Explore the Benefits of Predictive Modeler and Its Certification

​What Is Predictive Modeler?

​​In short, a Predictive Modeler is a statistical technique applying machine learning and data mining to predict and forecast likely future issues with the help of historical and existing data. It operates by analyzing current and historical data and projecting what it learns on a model made to forecast likely outcomes.

Predictive Modeler can be used to predict just about anything, from TV ratings and a customer’s next purchase to credit risks and corporate earnings. A predictive model is not fixed; it is approved or revised regularly to incorporate changes in the underlying data. In other words, it is not a one-and-done prediction.
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Predictive models make opinions based on what has happened in the past and what is occurring now. If incoming, new data reveals changes in what is occurring now, the likely future outcome's impact must be recalculated, too. A software company could model historical sales data next marketing expenditures across multiple regions to create a future revenue model based on the marketing spend.

Most predictive models work fast and often perform their calculations in real-time. That’s why banks and retailers can, for example, calculate the risk of an online contract or credit card application and accept or decline the offer almost immediately based on that prediction.

Some predictive models are more complicated, such as those used in computational biology and quantum computing; the resulting outputs take longer to measure than a credit card application but are done much more quickly than was likely in the past thanks to advances in technological capabilities, including computing power.

What Are the Benefits of Predictive Modeler?

As the industry goes towards digitalization, manufacturers face more significant pressure to have an aggressive edge, and many begin asking why Predictive Modeler?

Predictive Modelers are essential for applications such as predictive quality and predictive performance that allow manufacturers to recognize problems at their very earliest stages, so they can be dealt with before issues start to unfold.

With return on investment a key driver for the industry, Predictive Modeler can deliver quick wins, with many factories seeing average cost savings and optimization opportunities after just a few months.

1. Identify Patterns to Predict Performance

Predictive Modeler sifts through vast amounts of historical data much more quickly and accurately than a human can. Machine learning technologies can identify repeated patterns and other relationship variables, such as when we turn these settings, we improve production by 10% without sacrificing the first-pass yield. AI and machine learning can search for patterns and explore different combinations that support your organization, identify potential efficiency improvements, predict issues, and decrease waste.

2. Improve Operations in Real-Time

A Predictive Modeler delivers near real-time insights by comparing data from historical production runs with live production activity. These comparisons, which convert to predictive and prescriptive analytics, drive recommendations and alerts to improve real-time operations.

3. Decrease Costs

Quality failures can translate into actual losses in the product, overhead labor, and time. Predictive Modeler can enable factories to identify quality failures and take corrective action faster to minimize impact and decrease waste costs. Prescriptive analytics can further these cost savings by allowing you to replicate your most efficient runs more consistently. Additionally, Predictive Modeler and condition-based monitoring can help factories reduce unplanned downtime and lost productivity by notifying plants of potential equipment problems.

4. Optimize to Perfection

Manufacturers have been accustomed to Lean Principles for decades. These best practices sought to help manufacturers achieve maximum production efficiency with minimum waste. Predictive Modeler ultimately provides manufacturers with real-world data to help them optimize their processes reach perfect perfection.

Earn Predictive Modeler Certification

A predictive Modeler is an attractive option because it brings a ton of value to any organization. However, it is also on the higher end of the complexity spectrum than some other business analytic options.
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A predictive Modeler is an attractive option because it brings a ton of value to any organization. However, it is also on the higher end of the complexity spectrum than some other business analytic options.

​The complexity in utilizing the Predictive Modeler predominantly manifests in the number of steps required and the expertise needed for some of the steps. This course is designed to reduce and eliminate these issues.

The SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 credential is globally recognized for validating SAS Predictive Modeler knowledge. With the Certification credential, you stand out and prove that you have the SAS Predictive Modeler knowledge to distinguish within the organization.

During this performance-based examination, the candidates will use the SAS Enterprise Miner to perform the examination tasks. The candidate must have a firm understanding and mastery of Predictive Modeler's functionalities in SAS Enterprise Miner.