|Data Scientists Spend 80 Percent of Their Time Cleaning Data
I heard this stat referenced over and over at the recent DataBeat conference, which is not surprising. It was also a prominent pain point discussed at the Big Data Innovation Summit in Las Vegas last week. Clean data is crucial to building a good predictive model and cleaning massive amounts of data is a challenge. The task is equally dreadful as it is time consuming. I have yet to see a data scientist who prefers cleaning data to building a better model or creating a more insightful visualization.
Microtasking – The Data Scientist’s Best Friend
With data cleaning being discussed as one of the primary pain points of data science, it surprises me that there is not more discussion of ways to address it. Microtasking is a form of crowdsourcing and it is an extremely powerful way to clean up your data, create a labeled dataset or mark up data to drive your business decisions.
Our platform is designed to help data scientists sort, classify and organize large datasets using our on-demand workforce. You simply upload your data, design a job that tells our on-demand workers how to label your data, and let our platform do the rest. You get results.
How Are Data Scientists Using CrowdFlower’s Platform?
Our customers use the datasets produced by our platform to evaluate and train their algorithms at a scale that they could never achieve before. CrowdFlower can help you produce fast, accurate results at a fraction of the cost of other methods so you can spend more time utilizing your data instead of cleaning it. We give you tools that help you get back up to 80 percent of your time!
If you still think that you cleaning your data is hard, check out our platform or request a demo. Our team of microtasking experts would be happy to discuss your data needs and see how we can help you save time and money.
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