System and method for data analysis and presentation of data

1. A system for data analysis and presentation of data comprising:

a memory configured to receive a plurality of data sets from a plurality of means;

a processing subsystem operatively coupled to the memory wherein the processing subsystem comprises:

a data accumulator configured to combine the plurality of data sets received from the plurality of means using a mashup component to generate a plurality of combined data sets;

an expert rule system configured to:

determine a plurality of properties of the plurality of combined data sets;

identify one or more categorical variables based on the plurality of properties of the plurality of combined data sets;

select a categorical variable from one or more of identified categorical variables;

identify one or more custom rules based on a selected categorical variable obtained from the plurality of combined data sets;

an algorithm selector configured to select one or more statistical tests or one or more machine learning models based on the one or more custom rules;

a job sequencer configured to decide a sequence and manage the execution of the one or more statistical tests or one or more machine learning models;

a data processing engine configured to:

analyse a performance of a scenario based on the sequence of execution of the one or more statistical tests or one or more machine learning models;

analyse a plurality of factors influencing the identified categorical variable comprising:

determine an impact of selected dimension parameters on the chosen categorical variable, wherein the dimension parameters are entities and comprise at least one of an organisation, an agent name, a state, education and a call type;

determine an impact of measures over the selected categorical variable, wherein measures are measurable quantities and comprise at least one of count, volume, and time duration;

generate recommendation results to increase or optimize the categorical variable based on the impact of the selected dimension parameters and the impact of the measures using prescriptive analytics;

a visualization builder configured to identify a graph based on the performance of the scenario;

display count of selected dimension parameters, selected measures and a selectable user interface element for viewing presentation of the analysed data and textual insights to be created based on the identified graph;

an insights generator configured to:

identify one or more textual insights based on an identified graph;

generate the one or more textual insights in a natural language; and

a display device configured to present the identified graph and the one or more textual insights.

2. The system as claimed in claim 1 , wherein the plurality of data sets comprises a plurality of structured data, a plurality of unstructured data or a plurality of semi-structured data.

3. The system as claimed in claim 1 , wherein the plurality of properties of the plurality of data sets comprises an instruction set, a data type, a hierarchy of data and a category of data.

4. A method for data analysis and presentation of data comprising:

receiving, by a memory, a plurality of data sets from a plurality of means;

combining, by a data accumulator, the plurality of data sets received from the plurality of means using a mashup component to generate a plurality of combined data sets

determining, by an expert rule system, a plurality of properties of the plurality of combined data sets;

identifying, by the expert rule system, one or more categorical variables based on the plurality of properties of the plurality of combined data sets;

selecting, by the expert rule system, a categorical variable from one or more identified categorical variables;

identifying, by the expert rule system, one or more custom rules based on a selected categorical variable obtained from the plurality of data combined sets;

selecting, by an algorithm selector, one or more statistical tests or one or more machine learning models based on the one or more custom rules;

deciding, by a job sequencer, a sequence and manage the execution of the one or more statistical tests or one or more machine learning models;

analysing, by a data processing engine, a performance of a scenario based on the sequence of execution of the one or more statistical tests or one or more machine learning models, wherein the data processing engine is configured to analyse a plurality of factors influencing the identified categorical variable, wherein analysing the plurality of factors comprises:

determining an impact of selected dimension parameters on the chosen categorical variable, wherein the dimension parameters are entities and comprise at least one of an organisation, an agent name, a state, education and a call type;

determining an impact of measures over the selected categorical variable, wherein measures are measurable quantities and comprise at least one of count, volume, and time duration;

generating recommendation results to increase or optimize the categorical variable based on the impact of the selected dimension parameters and the impact of the measures using prescriptive analytics;

identifying, by a visualization builder, a graph based on the performance of the scenario;

displaying count of selected dimension parameters, selected measures and a selectable user interface element for viewing presentation of the analysed data and textual insights to be created based on the identified graph;

identifying, by an insights generator, one or more textual insights based on an identified graph;

generating, by the insights generator, the one or more textual insights in a natural language; and

presenting, by a display device, the identified graph and the one or more textual insights.

5. The method as claimed in claim 4 , wherein receiving the plurality of data set comprises receiving the plurality of data from a plurality of means such as a web, a manual entry of data, a local data and an experimental data.

6. The method as claimed in claim 4 , wherein identifying one or more textual insights comprises:

interpreting one or more selected statistical tests;

prioritising the one or more interpreted statistical tests;

presenting the one or more prioritised statistical tests graphically; and

generating the one or more textual insights from a represented graph of the one or more interpreted statistical tests.