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Predictive Analytics For Retail: What Lies Ahead?

Nastel Technologies®
March 4, 2019
Comments: 1

Predictive Analytics For Retail: What Lies Ahead?I am personally fascinated by predictive analytics and the ability to combine data elements to create an approximate idea of what the future may hold. Although data modeling has been used quite extensively in certain industries (e.g., weather predictions based on specific historic models and key indicators, insurance estimates and actuarial tables, etc.), the concept of applying similar science to retail holds unrealized potential. Given technology advancements and data-mining tools, potential future predictions — in other words, answering the question “What lies ahead?” — seems far more attainable than ever before. Considering big data already captured within the retail sector, it becomes mind-boggling.

Virtually all industries have pools of information that could be used for predictive purposes. This reminds me of a presentation I sat through nearly three decades ago by a then-IBM executive who suggested that the future will be owned by those who have the keys to data and the intelligence that it generates. And, as recently as this month’s National Retail Federation event, the power of data was repeatedly emphasized.






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Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously.  To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:

  • Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
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  • End-to-end business transaction tracking that spans technologies, tiers, and organizations
  • Intuitive, easy-to-use data visualizations and dashboards

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Nastel Technologies is the global leader in Integration Infrastructure Management (i2M). It helps companies achieve flawless delivery of digital services powered by integration infrastructure by delivering tools for Middleware Management, Monitoring, Tracking, and Analytics to detect anomalies, accelerate decisions, and enable customers to constantly innovate, to answer business-centric questions, and provide actionable guidance for decision-makers. It is particularly focused on IBM MQ, Apache Kafka, Solace, TIBCO EMS, ACE/IIB and also supports RabbitMQ, ActiveMQ, Blockchain, IOT, DataPower, MFT, IBM Cloud Pak for Integration and many more.


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  • Predictive retail analytics
    July 15, 2022
    Thanks for the article on Predictive Analytics For Retail: What Lies Ahead?.Looking forward for more articles like this.
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