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Within the financial services sector, for example, McKinsey estimates that AI has the potential to generate an additional $1 trillion in annual value while Autonomous Research predicts that by 2030 AI will allow operational costs to be cut by 22%. Snorkel AI solves this bottleneck with Snorkel Flow, the data-centric AI platform.
Within the financial services sector, for example, McKinsey estimates that AI has the potential to generate an additional $1 trillion in annual value while Autonomous Research predicts that by 2030 AI will allow operational costs to be cut by 22%. Snorkel AI solves this bottleneck with Snorkel Flow, the data-centric AI platform.
This capability is essential for businesses aiming to make informed decisions in an increasingly data-driven world. billion by 2030. This step includes: Identifying Data Sources: Determine where data will be sourced from (e.g., In 2024, the global Time Series Forecasting market was valued at approximately USD 214.6
Those pillars are 1) benchmarks—ways of measuring everything from speed to accuracy, to dataquality, to efficiency, 2) best practices—standard processes and means of inter-operating various tools, and most importantly to this discussion, 3) data. In order to do this, we need to get better at measuring dataquality.
Those pillars are 1) benchmarks—ways of measuring everything from speed to accuracy, to dataquality, to efficiency, 2) best practices—standard processes and means of inter-operating various tools, and most importantly to this discussion, 3) data. In order to do this, we need to get better at measuring dataquality.
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