Buying vs. Scraping Data
How to get the most of your data acquisition strategy in 2023
You may have heard the quote ‘data is the new oil’, and with the continuing evolution of data-driven business environments, data truly is the oil that is keeping businesses moving forward in 2023. But unlike oil, data is an infinite resource, with the collection and distribution of data costing businesses more and more every year.
With an ever growing need to provide refreshed and expanded data to your teams, technical experts are grappling with the need to gather data using every means possible. So the question is… to buy your data from a vendor who has done the work for you, or to scrape and gather the data yourself?
Buying data vs. scraping data
Data Quality
Buying Data: Purchasing data from reputable providers ensures high-quality and pre-validated information. Data vendors invest significant resources in verifying, cleaning, and maintaining their datasets. As a result, businesses can rely on accurate and up-to-date information without the need for extensive cleaning or processing.
Scraping Data: Scraping data involves extracting information from websites and online sources. While it provides access to a vast pool of data, the quality can vary significantly. Websites often undergo updates, making scraping efforts prone to errors and inconsistencies. Scrapped data may require substantial cleaning and normalisation to be useful, potentially increasing the time and effort required for data enrichment.
Data Privacy and Compliance
Buying Data: Third-party data providers must adhere to privacy regulations and ensure data compliance. Reputable providers have stringent data protection measures in place, safeguarding sensitive information and ensuring compliance with laws such as the General Data Protection Regulation (GDPR). By purchasing data, businesses can avoid potential legal and ethical issues associated with data scraping.
Scraping Data: Data scraping, especially when performed on publicly accessible websites, raises concerns regarding data privacy and legal implications. Websites may have terms of service or usage agreements that prohibit scraping activities. Violating these terms can lead to legal consequences and damage to a company’s reputation. Moreover, scraping personal or sensitive data without proper consent may result in severe legal repercussions.
Data Customization and Relevance
Buying Data: Third-party data providers offer customised datasets tailored to specific business needs. Businesses can specify their desired criteria, such as demographics, geographies, or industry segments, and obtain relevant data that aligns with their objectives. This targeted approach saves time and effort in filtering and organising vast amounts of data.
Scraping Data: Scraping data allows for greater flexibility and control over the specific data sources to be collected. Businesses can curate their own datasets by scraping from websites that are most relevant to their industry or target audience. However, this process requires technical expertise, ongoing monitoring of data sources, and potential adjustments to scraping algorithms as websites change their structure.
Cost Considerations
Buying Data: Acquiring data from third-party providers typically involves a financial investment. The cost varies depending on factors such as data volume, customization, and data provider reputation. While buying data can be more expensive upfront, it may save businesses time and resources by providing readily available, clean datasets.
Scraping Data: Scraping data can be a cost-effective option, especially for businesses with limited budgets. However, it is crucial to consider the hidden costs associated with data scraping. These may include infrastructure for hosting scraped data, maintenance costs, anti-scraping measures, and ongoing efforts to adapt scraping processes to changes in target websites. Additionally, the time and expertise required for scraping and data cleaning should be factored into the overall cost analysis.
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Which option to choose?
Before deciding between buying data and scraping data, businesses should thoroughly assess their project specifics, technical capabilities, time constraints, and budget limitations. If your project demands unique, complex, and ultra-current data, buying from reputable providers may be the ideal choice. However, if you have the technical expertise, time, and flexibility, scraping data can be a viable option, particularly when dealing with publicly available and less specialised information. Ultimately, the decision should align with your organisation’s goals, resources, and constraints.
Project Specifics
Consider whether your project requires unique, complex, and up-to-the-minute data or if pre-packaged, structured data would suffice. If your project demands highly specialised or real-time information, buying data from reputable providers might be the best option. However, if your needs are more generic or can be fulfilled with publicly available data, scraping may be a viable and cost-effective choice.
Technical Capability
Evaluate your organisation’s technical expertise, tools, and resources. Scraping data effectively requires proficiency in web scraping techniques, data extraction, cleaning, and structuring. If your team possesses the necessary skills and resources, scraping can be a viable option. Otherwise, purchasing data provides a more straightforward and reliable solution, as data providers invest significant efforts in data validation and maintenance.
Time Constraints
Consider the urgency of accessing the data. If time is of the essence and you require immediate access to quality data, buying data can save valuable time. Data providers have already invested resources in gathering, validating, and structuring the information, allowing you to focus on utilising the data rather than collecting and processing it. In contrast, scraping data can be time-consuming, especially when dealing with large volumes or complex data sources.
Budget
Evaluate your budgetary constraints and trade-offs. Buying data typically incurs upfront costs, as data providers charge for their curated datasets. However, this approach can save time and resources in the long run, as the data is ready to use and often of high quality. On the other hand, scraping data can offer potential cost savings, as publicly available data can be acquired at a lower or even no cost. However, it is essential to consider the hidden costs associated with scraping, such as infrastructure, maintenance, and data cleaning efforts.
Conclusion
The decision between buying data and scraping data depends on various factors, including data quality requirements, privacy concerns, customization needs, and cost considerations. Buying data provides businesses with validated and readily usable datasets, ensuring data compliance and saving time. On the other hand, scraping data offers flexibility, customization, and cost advantages, but requires technical expertise and entails legal and privacy risks. Ultimately, businesses must assess their unique requirements and consider the benefits and challenges associated with each approach to make an informed decision on enriching their databases.
