The Future of Web Scraping and Alternative Data - Predictions for 2023

As many economies are predicted to face recession, investment decisions will need to be tighter and less risky. Collecting alternative financial data will be key in getting the necessary signals to make these predictions.

Cybersecurity practices continue to be adopted by more organizations. Hence, use cases like proactive threat hunting and monitoring that require continuous large-scale web monitoring will become more common.

We can expect that during 2023 other legal grounds and arguments will be tried and become more popular in the courts against data scraping companies, such as infringement of terms of service, intellectual property protection, etc.

Finally, 2023 might be the year when the scraping and data collection industry will begin self-regulation initiatives.

Therefore, I suggest leaving web scraping in the expert’s hands. Although the cost of commercial scraping will increase, doing it yourself will be even more expensive than with professionals’ help.

Although there have been many ML failures in the past, I believe the tide is turning for ML engineering teams due to a combination of greater attention on data quality and economic pressure to make ML more useful.

Many businesses will have difficulties in the next year. As a result, IT companies must discover methods to save expenses, make the greatest use of data scientists' time and talents, and incorporate machine learning and predictive modeling capabilities into teams that directly influence revenue and profitability. As a result, I expect that businesses will maximize data science resources by augmenting skilled data scientists inside the company with data technologies that automate regular portions of data science work using reliable approaches.