Why Is SAS Predictive Modeler Certification Important for You?
The software company SAS provides certification through a performance-based examination
Today’s oil field equipment is embedded in sensors that monitor flow rate, pressure, temperature, and other performance measures. Analysis of that data enables an oil production company to indicate when a piece of gear is ready for repair. By scheduling repairs across an oil field as characterized by data patterns instead of reacting as they happen, a production company can deploy personnel and supplies more efficiently, saving time and money.
Companies in different industries and the oil industry have embraced predictive modeling and analytics
The people harnessing the floods of data are predictive modelers. They own the knowledge and skills in mathematics, statistics, and analytics to assemble, transform and process data into appropriate models. Aspirant predictive modelers can create a strong career foundation with an advanced degree in business analytics
A predictive modeler draws order and circumstances from the chaos of large datasets. Data can gather intelligence on products, customers, and competitors in a business setting. The modeler’s work marks objective information in which patterns have been identified. Part of the job is to trade data as you find it, clean it up, and organize it to meet the task.
The data comes from the past, things that have occurred. By combing through the data, the predictive modeler can remember repeating patterns that indicate that the same patterns will continue in the future. The modeler may notice a slight rise in sales of a specific product at the same time each year, and the company can parlay this information into specials or coupons to drive those sales even higher.
First, the predictive modeler gathers data, using what’s appropriate and casting off what’s not. Some tasks may be as simple as exporting data to a spreadsheet so that other employees can access the information.
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For more complicated tasks, the predictive modeler writes computer code to process what can seem like overpowering amounts of data into understandable presentations. The modeler often creates data visualizations
Why Is Predictive Modeling Important?
Businesses have used predictive analytics for decades. With some sales data and a spreadsheet, executives have recognized patterns that have enabled them to predict when and where sales will rise and fall.
Over the years, the amount of data available to predictive modelers has increased dramatically. Consumer companies have more customer information from reward programs and social media mentions. Computer chips and sensors have been embedded in industrial machinery, so manufacturers can draw on extensive data to track long-term product performance. In health care, anonymized patient data enables healthcare providers, pharmaceutical companies, and insurers to focus on effective treatments and therapies.
Should You Study Predictive Modeling?
Learning predictive analysis can be a boon to you and your career if you like to predict business trends and gather data from various companies and individuals.
Although data science includes many subfields and subsets, predictive analytics is arguably one of the most significant for success. Financial services, corporations, and even individuals all advantage from learning the basics of data and predictive analytics. Understanding what a good business decision, who is a credit risk is, and what past data can tell you about the future is invaluable knowledge that is always in high demand.
Finally, SAS is a perfect option to launch your career in analytics, which is in demand in today’s business world. The SAS language is comparatively easy to any such programming language and does not require prior programming knowledge; you must sharpen your logical thinking ability to learn SAS. And once you have obtained the basic knowledge and certifications, go for the advanced methods to excel in your career. So, go for it to do a remarkable job.