Big Data Scientists

Reduce Big Data Wrangling While Saving Time and Money

Having organized data warehouses full of millions of variables may seem like a great idea. On the surface. But in its raw sate, that much data will require time-consuming joining, cleaning, and processing before it is useful. Many big data scientists say they spend too much of their time, up to 80% of it, cleaning data before they can do any meaningful analysis with it. This is a poor allocation of resources a company could be utilizing elsewhere.

CrowdFlower can assist you with the time-consuming joining, cleaning and processing of your big data. Using advanced quality control mechanisms, worker targeting, and sophisticated job design tools, CrowdFlower contributors will collect, clean, and label high-quality large-scale data sets, saving you both time and money over alternative methods like outsourcing or managing interns.

With CrowdFlower, you can

  • Organize anything: There’s no limit to what our human-in-the-loop platform can do it. You provide the categories and we’ll take care of the rest.
  • Train your algorithms: Use the rich, human-curated data sets to train your machine learning models.
  • Save valuable time: Data categorization is time consuming. Our massive contributor base works 24/7 and lets you cut data cleaning time to a fraction.

Whether you need to categorize sentiment, business information, product pages, or any other kind of big data, CrowdFlower can help you. Save time and money and use your big data as a competitive asset. Get started with CrowdFlower today!