17969827. MULTI-LAYER MICRO MODEL ANALYTICS FRAMEWORK IN INFORMATION PROCESSING SYSTEM simplified abstract (Dell Products L.P.)

MULTI-LAYER MICRO MODEL ANALYTICS FRAMEWORK IN INFORMATION PROCESSING SYSTEM

Organization Name

Dell Products L.P.

Inventor(s)

Sujit Kumar Sahoo of Bangalore (IN)

Dhilip S. Kumar of Bangalore (IN)

Ajay Maikhuri of Bangalore (IN)

Devaraj Marappa of Krishnagiri District (IN)

MULTI-LAYER MICRO MODEL ANALYTICS FRAMEWORK IN INFORMATION PROCESSING SYSTEM - A simplified explanation of the abstract

This abstract first appeared for US patent application 17969827 titled 'MULTI-LAYER MICRO MODEL ANALYTICS FRAMEWORK IN INFORMATION PROCESSING SYSTEM

Simplified Explanation

The abstract describes a multi-layer micro model analytics framework for analyzing data, where micro models are built for different stages of a process and then assembled to perform analysis. In a specific example, the process is a new product introduction process, and each micro model is built for a specific lifecycle stage.

• The framework involves building two or more micro models for different stages of a process.
• Each micro model consists of a user interaction layer and a predictive learning layer.
• The user interaction layer takes input, while the predictive learning layer uses data to train the model.
• The micro models are then assembled to analyze the entire process, such as a new product introduction process.

Potential Applications

The technology can be applied in various industries for analyzing different processes, such as supply chain management, customer relationship management, and project management.

Problems Solved

This technology helps in improving decision-making processes by providing insights and predictions at different stages of a process, leading to more efficient and effective outcomes.

Benefits

The benefits of this technology include enhanced data analysis, improved process optimization, better resource allocation, and overall increased productivity.

Potential Commercial Applications

One potential commercial application of this technology is in the field of business intelligence and analytics software, where companies can utilize the framework to gain valuable insights and make informed decisions.

Possible Prior Art

One possible prior art for this technology could be traditional data analytics methods that do not involve the use of multi-layer micro models for analyzing processes.

What are the specific industries that can benefit from this technology?

Various industries such as manufacturing, healthcare, finance, and retail can benefit from this technology by improving their decision-making processes and optimizing their operations.

How does this technology compare to existing data analytics frameworks?

This technology stands out by utilizing multi-layer micro models for analyzing processes, which allows for more detailed and accurate insights compared to traditional data analytics methods.

Original Abstract Submitted

Techniques are disclosed for a multi-layer micro model analytics framework for analyzing or otherwise processing data. For example, a method comprises building two or more micro models respectively for two or more stages of a given process, wherein each micro model of the two or more micro models comprises a user interaction layer and a predictive learning layer that coordinate to train the micro model based on input to the user interaction layer and data accessible by the predictive learning layer for the corresponding stage of the two or more stages of the given process. The method then assembles the two or more micro models to perform analysis for the given process. In one non-limiting example, the given process is a new product introduction process and each micro model is built and trained to perform analytics for a specific lifecycle stage of the process.