SYSTEM AND METHOD FOR AUGMENTED MEDIA INTELLIGENCE
Aspects of the present disclosure involve systems, methods, devices, and the like for augmented media intelligence using data analytics, machine learning and data visualization. In one embodiment, a system is introduced that can retrieve real-time data from social media platforms to perform augmented media intelligence analytics. The augmented media system is designed to generate reports/actionable insights for user visualization on an interactive user interface, where the reports are based in part on the user social currency.
1 . A system comprising:
a non-transitory memory storing instructions; and
a processor configured to execute instructions to cause the system to:
in response to a determination that new data is available for processing, retrieve real-time digital data;
determine a combination of data analytics to be performed based in part on the digital data and user preferences;
calculate, the combination of data analytics the data analytics including diagnostic analytics, wherein the data analytics uses a machine learning algorithm to determine a reason for a first event occurrence;
generate, a performance metric and report using the diagnostic analytics performed; and
calculate, using a machine learning technique, proactive analytics to predict a second event base in part on the first event occurrence.
2 . The system of claim 1 , executing instructions further causes the system to:
calculate, using the machine learning technique, prescriptive analytics to determine historical trends in the digital data from the first event.
3 . The system of claim 1 , executing instructions further causes the system to:
generate a second report using the proactive analytics calculated.
4 . The system of claim 1 , wherein the reason for the event occurrence is determined based on a monitoring of the real-time digital data.
5 . The system of claim 1 , wherein the diagnostic analytics includes determining a correlation between media sentiments and a business key performance indicator.
6 . The system of claim 1 , wherein the performance metric and report are transmitted, via network connection, to a user device for presentation on an interactive user interface.
7 . The system of claim 6 , wherein the performance metric and the report transmitted is personalized using a social currency of the user of the user device.
8 . A method comprising:
in response to a determination that new data is available for processing, retrieving a real-time digital data;
determining a combination of data analytics to be performed based in part on the digital data and user preferences;
calculating, the combination of data analytics the data analytics including diagnostic analytics, wherein the data analytics uses a machine learning algorithm to determine a reason for a first event occurrence;
generating, a performance metric and report using the diagnostic analytics performed; and
calculating, using a machine learning technique, proactive analytics to predict a second event base in part on the first event occurrence.
9 . The method of claim 8 , further comprising:
calculating, using the machine learning technique, prescriptive analytics to determine historical trends in the digital data from the first event.
10 . The method of claim 8 , further comprising:
generating a second report using the proactive analytics calculated.
11 . The method of claim 8 , wherein the reason for the event occurrence is determined based on a monitoring of the real-time digital data.
12 . The method of claim 8 , wherein the diagnostic analytics includes determining a correlation using machine learning between media sentiments and a business key performance indicator.
13 . The method of claim 8 , wherein the performance metric and report are transmitted, via network connection, to a user device for presentation on an interactive user interface.
14 . The method of claim 13 , wherein the performance metric and the report transmitted is personalized using a social currency of the user of the user device.
15 . A non-transitory machine readable medium having stored thereon machine readable instructions executable to cause a machine to perform operations comprising:
in response to a determination that new data is available for processing, retrieving real-time digital data;
determining a combination of data analytics to be performed based in part on the digital data and user preferences;
calculating, the combination of data analytics the data analytics including diagnostic analytics, wherein the data analytics uses a machine learning algorithm to determine a reason for a first event occurrence;
generating, a performance metric and report using the diagnostic analytics performed; and
calculating, using a machine learning technique, proactive analytics to predict a second event base in part on the first event occurrence.
16 . The non-transitory medium of claim 15 , further comprising:
calculating, using the machine learning technique, prescriptive analytics to determine historical trends in the digital data from the first event.
17 . The non-transitory medium of claim 15 , further comprising:
generating a second report using the proactive analytics calculated.
18 . The non-transitory medium of claim 15 , wherein the reason for the event occurrence is determined based on a monitoring of the real-time digital data.
19 . The non-transitory medium of claim 15 , wherein the performance metric and report are transmitted, via network connection, to a user device for presentation on an interactive user interface.
20 . The non-transitory medium of claim 19 , wherein the performance metric and the report transmitted is personalized using a social currency of the user of the user device.