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Highlights

  • While processing IoT/IIoT data, a challenge is having to work with small data sets, lack of labels and training samples, unbalanced data sets, missing or irregular data.

  • TCS Connected Universe Platform Analytics can help with its out-of-the-box algorithms for data preparation.

  • From quick AI model development to flexible deployment on any cloud or edge environment, the benefits are many and can help you get to IoT-based digital transformation faster.

CHALLENGE

In the IoT/IIoT world, while dealing with large volumes of data from various kinds of devices, we often face some hard technical problems such as working with small data sets, lack of labels and training samples, unbalanced data sets, missing or irregular data, noisy data and so on. To deal with the challenges faced in processing IoT data, a smart and efficient analytics tool is required that can enable faster data insights without having to worry about these complexities.

SOLUTION

TCS Connected Universe Platform Analytics is an advanced analytics component of TCS Connected Universe Platform, our IOT platform. Generating insights, predictions, and prognosis on IoT data are the critical success factors for IoT-based digital transformation projects and TCS Connected Universe Platform Analytics is particularly suited for these objectives. Its key features are:

  • Out-of-the-box algorithms for data preparation—transformations, data filtering, noise cleaning, missing data imputation, feature extraction, etc.  

  • Advanced analytics on sensor-generated time series data and other rich data such as videos and images  

  • Focus on unsupervised machine learning techniques  

  • Out-of-the-box library of algorithms for diagnostic, predictive and prognostic analytics 

  • Seamless testing, training and deployment of models to production

 

BENEFITS

Here’s what you stand to gain when you leverage TCS Connected Universe Platform Analytics:

  • Sophisticated data preparation: Accurate handing of unbalanced, unlabeled and noisy data 
  • Ready-to-use algorithms: Out-of-the-box capability to enable the entire analytics pipeline 
  • Quick AI model development: Automated feature engineering and hyperparameter tuning  
  • Flexible deployment: Deployed on any cloud or edge environment  

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