Download our free eBook to learn about critical steps in the process and the following 3 key features to accelerate the predictive analytics journey:

  • Automated data collection with drag and drop data import and flexible database connectivity
  • AI-Focused data preparation that includes data value cleansing, statistical data profiling, and data re-architecting
  • AI-Powered Feature Engineering with feature hypothesis, query generation, and feature relevance validation

Insight: Organizations around the world are leveraging predictive analytics, an advanced form of analytics, and data science automation to gain greater agility and faster, more accurate decision-making.  If your team is new to ML-driven analytics, performing mostly BI reporting and visualization, and your business has been doing traditional analytics, you need to follow a process to ensure success and get a head start with predictive analytics.

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