huge and varied data being generated across multiple sources on the web. Irrespective of the sector you are working in, data extraction and mining is a crucial necessity to glean insights into consumer behavior, market forces, competitive intelligence, and price movements, and assist in management decision making.

There’s no denying the fact that numerous brands and enterprises are leveraging data extraction for further development and growth. Of late, hedge fund owners too are showing a huge affinity to utilizing the prowess of web scraping for unlocking new investment opportunities.

What we need to know is how web scraping is helping out hedge fund owners. What is it that makes web scraping essential for them and how can they use the technology to their advantage?
Fund management with web scraping

For a majority of discretionary fund managers, web scraping is a relatively new term. Although data scientists are aware of the concept, they might not have the right skills that lead to effective use of web scraping and data extraction. So, how does hedge fund management take place now? Let’s take a look at the current processes.

Most of the hedge funds have dedicated and centralized teams looking after the data extraction process. They have a group which is continuously looking for crucial data thus extracting it for more information. Once they find what they are looking for, they seek assistance from skilled data scientists who prepare comprehensive reports on the key findings. Based on these reports, managers have to take significant steps and implement crucial business strategies.

It’s here that the major problem arises. Most of these managers aren’t aware of the technicalities involved in data extraction. They don’t know what to do with these reports when it comes to devising business strategies.
The need for effective techniques

What you need is a comprehensive and integrated approach towards the entire process. Data scientists and business managers should have crystal clear understanding of web scraping thus working in tandem for better results. Here’s how they can work together:

1. Portfolio managers: PMs will need to develop a comprehensive understanding of trading strategies along with the power to explain his understandings. He should have the power to identify alpha opportunities.

2. Data scientists: Data scientists should know the art of data mining thus ingesting the findings into a database.

Simultaneous operations should take place where PMs, data scientists, and web scraping experts will take active parts. In a nutshell, business owners need highly efficient quant teams capable of extracting quant data sets.
The steps around web scraping for hedge funds

If you are managing hedge funds, data extraction and web scraping will be essential for you. Before knowing how to use this particular technique, make sure you gain information about the crucial steps that lead to web scraping.

•   Gaining access to data sets: Without the right data sets, it is impossible to perform web scraping. Data scientists and PMs must put their best efforts to find the correct information. It can come from internal divisions, external publications, or even from social media.

•   Understanding the financial drivers: You should know about the financial drivers involved in the process. Web scraping will depend on these key drivers to a great extent.

•   Quant vs. fundamental: There’s always a debate between data quants and fundamental knowledge. The prime emphasis should always be on identifying the insights, working on them, and turning them into effective actions.

With these steps in mind, you can plan the fund management process in detail thus taking the venture towards unsurpassed growth. Hedge fund owners have been relying on fundamental knowledge since a long time; it is high time they made a move and embraced web scraping.

Current positions and prospects

If market reports are anything to go by, you will come across nearly 70 hedge funds who claim to leverage big data. Once you take a closer look, the entire situation will get revealed. Only 20 amongst these 70 hedge funds work with Big Data and rely on web scraping techniques. Market reports also suggest that only a few of them are good at performing the process.

Web scraping is going to be the future! Just after a few years, hedge fund owners will have to rely on web scraping for effective fund management. Therefore, it’s high time to upgrade performances, processes, and operations. Those getting introduced to the concept for the first time should learn the art of performing web scraping and data extraction.

Building strong and effective financial models

Do you feel the existing infrastructure is enough to leverage web scraping? That’s not true, as there are numerous other aspects involved in the process. The presence of a strong and reliable financial model is of paramount significance. Financial models play a highly significant part in the utilization of technologies. If you are thinking of implementing web scraping, check the financial infrastructure and support your venture offers to you.

The third wave

Before the emergence of web scraping and data extraction, hedge fund owners relied on traditional data mining techniques. Those weren’t effective to a great extent, as they failed to offer targeted insights into the extraction process.

It’s here that the need for a third wave came up, and web scraping was what we all waited for. With this new and innovative technology, hedge fund managers will be able to utilize insights to stay ahead of the growth curve!

Final thoughts

Hedge fund management involves quite a few significant processes in order to yield the benefits expected by senior management of the company. However, if you are planning to use web scraping, it is important to know the right tips to do so. Most of the data scientists want to bridge the gap between fundamental fund management and web scraping. It is quite obvious that the latter is beneficial in the long run. With these tips and web scraping techniques in mind, you can ensure targeted hedge fund management and handling.

Source:https://www.promptcloud.com/blog/how-hedge-funds-can-use-web-scraping

Friday, 30 June 2017

Web Scraping using Chrome Scraper Extension

Do you want to get data from a web page or website to CSV or Excel Spreadsheet? The answer is web scraping. There are number of web scraping software and services available in the market like Visual Web Ripper, Mozenda, Kimono Labs, Outwit Hub, ScraperWiki and Automation Anywhere etc. for web data extraction. These all tools and services are paid and not easy to use for non-technical persons. Now I am going to discuss another method of doing web scraping that is easy to use and free.  There are various Google Chrome browser extensions available at Google Web Store (https://chrome.google.com/webstore/category/apps) using that we can do screen scraping/web scraping.

1. Web scraper
Official Website: http://www.webscraper.io

Install it by visiting following link:

https://chrome.google.com/webstore/detail/scraper/mbigbapnjcgaffohmbkdlecaccepngjd

Web Scraper is a chrome extension for scraping data out of web pages to Excel Spreadsheet or database. It allows you to create a plan/sitemap. According to that plan/sitemap a website is traversed and the data is extracted. The extracted data can be exported to CSV or stored in CouchDB. It also supports scraping from multiple pages with pagination. You can use Web Scraper for scraping multiple types of data like text, tables, images, links and more. It also supports web data extraction from dynamic web pages built up with modern web technologies like JavaScript and AJAX.

2. Data Miner
Install DataMiner by visiting following link:

https://chrome.google.com/webstore/detail/dataminer/nndknepjnldbdbepjfgmncbggmopgden

DataMiner is a standalone chrome browser plugin for extracting data from the websites. Later on extracted data can be exported to Microsoft Excel spreadsheets or Google Sheets.

Using DataMiner extension, you can scrape data from tables and lists on the websites and easily export them into CSV file or Microsoft Excel. It also supports XPath selectors. You can use it for scraping emails, Google search results, HTML tables etc.



3. Screen Scraper:
Install it by visiting following link:

https://chrome.google.com/webstore/detail/screenscraper/pfegffhjcgkneoemnlniggnhkfioidjg

Screen Scraper is another chrome scraper as it name suggest is a Chrome browser extension/plugin for screen scraping. Screen scraping is the process of automatically scraping/extracting information from websites. Later on, Scraped information can be downloaded as a CSV file or JSON file. It supports Element Selectors and Xpath Selectors method.

4. iMacro
Official Website of iMacro: http://imacros.net/

Install iMacro it by visiting following link:

https://chrome.google.com/webstore/detail/imacros-for-chrome/cplklnmnlbnpmjogncfgfijoopmnlemp?hl=en

iMacro is a macro recorder for your Google Chrome browser. Macro recorder is a piece of tool that records user actions. It allows users to record repetitious tasks on the web and replay it at later time. It is useful tool for web automation, data extraction and web testing. Using iMacros you can remember passwords, fill out web forms, download files and possibilities are endless. iMacros is useful to Web developers for web regression testing, performance testing and web transaction monitoring. To use iMacros you just need to record the task once and save it in your machine next time when you need to perform the same task you need not repeat the same task again and again. iMacro plugin comes for Chrome, Firefox and Internet Explorer too.

Source url :-http://webdata-scraping.com/web-scraping-using-chrome-scraper-extension/

Tuesday, 20 June 2017

Six Tools to Make Data Scraping More Approachable

What is data scraping?

Data scraping is a technique in which a computer program/software extracts data from a website, so it can be used for other purposes.Scraping may sound a little intimidating, but with the help of scraping tools, the process can be a lot more approachable. The tools are used to capture data you need from specific web pages quicker and easier.

Let your computer do all the work

It takes only a few minutes for systems to recognize each others codes even in huge databases. Computers have their own language and that is why some of these tools make it easier to pull and format information in a way that is simpler for people to reuse.

Here is a list of some data scraping tools:

1.Diffbot

What makes this tool so likable is the business-friendly approach. Tools like Diffbot are perfect for searching through competitors work and the performance of your own webpage. Get product data from images, articles, discussions, web crawling tools and process websites. If you like how this sounds, see for yourself and sign up for their 14-day free trial.


2.Import.io

Import.io can help you easily get the information from the any source on the web. This tool can get your data in less than 30 seconds, depending on how complicated the data is and its structure in the website.  It can also be used for multiple URL scraping at once.

Here is one example: Which city of California based organizations try to hire the most through Linkedin? Check this list of jobs available in linkedin, download a csv file, sort from A to Z the cities and voila – San Francisco it is. Did you know that it’s for free?

3.Kimono

Kimono gives you easy access to APIs created for various web pages. No need to write any code or install any software to extract data. Simply paste the URL into the website or use a bookmark. Select how often you want the data to be collected and it saves it for you.

4.ScraperWiki

ScraperWiki gives you two choices – extract data from PDFs or build your own scraping tool in PHP, Ruby and Python language. It is meant for more experienced users and offers consulting (a paid service) if you need to learn some coding to get what you need. The first two PDF files are analyzed and reorganized for free, afterwards it’s a paid solution.

5.Grabz.it

Yes, Grabz.it does grab something. It takes information that is meaningful to you. The tool extracts data from the web, then converts videos into animated GIF that you can use on your website or application. This tool was made for those who code in ASP.NET, Java, JavaScript, Node.js, Perl, PHP, Python and Ruby languages.

6.Python

If programming is the language you love the most, then use Python to build your own scraping tool and get the data from a page you want to explore. It is particularly useful if the other tools don’t recognize the data you need.

If you haven’t used this tool before, follow this playlist of videos to learn how to use Python for web scraping:

If you want more tools, look into the Common Crawl organization. It is made for those who are interested in the data crawling world. Need a more specific tool? DMOZ and KDnuggets have lists of other tools for web data mining.

All of these tools extract information in spreadsheet formats and that is why this webinar about how to work with data in Excel can help you understand more about what to do if you desire  to supply the world with unique and beautifully data visualizations.



Source Url:-https://infogr.am/blog/six-tools-to-make-data-scraping-more-approachable/

Tuesday, 13 June 2017

Things to Consider when Evaluating Options for Web Data Extraction

Things to Consider when Evaluating Options for Web Data Extraction

Web data extraction possess tremendous applications in the business world. There are businesses that function solely based on data, others use it for business intelligence, competitor analysis and market research among other countless use cases. While everything is good with data, extracting massive data from the web is still a major roadblock for many companies, more so because they are not going through the optimal route. We decided to give you a detailed overview of different ways by which you can extract data from the web. This could help you make the final call while evaluating different options for web data extraction.

Different routes you can take to web data

Although different solutions exist for web data extraction, you should opt for the one that’s most suited for your requirement. These are the various options you can go with:

1. Build it in-house

2. DIY web scraping tool

3. Vertical-specific solution

4. Data-as-a-Service

1.   Build it in-house

If your company is technically rich, meaning you have a good technical team that can build and maintain a web scraping setup, it makes sense to build a crawler setup in-house. This option is more suitable for medium sized businesses with simpler requirements when it comes to data. However, building an in-house setup is not the biggest challenge- maintaining it is. Since web crawlers are really fragile and are vulnerable to the changes on target websites, you will have to dedicate time and labour into the maintenance of the in-house crawling setup.

Building your own in-house setup will not be easy if the number of websites you need to scrape are high or the websites aren’t using simple and traditional coding practices. If the target websites use complicated dynamic code, building your in-house setup becomes a bigger hurdle. This can hog your resources especially if extracting data from the web is not a competency of your business. Scaling up with your in-house crawling setup could also be a challenge as this would require high end resources, an extensive tech stack and a dedicated internal team. If your data needs are limited and the target websites simple, you can go ahead with an in-house crawling setup to cover your data needs.

Pros:

- Total ownership and control over the process
- Ideal for simpler requirements

2.   DIY scraping tools

If you don’t want to maintain a technical team that can build an in-house crawling setup and infrastructure, don’t worry. DIY scraping tools are exactly what you need. These tools usually require no technical knowledge as such and can be used by anyone who is good with the basics. They usually come with a visual interface where you can configure and deploy your web crawlers. The downside however, is that they are very limited in their capabilities and scale of operation. They are an ideal choice if you are just starting out with no budgets for data acquisition. DIY web scraping tools are usually priced very low and some are even free to use.

Maintenance would still be a challenge that you have to face with the DIY tools. As web crawlers are susceptible to becoming useless with minor changes in the target sites, you still have to maintain and adapt the tool from time to time. The good part is that it doesn’t require technically sound labour to handle them. Since the solution is readymade, you will also save the costs associated with building your own infrastructure for scraping.

With DIY tools, you will also be sacrificing on the data quality as these tools are not known for providing data in a ready to consume format. You will either have to employ an automated tool to check the data quality or do it manually. With these downsides apart, DIY tools can cater to simple and small scale data requirements. 

Pros:

- Full control over the process
- Prebuilt solution
- You can avail support for the tools
- Easier to configure and use

3.   Vertical-specific solution

You might be able find a data provider catering to only a specific industry vertical. If you could find one that has data for the industry that you are targeting, consider yourself lucky. Vertical specific data providers can give you data that is comprehensive in nature which improves the overall quality of the project. These solutions typically give you datasets that are already extracted and is ready to use.

The downside is the lack of customisation options. Since the provider is focusing on a specific industry vertical, their solution is less flexible to be altered depending on your specific requirements. They won’t let you add or remove data points and the data is given as is. It will be hard to find a vertical-specific solution that has data exactly the way you want. Another important thing to consider is that your competitors have access to the same data from these vertical-specific data providers. The data you get is hence less exclusive, but this may or may not be a deal breaker depending upon your requirement.

Pros:

- Comprehensive data from the industry
- Faster access to data
- No need to handle the complicated aspects of extraction

4.   Data as a service (DaaS)

Getting the required data from a DaaS provider is by far the best way to extract data from the web. With a data provider, you are completely relieved from the responsibility of crawler setup, maintenance and quality inspection of the data being extracted. Since these are companies specialised in data extraction with a pre-built infrastructure and dedicated team to handle it, they can provide this service to you at a much lower cost than what you’d incur with an in-house crawling setup.

In the case of a DaaS solution, all you have to do is provide them with your requirements like the data points, source websites, frequency of crawl, data format and the delivery methods. DaaS providers have high end infrastructure, resources and expert team to extract data from the web efficiently.

They will also have far superior knowledge in extracting data efficiently and at scale. With DaaS, you also have the comfort of getting data that’s free from noise and is formatted properly for compatibility. Since the data goes through quality inspections at their end, you can focus only on  applying data to your business. This can greatly reduce the workload on your data team and improve the efficiency.

Customisation and flexibility are other great advantages that come with a DaaS solution. Since these solutions are meant for the large enterprises, their offering is completely customisable for your exact requirements. If your requirement is large scale and recurring, it’s always best to go with a DaaS solution.

Pros:

- Completely customisable for your requirement
- Takes complete ownership of the process
- Quality checks to ensure high quality data
- Can handle dynamic and complicated websites
- More time to focus on your core business

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