Fake It, So You Can Make It: Using Synthetic Data To Fill In The Gaps
Synthetic data is, in theory, a useful way to fill in the gaps and get an understanding of trends and patterns when the picture is incomplete.
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Synthetic data is, in theory, a useful way to fill in the gaps and get an understanding of trends and patterns when the picture is incomplete.
To stay functional, a stack needs to be maintained, supported, and grown in a way that serves the people using it.
You need to create experiences that feel genuine and encourage excitement around fans’ favorite teams and players.
When the Yankees Entertainment Network wanted to launch a new DTC offer, they turned to Pickaxe to help.
Long before BritBox was streaming much loved shows to audiences around the world, they were looking for an experienced team to help them take the idea from concept to launch.
Nexstar needed a better way to understand user behavior, ad anomalies, and advertising performance across the hundreds of federated stations and websites that they operate from a mix of technology platforms built by them, or that they had acquired from multiple legacy parent companies over the years. The result was inconsistent and disparate reporting.
Synthetic data is, in theory, a useful way to fill in the gaps and get an understanding of trends and patterns when the picture is incomplete.
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