Having access to the right data in a clean and accessible format is the first step (or series of steps) leading up to actually extracting business value from your data. As much as 80% of the time spent on data science projects involves data integration and preparation. Once we get there, the real fun begins. With the continued focus on big data and analytics to drive competitive advantage, data science has been spending a lot of time in the headlines. (Can we fit a few more buzzwords into one sentence?)
Let’s take a look at a few data science apps available on our platform and how they can help us into our data monetization efforts.
One of the most popular algorithms is market basket analysis. It provides the power behind things like Amazon’s product recommendation engine and identifies that if someone buys product A, they are likely to buy product B. More specifically, it’s not identifying products placed next to each other on the site that get bought together, rather products that aren’t placed next to each, This can be useful in improving in-store and on site customer experience, target marketing and even the placement of content items on media sites.
Anomaly detection refers to identifying specific events that don’t conform to the expected pattern from the data. This could take the form of fraud detection, identifying medical problems or even detecting subtle change in consumer buying behaviors. If we look at the last example, this could help us in identifying new buying trends early and taking advantage. Using the example of an eCommerce company, you could identify anomalies in carts created per minute, a high number of carts abandons, an odd shift in orders per minute or a significant variance in any other number of metrics.