Mozenda Tech Blog

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Where Does Data Come From? | Visual.ly

Data is constantly increasing and comes from many different sources. Tracking down this data would be difficult without the help of web scraping softw

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Google Closes Its Freebase Knowledge Base

Recently, Google announced that it will be shutting down Freebase, the crowdsourcing knowledge base that it acquired upon purchasing Metaweb in 2010. Fans of Freebase have enjoyed the popular outlet due to its incredible volume of information covering over 46 million different topics from music to meteorology. For recreational users and web scraping specialists alike, the system could be both searched and queried like a database. Needless to say, many will miss the services provided by Freebase.

Wikidata to Take Charge

According to recent reports, Wikidata will take over where Freebase left off with her mass amount of digital information. By the end of March, Freebase’s data will begin being exported to Wikidata, ending with the formal retirement of Freebase come June 30, 2015. Heavily praised by web scraping experts and big data enthusiasts over the years, Freebase’s database helped develop Google’s fast-growing Knowledge Graph. Oddly enough, the Freebase developer APIs will be replaced by the very set of Knowledge Graph powered ones that Freebase actually helped create. 

The Reason Behind Such a Change

In a statement released through their Google+ page, said Freebase, “We believe strongly in a robust community-driven effort to collect and curate structured knowledge about the world, but we now think we can serve that goal best by supporting Wikidata — they’re growing fast, have an active community, and are better-suited to lead an open collaborative knowledge base.” Even in the digital realm, many things come full circle.

More Than an Information System

Though a source of information for professionals of the web scraping industry and typical Internet users, the real value of Wikidata isn’t solely found in its information — much of which is already made readily available for people on Wikipedia — but in its structured format. In the near future, as smarter search engines become more commonplace, Wikidata’s structured format will help them become more efficient at seeing, identifying and reacting to searched terms.

Lucas Miller is a tech writer. Information provided by Mozenda. He writes for Fusion 360, an advertising agency in Utah. Find him on Google+.

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Web Scraping’s Future Involvement In Campaigns Like the ALS Ice Bucket Challenge

This past summer, America witnessed an incredible awareness campaign: the ALS Ice Bucket Challenge. According to Facebook estimates, nearly 28 million people posted about the challenge — be it through a video, comment or tag — between June 1 and August 28. 

Furthermore, on YouTube alone 2.4 million videos were shot and shared, raising understanding as to the difficulties associated with amyotrophic lateral sclerosis, more commonly known as “Lou Gehrig’s Disease.” 

While most Americans may have fond memories of the promotional venture, the big data behind the campaign reveals an interesting truth: as a society, we’ve been equipped for this sort of global, groundbreaking movement for decades, yet have done nothing about it.

Posing an interesting question is Jay Goulart, Founder and Chief Data Artist for NewSci, LLC: “Would you be willing to cross the busiest street in your area blindfolded with information five minutes old? In response to his own question, says Goulart, “The nonprofit sector is taking that walk daily with dated systems unable to develop strategy effectively and in real time.”

Truthfully, Goulart is spot on with his claim. Every single day, we build upwards of 2.5 quintillion bytes of data. In fact, in the past two years, we’ve created 90 percent of all the data the world has ever known. Shocking as it may seem, it’s even more startling to think of the data that we’ve put into nonprofit databases. 

Says IdmBigDataHub.com of the nonprofit sector’s lack of big data prowess, “In the nonprofit sector, the pace of strategy creation over the last five decades has been set by the speed at which humans manually input information into data fields.”

If there was ever an industry to benefit from the perks of web scraping, it’s the realm containing all the world’s nonprofit organizations. Web scraping is a computer software technique which helps individuals extract complex information from any and all websites found on the World Wide Web. 

For example, imagine the good that could’ve been accomplished through web scraping if those responsible for the construction of the Ice Bucket Challenge platform were able to — of the 2.4 million YouTube videos — identify those directly or indirectly affected by Lou Gehrig’s Disease. 

Through precious data collected via web scraping, important connections could’ve been formed between the afflicted who participated in the Ice Bucket Challenge and other ALS supporters already housed in more traditional databases.

Additionally, with the help of expert web data extractors and big data analysts, future nonprofit organizations can not only customize messages according to audience, but direct them toward more meaningful segments of society. 

If such a practice were put into place, it can safely be assumed that active campaign participation would lead to an exponential increase in successful donation obtainment. Through web scraping, all stand to benefit.

Lucas Miller is a tech writer. Information provided by Mozenda. Lucas writes for Fusion 360, an advertising agency in Utah. Find him on Google+.

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Understanding the Differences Between Unstructured, Semi Structured, and Structured Data

Big data is a hard enough concept for some people to grasp, especially considering that many people don’t even know what it is or that their business can greatly profit from sorting through it. To make things more complicated, data can fall into one of three categories: unstructured, semi-structured, and structured data.

While all of this data may be hard to manage, web scraping software exists to take this information and translate it into easily readable documents that companies can use for a variety of reasons. First, though, companies may benefit from understanding the differences between unstructured, semi-structured and structured data. 

Structured data is considered structured because when it was placed in a database, a set structure or form was forced upon it. This type of data is easy for web scraping software to sort through because it is all in the same format. 

Unstructured data becomes a little more complicated. For the most part, anything that isn’t considered structured is considered unstructured. This data is more complicated to harvest, but with web scraping software it can be done easily and efficiently. Unstructured data usually contains multi media such as images, videos, or audio files. Because of its multidimensionality, it is considered unstructured. 

Semi-structured data, as can likely be guessed, falls somewhere between structured and unstructured. If data has any type of structure and carries a tag, it is easier to organize and analyze, especially with the use of a web scraping tool. Oftentimes, semi-structured data is classified as unstructured, such as text (like e-mails), web server logs and search patterns, and sensor data.

Any type of data can be immensely useful for a business. With the aid of a web scraping tool, companies can better gather and utilize data and help put them a step ahead of the competition.

Rachel Wood is a tech writer. Information provided by Mozenda. Rachel writes for Fusion 360, an advertising agency in Utah. Find her on Google+.

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3 Ways Businesses Use Web Scraping

Remain Competitive

As the amount of online data increases, prominent organizations become more data driven. In fact, several of the top American companies use data extraction to improve almost everything they do. Although change can be daunting, companies that want to remain competitive realize that web scraping is an incredible technique that has the ability to transform their business for the better.

Gain Customer Insight

Originally, companies had to look at individual sources of data to find information about their customers. However, web scraping is changing this technique. Contemporarily, businesses use big data to gather and sort information from a broad range of sources that help them better understand their clients. For example, a company could might use web scraping to look at their clients purchase history as well as their social media to create more efficient marketing based on their audience’s preferences.

A company can also use data extraction to develop their future products and services. For example, a company can collect online data to understand what their target audience is purchasing and create a product based on their targets’ preferences.

Improve Operations

Data extraction is also enabling various types of companies to improve their everyday business operations. For example, various call centers use data extraction to analyze several sources and determine what type discount they should offer their clients.

Many insurance companies have also started to use data scraping to improve their businesses. These companies use web scraping to spot potential fraud and flag suspicious content for their fraud specialists.

Although data extraction is a relatively new technique, it’s quickly growing in popularity. Today, many prominent companies use data extraction to remain competitive, increase their understanding of a target audience and improve their operations.

Mackenzie Martin in a technology writer and Mozenda provided the information for this piece. Mackenzie writes for Fusion 360, an advertising agency in Utah. Find her on Google +.

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Data vs. Quality Data: Yes, There’s a Difference

In the world of information gathering, there is a big difference between run-of-the-mill data and quality data. Companies that use web crawlers to collect online information end up with a lot of useless, extraneous data. 

Web scraping, or data extraction, is rigorous software that has the capability of processing and organizing huge amounts of complex data quickly and effectively. The “effectively” characteristic of web scraping is what sets it apart from web crawlers. 

Web crawlers are not as adept at distinguishing quality data from irrelevant data. As a result, some findings within the document produced are useless, or worse, the entire data within the document becomes skewed and thereby useless. 

Alternatively, web scraping allows users to customize the information extracting process--resulting in a more refined and thus more useful document for analysis. 

For example, imagine an online business on a mission to gather the pricing index from multiple online stores to gauge the prices of their competitors. If the company didn’t use sophisticated data extraction software, the end result may contain a bunch of useless html coding data. 

Data extraction is the most effective and cost-efficient way to sift through coded html and translate it into a readable document, while simultaneously gathering the information that is relevant to the user. 

As companies that provide web scrapers refine their methods, more industries are beginning to take advantage of the technology including: healthcare, finance, online business, marketing, journalism and academia. 

The information age continues to churn out more information everyday at an accelerated pace. But its availability is limited to those who have the means to capture it. 

Mitchell Reber is a tech writer. Information provided by Mozenda. Mitchell writes for Fusion 360, an advertising agency in Utah. Find him on Google+

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How Web Scraping is Changing Internet Security

Web scraping and data extraction can be used in so many fields today; the options are almost endless. Online security companies are now looking to use big data and data gathering processes to help protect Internet users from becoming victims of cyber attacks. 

Web scraping software has the ability to gather large amounts of encrypted data quickly and efficiently. What may take hours for 30 or 40 people, the software can accomplish simply and quickly. Technicians see the ability for this type of data extraction to be used for security purposes.

Data extraction tools can be used to monitor large amounts of data in a given system. Through this extensive monitoring, data can be better protected. This way, if any sort of hacker or virus is trying to infiltrate the system, it can instantly be detected. 

For companies that have very sensitive information that needs to be heavily protected, this type of security software is highly coveted. Any means of guarantying that information will be protected and secure is what any company wishes for. 

Additionally, companies can use this to detect internal fraud. Web scraping software can be programmed to look for specific information that indicates fraudulent activity. Companies hope to reduce internal as well as external fraud with this software that is able to monitor more extensively. 

The numbers of cyber attacks that are still occurring today show that the current security efforts in place are not effective enough. With the incorporation of this advanced technology, companies hope to see less fraudulent activity as well as better-protected data and information.

Kate Giolas is a tech writer. Information provided by Mozenda. Kate writes for Fusion 360, an advertising agency in Utah. Find her on Google+.

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Data Extraction: An Academic’s Best Friend

Doing extensive research and gathering information can take hours and hours. A great deal of data is encrypted and cannot be found with simple web searching methods. Because of this, those in the academic world can benefit greatly from web scraping and data extraction tools and tactics. Compiling complicated data into one place through web scraping to be used in the scholastic department is effective and efficient.

Decoding of extensive data for research purposes can be time consuming. Most researchers do not want to spend quality research time decoding and compiling information. Web scraping tools are able to compose data from other research done. The data gathered is then placed into organized, easy to read documents that can be quickly referenced. Having this background knowledge available to academics allows them to do more thorough research and move forward more efficiently in their field.

Obtaining statistics and numbers across the web can often times be a complicated task. This data is usually coded and encrypted within websites and cannot be always be accessed with ease. Web scraping comes in handy here, as it allows researchers to easily find web statistics and other numbers without having to do the extensive data decoding themselves.

Web scraping is such a versatile tool. It can be used across so many different platforms in many various fields. The world of academia can benefit from it greatly as it provides a quality reporting method of obtaining data. This tactic helps academics acquire better research and come to better conclusions.  

Kate Giolas is a tech writer. Information provided by Mozenda. Kate writes for Fusion 360, an advertising agency in Utah. Find her on Google+.

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Small Companies: Why They Need Screen Scraping

Small companies can benefit from screen scraping in every way. This process provides an extra helping hand in making any company great. Having a small business can be a hard undertaking for anyone, add the stress of big competition during the holiday season and it can feel overwhelming. 

Screen scraping helps organize the data and cuts out the copy and paste middleman that takes time and effort. The biggest plus to investing in screen scraping as a small company is the time saver. Having a company hired out to help get data that is beneficial to marketing and item stocking allows the employees to focus on other areas of business.

Another benefit of hiring out for screen scraping, as a small business, is it takes away the cut and paste and organizational methods. For a low price a small company can hire a screen scraping company. They will gather all the requested data and form it into an organized sheet. The company can then take this sheet and analyze it in a way that will benefit them.

Screen scraping companies do the work of 40 people and in less time. By getting the prices of competitor products a small company can offer lower prices. This is all in hopes of getting a stronger client base. The use of screen scraping is becoming a trend that is no longer reserved for big business.

Don’t let the small business get stuck in the cold this winter. Invest in a screen scraping company. 

Ciera Putnam is a tech writer. Information provided by Mozenda. She writes for Fusion 360, an advertising agency in Utah. Find her on Google+

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The Unlikely Relationship Between Air Pollution and Big Data

Recently, the World Health Organization announced that air pollution is the world’s largest single environmental health risk. However, many areas all over the world evaluate air quality differently, which makes it difficult to understand and analyze air pollution. To combat this issue, a group of researchers produced a mobile application that uses web scraping to analyze air pollution.

The application’s design is simple, but it can give its users important information, such as what parks have better air quality. Moreover, this information could help parents make informed decisions about where they will play with their kids on any given day. It might also help a family decide what neighborhood they want to move to based on air quality.

Although many believe that web scraping is the answer to understanding air pollution, other technologies are also proving promising in combating the issue. For example, a company named Oxie is contemporarily designing a wearable device that can purify the air one breathes. 

However, these two technologies are not the only innovations that are designed to protect individuals from poor air quality. When the Word Health Organization announced that the risks from air pollution are greater than researchers previously thought, many companies saw an opportunity for a successful business that provided products or services that helped protect others from air pollution.

Today, many groups are creating products with the same mission: solve air quality problems. Furthermore, these companies are not only addressing environmental factors, they’re addressing healthcare. Although healthcare and the environment are generally viewed as separate topics, web scraping and other air pollution technologies are helping individuals understand that they’re more related than ever before.

Mackenzie Martin in a tech writer. Information provided by Mozenda. Mackenzie writes for Fusion 360, an advertising agency in Utah. Find her on Google +.

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Data Extraction and Big Data: What You Need to Know

Over the last few years, big data has taken huge leaps, especially in 2014. The process of data extraction and how it is used across many companies and enterprises has been adopted at a fast rate.  We already know what has come and gone, but now we need to look to the future and see what 2015 has in store for big data analytics.

It’s no secret that big data has helped pave the way for big changes in the world of business. Companies and enterprises are benefiting from data analytics and making a huge difference in their bottom line. 

The data extraction industry sees big data not just as a luxury, but a necessity. The process is complicated and best left to the professionals. The large companies and enterprises utilizing the service often have many components of the business that need to be tracked. 

Retrieving data out of certain data sources to further process and analyze has historically used scripts to load html pages at high speed. This method consumes bandwidth and doesn’t perform well. 

Now data extraction professionals can capture information using browser parameters. This method is less taxing on a website and doesn’t require any manual copying and pasting. 

This simplifies the process so that a data extraction can be done by a software service rather than grueling human labor. These softwares are all about being easy to use and getting the job done quickly. It can be automated, stored in the cloud and published with the click of a button.

Katie Alvarez is a tech writer. Information provided by Mozenda. Katie is a writer for Fusion 360, an advertising agency in Utah. 

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What is Big Data and why should Businesses use it?

sBig data allows individuals to extract and sort large pieces of data from the web. Moreover, big data is changing the way a lot of organizations conduct their research. It’s essential that organizations understand big data in order to remain competitive in today’s business market. 

As time progresses, more and more data is created. In addition, as the volume and complexity of data increases, it becomes increasingly difficult for businesses to analyze online data in an efficient manner. Fortunately, data scraping allows individuals to collect, organize and analyze large amounts of data more efficiently than ever before. 

Regardless of what industry an organization operates in, it’s essential that they understand big data. According to a recent Gartner study, organizations that take advantage of big data will outperform companies that don’t use big data by 20 percent across several major financial measures. 

Furthermore, although data scraping and analysis can sound confusing, they don’t have to be. Thanks to data extraction companies, it’s now easier than ever for organizations to collect big data and use this information to improve their business. 

For example, data scraping companies have helped various fast food companies improve their businesses. Several major fast food vendors are now analyzing big data to improve their customer service and public relations. Furthermore, healthcare providers are using data scraping to collect and sort more information on their patients, making healthcare more personalized than ever before. 

Although many definitions of big data sound complicated, using and understanding big data has become attainable because of the work of data scraping companies. Today, data extraction companies help their clients identify, analyze and implement information in a way that improves their business. 

Mackenzie Martin in a tech writer. Information provided by Mozenda. Mackenzie writes for Fusion 360, an advertising agency in Utah. Find her on Google +.

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Uncommon Bonds: Healthcare and Big Data

Thanks to data scraping, health professionals can now gather and organize more information about their patients than ever before. Furthermore, many individuals in healthcare believe that big data will change the field for good. In the future, there is a chance that data scientists, not general Doctors of Medicine, will solve medical problems.

Today, big data allows researchers to understand more about one’s health and genetic coding than ever before. Moreover, this information is helping healthcare providers find patterns of disease and evaluate the effectiveness of treatments. 

Although data scraping is a relatively new technology, many healthcare providers are excited about the opportunities it offers. For example, the University of Irvine Medical Center is attempting to use data extraction to track and reduce the number of medical error deaths they experience every year. 

In order to do this, the center has gathered and organized all data relating to their patients’ conditions for the duration of their illnesses. This data is collected from electronic devices such as heart monitors and wearable devices. Whenever a patient’s health deteriorates, the hospital staff is notified, allowing them to reach the patient in their time of need. 

Data scraping has the opportunity to revolutionize healthcare like never before. For example, emergency response teams can now use big data to find the quickest route to an emergency, which could help save individuals who are at a significant risk, such as those in cardiac arrest. 

If data scraping is used correctly, it has the potential to personalize healthcare for every American citizen. It may also help professionals identify patients who are at risk of becoming sick or developing a serious condition, eliminating the need for many medical doctors. 

Mackenzie Martin in a tech writer. Information provided by Mozenda. Mackenzie writes for Fusion 360, an advertising agency in Utah. Find her on Google +.

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Data Mining Creates More Efficient Businesses

The way we gather information today is continuously evolving. With advanced web scraping software, the limits on the data that is available are almost nonexistent. Companies all over the world are utilizing data mining processes, now allowing people to have reserves of knowledge much faster than before.

Data mining is a tool that derives from the use of web scraping software. This process is used to analyze data from different perspectives and condense it into useful information. This information can be used for many different purposes such as increasing revenue and cash flow as well as to cut business expenditures. This analytical tool for gathering data is an excellent way to create comprehensive files of information that can be used as a reference for many different things.

This information gathering process has been used to monitor buying patterns of consumers in a given market. It shows what products are being bought, what times of the day people are doing their shopping, as well as what days of the week people are most likely to buy.

For a business to have access to this type of information is extremely valuable. This data can then be cross-referenced with inventory lists and product availability information so businesses can better serve their customers.

Knowing this type of information helps a business improve. They are able to send targeted promotions at the most efficient times. Companies can also endorse specific products more heavily that they know have been popular among customers. 

This web scraping and data mining process can also be used to eliminate waste. Finding where a business is spending money in unsuccessful ways helps cut costs. Products that are not selling and advertising tactics that are not reaching large enough audiences can be eliminated, leaving room for money to be spent in ways that are more effective.

Data mining allows for information to be gathered on a wider spectrum. Data that is readily available that can be easily read by the common user can now be gathered and compiled with complicated, computer coded data found with web scraping. 

Often this information intertwines, and so is collected into one straightforward document.  A knowledgeable business is a successful business. Data mining helps businesses become smarter, more prosperous and grow in efficiency.

As technology continues to evolve, so will the data evaluation process. In today’s day and age, there is very little knowledge that can’t be acquired. Web scraping is leading the way to a smarter and more successful marketplace.

Kate Giolas is tech writer. Information provided by Mozenda.  Kate is a writer at Fusion 360, an advertising agency in Utah. Find her on Google+.

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What is Big Data?

Bid data is comprised of large sets of data that can be analyzed. Commonly, individuals analyze big data to discover trends, patterns and associations between two or more variables. In order to collect big data, many organizations use a process called data scraping. Data scraping extracts data from online resources using specialized software. 

A popular individual in the growing field of big data, Doug Laney, believes that big data has three components: volume, velocity and variety.  Laney argues that every day, the volume of big data increases. However, it can be difficult to run analytics on this data. In order to solve this problem, Laney recommends that organizations use data scraping to make sense of contemporary big data. 

Laney also argues that velocity is a key component to big data. In general, data streams at incredible speeds, making it difficult to analyze. However, data scraping can help organizations react quickly to the increase in big data and identify today’s most important trends. 

For Laney, the last element of big data is variety. Contemporarily, data comes in several types of formats such as numeric data and unstructured data. These various formats can be difficult to organize and sort. However, businesses can solve this big data issue by hiring a data scraping company who specializes in data extraction. 

Many other prominent organizations in data scraping argue that variability and complexity are two other elements that are instrumental parts of big data. Every day, data becomes more and more complex, which makes big data more difficult to sort and understand. However, contemporary individuals who specialize in understanding are using data extraction tools to tackle the growing world of big data.

Other organizations argue that the sources of big data are instrumental to big data because as time progresses, more and more sources are contributing to big data. This trend often makes big data more difficult to understand. However, data scraping companies are experts in navigating today’s big data sources and discovering the important relationships between them. 

As big data continues to increase, many organizations are interested in using data scraping software to enhance their business. However, many companies still don’t understand why big data and data scraping are important. 

Every organization can benefit from big data. Big data has the potential to help companies that offer different products or services reduce their costs, save time and make smarter business decisions. 

For example, an online e-commerce company could use data scraping and big data to create retail coupons based on their client’s past purchases. It could also help a company determine who of their customers are the most important, which could then lead to a specific marketing plan that boosts company revenue. 

As big data continues to rise, many companies are learning the benefits of data scraping. Although these terms can seem confusing, they don’t have to be. Fortunately, there are several data scraping companies who specialize in helping their clients benefit from data scraping. 

Mackenzie Martin is a tech writer. Information provided by Mozenda. Mackenzie writes for Fusion 360, an advertising agency in Utah. Find her on Google +.

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Understanding Data Extraction

The Internet contains a plethora of data on a large amount of topics. However, it can be difficult for users to retrieve the exact data they desire from the web. Data scraping (also known as data extraction) makes information more readily available to users.

Although many companies believe that using search strategies, such as keyword searching, is enough to successfully gather data from the web, any company can benefit from data scraping. Historically, standard data collecting strategies return large amounts of data, which are difficult to understand. This difficulty leads to the development of programs called wrappers. 

Wrappers are individual programs, which identify data that an organization is interested in and then organize that data. Although wrappers are still used today, they have a major caveat. It is very difficult for a wrapper to sort out data of interest from uninteresting data, which can hinder the quality of the data it selects. Furthermore, wrappers can be extremely difficult to write and maintain.

Contemporarily, there are many web data extraction tools that have furthered data scraping efforts. For example, wrapper languages have been developed. Wrapper languages assist individuals in constructing wrappers efficiently. Although many tools, such as wrapper languages, have furthered data scraping efforts, creating and maintaining a wrapper is still extremely difficult. 

Fortunately, there are data scraping and screen scraping companies that specialize in this field. These companies have developed some of the best software tools in the world that help their clients quickly and efficiently extract information from the web. 

Today, data scraping is one of the top ways organizations collect data from the web. In fact, data extraction is rising in popularity because it is useful for a variety of businesses that offer different products and services. 

For example, a photography company can use data extraction to evaluate trending photographs. A company that sells a product as complicated as logic boards, on the other hand, can also use data scraping to compare their competitors most successful products to their own. 

Data scraping is growing in popularity because it helps companies maximize their data collecting efficiency. When data extracting was a new technique, many companies relied on manual data entry to extract data from the web. However, data extraction has eliminated this need, making companies faster and more efficient than ever. 

Data scraping is a relatively new field, but it progresses and grows in popularity every day. When data scraping was a new technology, it was used by companies with experienced programmers who could create successful wrappers, limiting other organizations’ access to the technology. Today, there are several data scraping technologies that help their non-programming and programming clients access valuable data. 

Mackenzie Martin is a technology writer. Information provided by Mozenda. Mackenzie writes for Fusion 360, an advertising agency in Utah. Find her on Google +.

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Web Scraping Info for Dummies: Data Extraction in the 21st Century

Most people have never heard the term “Web scraping,” but anyone interested in learning about it is in all probability more intelligent than the average dummy.

American consumers are not foreigners to the door-to-door salesman, nor are they so to the telemarketer with a profoundly annoying habit of calling during dinnertime. 

Web scraping accomplishes what such vendors strive to achieve, but it does so in a non-invasive, digital, far more efficient and un-annoying manner. The practice utilizes data extraction technology on the Internet to facilitate lead generation and consumer data for various purposes.

Perhaps the simplest way to think of the benefits that Web scraping offers its users as newly minted technology is through its algorithmic properties. The aforementioned door-to-door salesman and telemarketer gather their information heuristically; that is, in a way that is far more prone to human error, lost time and therefore reduced cost efficiency for businesses. 

Heuristic methods of data extraction are losing relevance because of their aforementioned downfalls. Algorithms utilized by Web scraping stand in direct opposition to heuristic data procuring methods because they are faster, dependable and far more accessible to their users.   

Among the various purposes of data extraction, is seeking insight to data analytics on the Web. Given the large movement toward metrics in business practices since the advent of the Internet, so much data is indexed on search engines and Web sites that it becomes very difficult to discern how said data extraction impacts various facets of business, technology and lead generation. 

However, Web scraping allows algorithms akin to that of a search engine’s; the ability to locate, scale and synthesize large amounts of information in an impressively small amount of time.

At this point, it becomes easy to see how such a tool can be useful and adapted to many demands. In fact, Web scraping is to data extraction what the invention of the bar graph was to data extraction. Although the latter of these two inventions evinced several hundred years ago, its various functions help us make sense of data in a sensible and compelling way; much like data extraction presently does and will increasingly continue to do in the future.

If one wonders how data extraction will benefit them, they need not look further than Google as an already established, algorithmic, data synthesizing technology. Much in the same way that Google is now the public’s library, Web scraping is on its way to being for businesses what Google is to consumers – an endless array of data that can be used for multiple purposes.   

James O’Connor is an information technology writer. Information provided by Mozenda. He is a writer at Fusion 360, an advertising agency in Utah. Find him on Google+