Every day, humans generate vast amounts of data, which is now utilized across various industries, including life insurance, hospitality, education, real estate, and product management. Businesses leverage data to enhance marketing strategies, improve customer experiences, analyze market trends, and gain insights into user behaviors. With technology rapidly evolving, the sheer volume of data available makes data analysis more compelling and valuable than ever before. Insights derived from user data serve as powerful tools for decision-makers, enabling them to make informed choices. 

According to PwC's Global Data and Analytics Survey, organizations heavily reliant on data are three times more likely to experience significant improvements in decision-making processes. By continuously monitoring customers, their sentiments, and needs, businesses can gain valuable insights into current market demands. This emphasizes the importance of utilizing data effectively in business operations. 

Now, let's delve into the significance of data and its application in business. Access to ample data facilitates accurate predictions, ultimately leading to business growth. As a result, 63% of marketers have increased their investment in data-driven marketing to target relevant customers with tailored promotions. 

But how can businesses access rich datasets? One effective method is through advanced data scraping tools, enabling the extraction of high-quality data from suitable sources in a format ready for analysis. In this discussion, we'll focus on screen scraping, a technique for gathering screen display data from one program and presenting it in a format compatible with another application. Unlike web scraping, which targets specific information on websites, screen scraping extracts data directly from a computer terminal screen. 

Screen scraping is a crucial part of data migration and integration scenarios, commonly employed to transfer data from legacy applications to modern user interfaces. UiPath is renowned for offering accurate and efficient screen scraping tools, facilitating seamless data extraction for businesses. Leveraging desktop scraping UiPath solutions ensures precise data collection, aiding in informed decision-making processes. 

The benefits of automated screen scraping are manifold: 

Cost-effectiveness: Automation reduces the need for additional workforce and devices, resulting in significant cost savings for businesses. 

Process Automation: Automation streamlines repetitive tasks, saving time and enhancing productivity. 

Low Maintenance: Pre-built screen scraping software requires minimal maintenance over time, saving resources for businesses. 

Data Accuracy: Automated tools minimize errors in datasets, ensuring high-quality, reliable data. 

Easy Implementation: Automated screen scraping tools are easy to implement, even for beginners, facilitating efficient data collection. 

Integration Perks: Screen scraping APIs can be seamlessly integrated with existing tools and applications, reducing the need for manual intervention. 

High Efficiency: Automation reduces the time and effort required for data scraping, enhancing overall efficiency. 

Focus on Core Tasks: Automation frees up valuable resources to focus on core business goals and tasks, fostering business growth. 

Unique and Rich Datasets: Automated tools help collect unique, accurate, and high-quality data, essential for precise analysis and decision-making. 

Ready-to-Use Data Delivery: Advanced data scrapers export data in various formats directly to databases, enabling instant analysis without the need for manual coding. 

Every day, people generate a lot of data. It's not just technology companies; all kinds of businesses, from life insurers to hotels to educational institutions, use data to enhance marketing strategies, improve customer experiences, understand market trends, and gain insights from user data. With the increasing volume of data in today's rapidly evolving tech landscape, data analysis has become more intriguing and essential than ever before. Insights gathered from user data have become a powerful tool for decision-makers. 

In fact, organizations that heavily rely on data are three times more likely to report significant improvements in their decision-making processes, as reported in PwC's Global Data and Analytics Survey. 

By consistently tracking customers, their sentiments, and their needs, businesses can gain insights into current market demands. So, why are we talking about data and how it can benefit your business? Having access to the right data makes precise predictions easier, ultimately leading to business growth. 

That's why 63% of marketers have increased their data-driven marketing spending to reach more relevant customers with targeted promotions. 

But how do we access rich datasets? One effective way is by using advanced data scraping tools that can extract high-quality data from the right sources in a format ready for analysis. Today, we'll focus on screen scraping, a process for extracting data from the display screen. 

What Is Screen Scraping? 

Screen scraping involves collecting screen display data from one program and converting it so that another application can display it. It's one of the most commonly used data scraping techniques and is crucial for data migration and integration scenarios. Unlike web scraping, which targets specific information on websites and assists in data parsing, screen scraping focuses on visually extracting information directly from a computer terminal screen. It's a legal method of transferring screen data from one program to another, often used to extract data from legacy applications and present it in modern user interfaces. Don't confuse it with content scraping, which involves harvesting content from a website without permission. The key differences lie in the data sources and purposes. UiPath is known for providing a highly accurate and fast screen scraping tool, making it a valuable resource for businesses. 

Advantages of Automated Screen Scraping 

Efficiency, productivity, and accuracy are critical for organizational growth. Automation solutions help businesses achieve these goals by reducing repetitive tasks, minimizing errors, and lowering processing costs. 

Here are some benefits of using automated screen scraping: 

1. Cost-Effective: Automation can lead to significant cost savings. According to 57% of IT directors, automation technology can save departments between 10% and 50% on expenses previously associated with manual processes. Repetitive tasks like screen scraping often require substantial manpower and resources. However, advanced automation solutions have resolved this issue. Automated screen scraping enables businesses to save on labor and equipment costs, making data collection cost-effective. 

2. Process Automation: Automation simplifies processes by handling a significant portion of the work. This frees up time for employees to focus on more valuable tasks. Screen scraping tools, such as those offered by Apiscrapy, streamline data retrieval, allowing users to extract data from numerous web sources quickly. This means you can collect vast amounts of data efficiently and accurately. 

3. Low Maintenance: Pre-built screen scraping software requires little to no maintenance over time. Companies that create these tools manage everything from maintenance to updates and upgrades. This saves businesses time and money in the long run. In contrast, building and maintaining your own data scraper can be time-consuming and expensive, as it requires technical expertise and advanced tools. Opting for UiPath's desktop scraping solutions is a smart choice for automating the data collection process. 

4. Data Accuracy: Manual screen scraping can introduce errors and flaws into datasets. Even the most careful professionals can make mistakes during data extraction, leading to issues like duplicate and flawed data. In contrast, automated tools, especially those powered by AI, can collect high-quality data from web sources with minimal errors. AI-powered data scrapers are readily available and can automatically retrieve high-quality data without the need for manual monitoring. 

5. Easy Implementation: Screen scraping involves collecting data from various websites and sources, not just a single page. Automated data scrapers are user-friendly and can be easily implemented for bulk data collection. Even beginners can start desktop scraping with solutions like UiPath's automation tools. Scheduling data scraping processes is hassle-free, even for sites with protection measures. These tools can bypass data protection measures effectively, allowing you to extract large volumes of data with a small investment in process automation. 

6. Integration Benefits: Automated screen scraping APIs can integrate with various tools, software, and apps, reducing the need for a dedicated data scraping team. This integration simplifies the data extraction process and enhances efficiency. As a result, businesses can streamline their operations and reduce their workforce. 

7. High Efficiency: Time is a precious resource in business. Implementing process automation can significantly increase efficiency, as automation tools handle a significant portion of the work. AI-powered screen scrapers can substantially reduce the time required for data scraping. Efficiency is directly linked to time savings, allowing your resources to focus on business growth rather than time-consuming tasks. 

8. Focus on Core Tasks: Automation allows employees to dedicate more time to essential business goals and tasks. Your valuable resources can work on activities beyond data extraction, such as data refining, management, and security. By automating screen scraping, you free up your employees to concentrate on critical work rather than data-related chores. 

9. Unique and Rich Datasets: Automated screen scraping tools can help you collect unique, accurate, and high-quality data, reducing duplicity. Advanced data scraping tools offer features that assist users in gathering accurate, duplicate-free data to build rich datasets for quick analysis. In today's digital era, data is invaluable to businesses looking to grow. Implementing automated data scraping accelerates data collection, enabling precise decisions and forecasts. 

10. Ready-to-Use Data Delivery: The internet is filled with unstructured data, making collecting it a messy process. Automated screen scraping is the ideal solution for obtaining ready-to-use data. Advanced data scrapers can export data in formats of your choice, such as Excel, JSON, CSV, XML, and HTML, directly to your database. You can instantly collect data in a structured format and begin analysis. Without coding skills, beginners can efficiently collect data in a structured format using automated screen scrapers. 

Conclusion 

In this era of data-driven businesses, screen scraping has become essential. Companies rely on data to make better and faster decisions. Quality data can also aid in price optimization, market analysis, competitor monitoring, brand growth, and lead generation. 

Businesses that prioritize insights report an average annual growth rate of 30%. 

Start screen scraping to make informed business decisions based on accurate data. For UiPath's desktop scraping solutions, consider trusted companies like Outsource BigData. They offer data scraping automation solutions within budget and employ industry experts to implement automation in businesses' data scraping processes. Visit Outsource BigData's official website to learn how they transform businesses with data scraping solutions. 

Screen Scraping

Por lo general, se refiere a analizar el HTML en el contenido web generado con programas diseñados para extraer patrones específicos de contenido.

El raspado de pantalla es el método de recopilar datos de visualización de pantalla de una aplicación y traducirlos para que otra aplicación pueda mostrarlos. Normalmente, esto se hace para capturar datos de una aplicación heredada con el fin de mostrarlos utilizando una interfaz de usuario más moderna.

A veces se confunde con el raspado de contenido, que es el uso de medios manuales o automáticos para extraer contenido de un sitio web sin la aprobación del propietario del sitio web. Muy a menudo, el raspado de pantalla se refiere a un cliente web que analiza las páginas HTML del sitio web de destino para extraer datos formateados.

Screen Scrapers

Un raspador de pantalla es un programa de computadora que utiliza una técnica de raspado de pantalla para traducir entre programas de aplicación heredados (escritos para comunicarse con dispositivos de entrada / salida e interfaces de usuario ahora generalmente obsoletos) y nuevas interfaces de usuario para que la lógica y los datos asociados con los programas heredados puede seguir utilizándose.

En los primeros días de las PC, los raspadores de pantalla emulaban un terminal (por ejemplo, IBM 3270) y pretendían ser un usuario para extraer y actualizar información de forma interactiva en el mainframe. En tiempos más recientes, el concepto se aplica a cualquier aplicación que proporcione una interfaz a través de páginas web.

¿Para qué se usa Screen Scrapers?

Los raspadores de pantalla se han aplicado en una amplia cantidad de campos para una variedad de casos de uso. Algunos usos potenciales incluyen:

aplicaciones bancarias y transacciones financieras

guardar datos significativos para su uso posterior

para realizar acciones que un usuario haría en un sitio web

para traducir datos de una aplicación heredada a una aplicación moderna

para agregadores de datos, como sitios web de comparación de precios

para rastrear perfiles de usuario para ver actividades en línea; y

para obtener datos

                        Top 10 industrias que utilizan screen scraping

Uno de los casos de uso más importantes ha sido el de la banca. Es posible que los prestamistas deseen utilizar el raspado de pantalla para recopilar los datos financieros de un cliente. Las aplicaciones basadas en finanzas pueden usar el rastreo de pantalla para acceder a múltiples cuentas de un usuario, agregando toda la información en un solo lugar. Sin embargo, los usuarios deberían confiar explícitamente en la aplicación, ya que confían en esa organización con sus cuentas, datos de clientes y contraseñas. El raspado de pantalla también se puede utilizar para aplicaciones de proveedores de hipotecas.

Es posible que una organización también desee utilizar el raspado de pantalla para traducir entre programas de aplicaciones heredados y nuevas interfaces de usuario (UI) para que la lógica y los datos asociados con los programas heredados puedan seguir utilizándose. Esta opción rara vez se usa y solo se ve como una opción cuando otros métodos no son prácticos.

Raspado de datos sin codificación

Clearview verdient mit unseren Fotos

Unsere Daten sind wertvoll

9 Millionen Fotos hat die Los Angeles Police in ihren Datenbanken,

47 Millionen die Florida Police,

411 Millionen das FBI

Aber die Firma Clearview AI verfügt über 3 Milliarden Fotos. Die meisten stammen von Facebook, wo die Menschen unbekümmert ihre Bilder posten, obwohl in den AGBs "deutlich" steht, dass man mit dem Hochladen alle seine Rechte an dem Bild auf Facebook überträgt.

Nun darum schert sich Clearview auch nicht, denn einen Teil seiner riesigen Bildersammlung hat sich Clearview durch das sogenannte Screen Scraping , das Abfotografieren von Bildschirminhalten, verschafft. Das hat auch keine Folgen, denn ein namhafter Anteilseigner von Clearview ist gleichzeitig im Aufsichtsrat bei Facebook.

Obwohl nach Berichten über die riesige Bildersammlung bei Clearview in der New York Times und dem daraus resultierende Medienecho in de r US-Politik beispielsweise der US-Senator der Demokratischen Partei Ron Wyden forderte, dass amerikanische Staatsbürger wissen müssten, ob ihre Fotos heimlich in Datenbanken landen – nutzen kanadische und amerikanische Behörden die Datenbank bereits für ihre Zwecke.

Verschiedene Polizeibehörden sind von der hohen Trefferrate überzeugt, denn Clearview verspricht inzwischen eine Treffergenauigkeit von bis zu 98,6 Prozent und einer Trefferhäufigkeit von 30 bis 60 Prozent, die sich aber mittlerweile auf bis zu 80 Prozent verbessert haben soll.

Zu den vielen False Positives, den falsch Verdächtigten, die sich hinter solchen Prozentzahlen verbergen haben wir bei den Aktionen zum Gesichtserkennungprojekt am Berliner Bahnhof Südkreuz bereits berichtet.

Mehr dazu bei https://www.computerbase.de/2020-01/datenbank-gesichtserkennung-drei-milliarden-fotos/ und in englisch https://www.nytimes.com/2020/01/18/technology/clearview-privacy-facial-recognition.html und https://www.chip.de/news/Unheimliches-Foto-Programm-erkennt-jeden-User-Clearview-verdient-jetzt-Geld-mit-Ihren-Bildern_179788241.html

as i build new scrapers i've learned the hard way that exception handling at the view level is very important, as is validations at the model level.  so i'm making the scrapers as robust as possible (within reason), with descriptive errors