Data Processing Machine Learning

process real-time events analytic computations of streaming data.

IBM, Data Processing, Machine Learning, Pragama Edge, PragmaEdge,

Machine learning is having a dramatic impact on the way software is designed so that it can keep pace with business change. Machine learning is so dramatic because it helps you use data to drive business rules and logic. How is this different? With traditional software development models, programmers wrote logic based on the current state of the business and then added relevant data. However, business change has become the norm. It is virtually impossible to anticipate what changes will transform a market. 

The value of machine learning is that it allows you to continually learn from data and predict the future. This powerful set of algorithms and models are being used across industries to improve processes and gain insights into patterns and anomalies within data.

But machine learning isn’t a solitary endeavor; it’s a team process that requires Data scientists, data engineers, Business analysts, and business leaders to collaborate. The power of machine learning requires a collaboration so the focus is on solving business problems.

drive business rules & logic

Machine learning is a form of AI that enables a system to learn from data rather than through explicit programming. However, machine learning is not a simple process. As the algorithms ingest training data, it is then possible to produce more precise models based on that data. A machine-learning model is the output generated when you train your machine-learning algorithm with data. After training, when you provide a model with an input, you will be given an output. For example, a predictive algorithm will create a predictive model. Then, when you provide the predictive model with data, you will receive a prediction based on the data that trained the model.

data-extraction-as-a-service

Data Extraction

SMART Client provides a easy to deploy, data extraction capabilities from different sources of data.

Data Analysis

Extracted data can be further analyzed to identify and route the data for further processing.
Data Analysis
Pragma Edge Stream Analytics Data Enrichment

Data Enrichment

Various data enrichment options are available to create golden data set that creates the required business object data.

Pattern Recognition

Different patterns in the data can be detected at real time to send alerts or action before, during or after processing the data.
Pattern Recognition
Pragma Edge Stream Analytics Data Visualization

Data Visualization

Utilize modern data visualization methods to present the data.

Data Processing Machine Learning Use cases

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On April 21 2021, 11 AM CT