Making sense of massive amounts of unstructured data from news and other sources is complicated. Our approach to aggregating, analyzing, cleansing and organizing all of that data helps our customers make better business decisions, faster.
Download this white paper and learn:
- How we leverage AI to process large datasets to perform predictive analytics.
- How municipal, economic and corporate precision news can drive predictive analytics.
- How we combined our data with outside requirements laid out by Amazon and predictive models to make intelligent predictions.
- Detailed results of our predictions.
The Bitvore platform ingests a massive amount of unstructured data and applies proprietary AI techniques to normalize and organize.
In this white paper, we go into detail about our approach to sifting through the massive amount of noise and how we identify business signals and associate them with corporate business entities.
- Sifting through all of this data is a huge challenge
- Learn our methodology to predictive analytics
- Learn how we incorporate the business signals that represent significant events into our modeling
We are often asked for examples of how our signal-driven,
precision news data can be predictive when we explain how
our customers use our data.
In this white paper, we set up a predictive experiment through backtesting around Amazons HQ2 Selection competition:
- We wanted to determine if, at each stage of the competition, we could predict which cities would advance to the next round.
- And determine if we could predict the final location(s) of
Amazon’s HQ2 before it became public information.
Download our white paper to find out how our signal driven, precision news data can help businesses make predictions.
