In today's tech-driven era, the importance of data is undeniable. The global big data analytics market is projected to grow at a compound annual growth rate of approximately 30%, with sales expected to surpass 68 billion US dollars by 2025, up from about 15 billion US dollars in 2019. In this highly competitive environment, organizations leveraging big data and analytics are poised for success. Data can be utilized for competitor analysis, market research, business monitoring, product and price optimization, among other applications. Data-driven decision-making has become a necessity for businesses.
According to BARC, enterprises are reaping significant benefits from big data, with a 69% likelihood of making better strategic decisions, a 54% chance of improved operational process management, a 52% chance of better customer understanding, and a 47% possibility of effective cost reduction. Organizations benefiting from big data reported an average 8% rise in revenues and a 10% decrease in expenditures.
The growing demand for data makes it crucial for companies to choose the right data extraction software. Web scraping (or data extraction) software is used to collect unstructured data from the web and convert it into a standardized format for database use. Unstructured data includes emails, reports, URLs, and more. The data conversion technique employs various structural assessment approaches, such as text pattern matching, tabulation, or text analytics. To collect high-quality data in a structured format, it's essential to evaluate data extraction software against certain factors that influence data quality. Here is a comprehensive checklist encompassing all the features, capabilities, and other aspects a reliable data extraction software should have.
Consider These Points While Choosing Data Extraction Software
The global data extraction software market is projected to exceed USD 196.88 million by 2030, up from USD 149.09 million in 2018, growing at a 3.75% CAGR from 2019 to 2030.
Key drivers of growth in the data extraction software market include the need to capture current market conditions and demand, market risks, competitor analysis, technology evaluations, acquisitions, and the implementation of new trends. With the increasing demand for automated digital data extraction, numerous types of data extraction software have emerged to simplify and manage the process for businesses, analysts, researchers, and organizations. The best automated data extraction solution for your business depends on your specific data extraction needs. The ideal tool performs well with minimal time and effort. Here is a list of important elements to consider when selecting the best automated data extraction software:
Points to Consider While Choosing Data Extraction Software
User Experience: Statistics show that 25% of apps are used only once, often due to poor user experience. An intuitive and user-friendly interface in data extraction software ensures that you can collect a large amount of data quickly and conveniently. Pre-built tools that are easy to set up and use without coding knowledge are ideal, especially for beginners. Opt for a software trial to assess the user experience.
Scalability & Flexibility: The software should be customizable to meet your changing requirements, such as scheduling data scraping and choosing data formats. It should integrate easily with external sources like databases, cloud storage, and other applications. Cloud-based extractors that scale with your business needs and handle large data volumes are preferable. Reliable options include Outsource Bigdata, Apiscrapy, and open-source software for flexibility and cost-effectiveness.
Overall Cost: Pre-built data extraction software saves time and infrastructure costs. Evaluate multiple software options to find one that fits your budget while offering necessary features. Look for software with various pricing plans and potential discounts for long-term use. Free tools or those with an output-based pricing model can save money, as you pay only for what you use.
Reliability: Choose software from a reputable provider with a proven track record of stability and quality. Reliable software should handle diverse document layouts and meet long-term data needs. AI-integrated, automated tools can enhance internal data extraction processes, ensuring consistency and accuracy.
AI Augmentation: AI integration can significantly boost productivity and efficiency. AI-powered data extraction software can mimic human behavior, adapt to different languages, and bypass scraper blocking bots, making data collection easier. AI tools help users with minimal tech knowledge to collect high-quality data for research and analysis, leading to better business decisions.
Conclusion
When your company needs data extraction software, ensure it meets the five key points outlined above. These factors will help you choose the right software based on your specific requirements and usage duration. Regardless of your data needs, the software should provide effective solutions. AI-powered data extraction software can enhance efficiency and accuracy. One recommended provider is Outsource BigData, which offers pre-built, AI-powered data extraction software with rich features, reliability, and scalability. They also offer free trials and custom solutions to meet diverse business needs.
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