Pecan AI Opens Platform and Fast Predictive Modeling for All Data Professionals

Platform now open to all users for free trials of fast, easy-to-use predictive modeling, accessible to all business teams

Pecan AI, the leader in AI-based predictive analytics for BI analysts and business teams, announced that it has opened its predictive analytics platform to all users. Free trials let anyone try the platform’s intuitive SQL-based editor for building predictive models focused on real business challenges. New “fast modeling” capabilities provide rapid results and generate real predictions, all within the trial experience. Data analysts and other data professionals can dive right in and quickly build their own predictive models without the assistance of data scientists — a critical step toward making data science available for all business teams.

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“With Pecan, data analysts can not just build models, but they can also build them much faster and achieve business impact far more quickly than a data scientist who has to manually adjust models and wait for re-training to complete”

Making Predictive Modeling Accessible

While AI may be buzzy right now, the reality is that many businesses still struggle to build even basic data science capabilities, especially in today’s economic conditions.

The U.S. Bureau of Labor Statistics says 13,500 additional data scientists are needed yearly, but there’s an ongoing shortage of qualified people. Moreover, experienced data scientists may demand $200K or more in total compensation, says Salary.com.

Pecan’s low-code predictive analytics platform lets businesses quickly and efficiently gain the competitive edge of AI and data science. The free trial reveals how easily analysts can rapidly use Pecan to create accurate, action-oriented predictive models — without help from data scientists — and integrate predictions directly into their existing business systems for immediate impact.

“Predictive modeling has a reputation as being extremely complex, requiring a lot of tricky, hand-crafted, time-consuming coding and statistical analysis,” says Noam Brezis, Pecan’s CTO and co-founder. “But with today’s powerful machine learning and automation capabilities, it doesn’t have to be that way. We’ve designed Pecan to be accessible, intuitive, and fast. We’re thrilled that more businesses can now open up new growth opportunities and see real value from data science with Pecan.”

Pecan’s prebuilt predictive modeling templates offer a shorter path to a finished, actionable predictive model than any other AutoML tool. Templates address common business challenges, such as customer churn and upsell prediction, or users can design their own modeling approach. Pecan’s battle-tested templates are continuously improved based on customer feedback and model performance.

The platform’s SQL-based interface allows users to identify relevant data and customize aspects of the predictive model. Then, Pecan’s state-of-the-art machine learning methods automate tedious, time-consuming parts of predictive modeling, including data cleansing, feature engineering, and model selection.

Finally, even within the free trial, users can view Pecan’s predictions. Easy-to-interpret interactive dashboards allow users to explore model performance metrics and feature importance, adjust parameters, and examine results.

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Experiment and Learn Rapidly with Pecan’s Fast Modeling

Pecan is also making predictive analytics easier and faster by releasing new fast modeling capabilities. Generating a predictive model can take hours using traditional data science methods. But Pecan enables analysts to quickly iterate and experiment by shortening that time to 15 minutes or less.

Pecan’s fast modeling uses a lean pipeline that completes the entire process of data cleansing, flattening, feature engineering, and model selection in just a few minutes. This capability speeds up experimentation for analysts, allowing them to refine their efforts without waiting hours for results. The ultimate goal is to create a model that not only performs well on typical metrics but also meets business needs.

“With Pecan, data analysts can not just build models, but they can also build them much faster and achieve business impact far more quickly than a data scientist who has to manually adjust models and wait for re-training to complete,” Brezis says.

Pecan’s newly opened platform experience and fast modeling capabilities are just two more steps toward achieving the company’s mission of making the power of data science available to all business teams.

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