Abstract: System and method for predicting and scoring a data model are provided. The system includes a memory configured to receive a plurality of data sets. The system also includes a processing subsystem operatively coupled to the memory and configured to select one or more variables based on a plurality of parameters, to apply feature engineering and transformation on one or more variables to extract a plurality of features from the plurality of data sets, to build new data model based on the plurality of features, to evaluate a classification technique to select a right machine learning model based on a plurality of elements, to predict a newly built data model based on an evaluated classification technique and score the predicted data model. The system further includes a display model operatively coupled to the processing subsystem and configured to present the predicted and scored data model in one or more forms.

Abstract: A system and method for data analysis and presentation of data are provided. The system for data analysis and presentation of data includes a memory configured to receive a plurality of data sets. The system also includes a processing subsystem operatively coupled to the memory and configured to determine a plurality of properties of the plurality of data sets, to analyse a categorical variable of the plurality of data sets based on the plurality of properties of the plurality of the plurality of data sets, to identify one or more custom rules based on an analysed categorical variable, to interpret the identified one or more custom rules, to identify a graph based on one or more custom rules, to identify one or more textual insights based on one or more custom rules and the identified graph, to present the identified graph and one or more textual insights.

Abstract: System and method to build and score predictive model for numerical attributes are provided. The system includes a memory and a processing subsystem. The processing subsystem is configured to select one or more numerical variables from the plurality of data sets based on a plurality of parameters, to apply feature engineering and transformation on the one or more numerical variables, to perform time series forecasting on the one or more numerical variables based on the plurality of features extracted, to evaluate and select appropriate prediction technique based a regression technique based on a plurality of elements, to build a prediction model, to score the built prediction model based on the performed time series forecasting and an evaluated regression technique and to predict the built prediction model based on an obtained score. Further, the system uses the plurality of parameters and the prediction method to score and predict the prediction model.

Abstract: System and method to analyze and predict impact of textual data are provided. The system also includes a processing subsystem configured to select textual data from a plurality of data sets stored in a memory, to extract data from external sources using crawling, to identify at least one context of the textual data using one or more identification methods. The processing subsystem includes an NLP module configured to match the textual data with NLP frameworks using a mapping method based on a plurality of parameters, to apply feature engineering and transformation on the textual data to extract a plurality of features from the plurality of data sets and to analyze matched textual data of the textual using at least one analysis method. The processing subsystem also includes a predictive module configured to predict one or more future values of the analyzed textual data using the one or more predictive methods.

Abstract: System and method to build and score predictive model for numerical attributes are provided. The system includes a memory and a processing subsystem. The processing subsystem is configured to select one or more numerical variables from the plurality of data sets based on a plurality of parameters, to apply feature engineering and transformation on the one or more numerical variables, to perform time series forecasting on the one or more numerical variables based on the plurality of features extracted, to evaluate and select appropriate prediction technique based a regression technique based on a plurality of elements, to build a prediction model, to score the built prediction model based on the performed time series forecasting and an evaluated regression technique and to predict the built prediction model based on an obtained score. Further, the system uses the plurality of parameters and the prediction method to score and predict the prediction model.

Abstract: System and method to analyze and predict impact of textual data are provided. The system also includes a processing subsystem configured to select textual data from a plurality of data sets stored in a memory, to extract data from external sources using crawling, to identify at least one context of the textual data using one or more identification methods. The processing subsystem includes an NLP module configured to match the textual data with NLP frameworks using a mapping method based on a plurality of parameters, to apply feature engineering and transformation on the textual data to extract a plurality of features from the plurality of data sets and to analyze matched textual data of the textual using at least one analysis method. The processing subsystem also includes a predictive module configured to predict one or more future values of the analyzed textual data using the one or more predictive methods.

Abstract: Disclosed subject matter relates to data analytics including a method and system for generating a contextual summary of one or more charts. A summary generating system extracts chart data associated with each chart received from one or more sources and determines context of the chart data. The summary generating system computes statistical data of each chart by analyzing chart data based on predefined rules corresponding to the context. The form of analysis to be performed depends on the context of the chart data. Furthermore, insights of each chart are generated by mapping the statistical data with predefined narratives corresponding to the context. Finally, the summary generating system, automatically generates the contextual summary of the charts corresponding to the context of the chart data in a predefined template format using the generated insights of each of the one or more charts. The contextual summary provides holistic information of the interpreted charts.

Abstract: A system and method for data analysis and presentation of data are provided. The system for data analysis and presentation of data includes a memory configured to receive a plurality of data sets. The system also includes a processing subsystem operatively coupled to the memory and configured to determine a plurality of properties of the plurality of data sets, to analyse a categorical variable of the plurality of data sets based on the plurality of properties of the plurality of the plurality of data sets, to identify one or more custom rules based on an analysed categorical variable, to interpret the identified one or more custom rules, to identify a graph based on one or more custom rules, to identify one or more textual insights based on one or more custom rules and the identified graph, to present the identified graph and one or more textual insights.

Abstract: A system and method for analysis and representation of data are provided. The system includes a memory configured to receive a plurality of data sets. The system also includes a processing subsystem operatively coupled to the memory and configured to select one or more numeric variables of the plurality of data sets. The processing subsystem is further configured to analyse the one or more numeric variables of the plurality of data sets based on the plurality of properties of the plurality of data sets, identify one or more custom rules based on the plurality of data sets, identify graphical representation based on outcome of the one or more identified custom rules, identify one or more textual insights based on outcome of the one or more custom rules and represent identified graphical representation and one or more textual insights on a display device.

Abstract: System and method for predicting and scoring a data model are provided. The system includes a memory configured to receive a plurality of data sets. The system also includes a processing subsystem operatively coupled to the memory and configured to select one or more variables based on a plurality of parameters, to apply feature engineering and transformation on one or more variables to extract a plurality of features from the plurality of data sets, to build new data model based on the plurality of features, to evaluate a classification technique to select a right machine learning model based on a plurality of elements, to predict a newly built data model based on an evaluated classification technique and score the predicted data model. The system further includes a display model operatively coupled to the processing subsystem and configured to present the predicted and scored data model in one or more forms.

Abstract: Disclosed subject matter relates to data analytics including a method and system for generating a contextual summary of one or more charts. A summary generating system extracts chart data associated with each chart received from one or more sources and determines context of the chart data. The summary generating system computes statistical data of each chart by analysing chart data based on predefined rules corresponding to the context. The form of analysis to be performed depends on the context of the chart data. Furthermore, insights of each chart are generated by mapping the statistical data with predefined narratives corresponding to the context. Finally, the summary generating system, automatically generates the contextual summary of the charts corresponding to the context of the chart data in a predefined template format using the generated insights of each of the one or more charts. The contextual summary provides holistic information of the interpreted charts.