Evomi Proxy Blog

When internal scrapers serve external consumers, reliability expectations change fundamentally. SLAs, schema versioning, and data contracts become necessary infrastructure. This post covers what it takes to treat a scraper as a product rather than a script.

Just scraped valuable data? Don't stumble on storage! JSON and CSV are the go-to formats, but picking the wrong one can create major headaches for analysis and use. Understand the key differences in the JSON vs CSV battle to choose the optimal format for your web scraping results.

Data generation is soaring, but so are the costs to collect it via APIs, web scraping, and complex infrastructure. Learn actionable strategies to slash these expenses, optimize your methods (including proxy usage!), and make your data acquisition truly cost-effective.

Every byte of data you collect holds value and risk. Don't let a backup failure expose sensitive information or halt operations. Master these 6 key tactics for truly secure data backups and protect your digital assets.

Janitor AI isn't just for chats! Harness its free NLP and data formatting for web scraping, and easily integrate reverse proxies for enhanced security and efficient data handling. Your comprehensive guide awaits.

Relying on proxies for data collection? Be warned: poor data quality costs businesses an average of $12.9 million annually. Understand the hidden ways bad data sabotages decisions and discover how to protect your insights.

A practical, no-fluff framework for building data quality assurance: metrics, profiling, cleansing, validation, integration, and monitoring—plus where reliable data collection fits in.

A practical guide to the data quality dimensions that matter for web scraping and analytics teams, plus how to prioritize fixes when you can't audit everything at once.

Proxy users know accessing web data isn't always simple. Should you rely on structured APIs or flexible web scraping? Discover the key differences to optimize your data strategy and navigate access restrictions effectively.

How managing data from collection to deletion keeps it accurate, secure, and useful. A practical DLM walkthrough for teams that collect public web data at scale.

Raw data is rarely analysis-ready. Here are five practical preprocessing techniques—assessment, cleaning, reduction, integration, and transformation—with concrete Python examples you can apply today.

A practical guide to datasets for scraping teams: how they're structured, the main types, how they differ from databases, and how to build clean, reliable ones from public web data.