SAS Asset Performance Analytics Description

Achieve production targets and financial objectives while minimizing unexpected disruptions. Utilizing status dashboards and automated alerts, operations personnel and managers are informed of potential failures, granting them the opportunity to pinpoint and resolve issues before they escalate into expensive challenges. Transition to predictive and prescriptive maintenance approaches that tackle known failure points and declines in performance without incurring additional costs. By recognizing leading indicators of potential breakdowns, you can eliminate the need for expensive preventive part replacements that may not be necessary. Employ advanced analytics, data mining, and data visualization techniques to swiftly and accurately uncover root causes, revealing hidden patterns within the data. This enables you to troubleshoot performance problems more effectively and gain insight into their origins, allowing for rapid corrective measures to be implemented. Ultimately, this proactive approach not only enhances operational efficiency but also fosters a culture of continuous improvement within the organization.

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The data generated by IoT devices is predominantly unstructured, posing challenges for analysis using conventional analytics and business intelligence tools that cater to structured data formats. This type of data is often derived from devices that capture inherently noisy processes like temperature, motion, or sound, leading to frequent occurrences of significant gaps, corrupted messages, and erroneous readings that necessitate cleansing prior to any analytical work. Moreover, the significance of IoT data frequently relies on supplementary inputs from third-party data sources. For instance, vineyard irrigation systems enhance moisture sensor readings with rainfall data, assisting farmers in making informed decisions on when to irrigate their crops, thereby optimizing water usage and boosting harvest yields. AWS IoT Analytics simplifies and automates the complex steps involved in analyzing data from IoT devices, making it easier for users to gain insights. This service is fully managed and operates on a pay-as-you-go model, ensuring automatic scaling to accommodate varying data volumes. Consequently, organizations can leverage AWS IoT Analytics to advance their operational efficiencies and make data-driven decisions with greater ease.
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Company Details

Company:
SAS
Year Founded:
1976
Headquarters:
United States
Website:
www.sas.com/en_us/software/asset-performance-analytics.html

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Product Details

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Web-Based
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Live Training (Online)
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Online Support

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