Content distribution and optimization system and method for deriving new metrics and multiple use cases of data consumers using base event metrics

1 . A content distribution and optimization system, comprising:

a memory for storing instructions; and

one or more processors configured to execute the instructions, and based on the executed instructions, the one or more processors are configured to:

ingest raw event data from a client computing device at an entry point of a data pipeline service in accordance with a defined schema, wherein:

(i) the raw event data corresponds to a base event comprising a plurality of contextual payloads and a plurality of base event metrics,

(ii) a contextual payload of the plurality of contextual payloads comprises at least one of a first set of dimensional properties provided by the client computing device or a second set of dimensional properties added at the entry point, and

(iii) the first set of dimensional properties and the second set of dimensional properties correspond to one or more logically grouped attributes and one or more data values corresponding to the one or more logically grouped attributes;

provide the raw event data to a message bus pipeline for enrichment, wherein:

(i) one or more transformations are applied on enriched raw event data comprising the plurality of base event metrics to derive, at a same time instant, a distinct use case for each data consuming tool or service of a plurality of data consuming tools or services, wherein each use case is in a respective format configured for direct access by each respective data consuming tool or service of the plurality of data consuming tools or services, wherein multiple distinct use cases are associated with a same base event and the one or more transformations comprises one or more of a depersonalization, a marketing transformation, a customer service transformation, a device information transformation, or a performance transformation, and a transformation of the one or more transformations for a respective use case is based on one or more contextual aspects of a respective data consuming tool or service for the respective use case; and

(ii) the distinct use cases correspond to one or more contextual payloads of the plurality of contextual payloads; and

provide the one or more contextual payloads from the plurality of contextual payloads to a stream-based messaging bus as raw video events, wherein one or more new metrics are derived based on the raw video events for network selection and centralized alarming and reporting.

2 . The content distribution and optimization system according to claim 1 , wherein the plurality of base event metrics comprise application metrics, device metrics, session metrics and heartbeat metrics to provide the distinct use case for each data consuming tool or service of the plurality of data consuming tools or services.

3 . The content distribution and optimization system according to claim 1 ,

wherein the raw event data is retrieved from a cloud object storage of the message bus pipeline, wherein the retrieved raw event data is enriched with additional information, and

wherein the additional information corresponds to geographic information associated with an internet protocol (IP) address of the client computing device.

4 . The content distribution and optimization system according to claim 1 , wherein the enriched raw event data and a normalized data feed is collated in a time-ordered series.

5 . The content distribution and optimization system according to claim 1 , wherein a user interaction is grouped with a player at the client computing device from a point associated with an initiation of play based on a last video session initiated timestamp and a device serial number or a device identifier (ID).

6 . The content distribution and optimization system according to claim 1 , wherein the raw video events are enriched to include additional information,

wherein the additional information includes at least geographic information of the client computing device and designated market area (DMA), and

wherein the raw video events are further validated and structured in addition to the enrichment.

7 . The content distribution and optimization system according to claim 1 , wherein the one or more new metrics are transmitted to an analytical search engine for real-time aggregation.

8 . The content distribution and optimization system according to claim 1 , wherein a session is constructed at server-side for an application based on a defined business rule using session timestamps from a session payload, and

wherein the session payload comprises an application launch timestamp.

9 . The content distribution and optimization system according to claim 1 , wherein the plurality of contextual payloads corresponds to an application payload, a device payload, a session payload, a referral payload, a visitor identity payload, an event payload, and a page payload.

10 . The content distribution and optimization system according to claim 9 , wherein the first set of dimensional properties of the event payload includes a type of the base event, a subtype of the base event, and a client timestamp, and

wherein the second set of dimensional properties of the event payload includes a server timestamp.

11 . The content distribution and optimization system according to claim 10 , wherein the subtype of the base event is a heartbeat event when the type of the base event is video quality of service (QOS) event,

wherein the heartbeat event corresponds to an application heartbeat or a video heartbeat, and

wherein a derivation of the distinct use case for each data consuming tool or service of the plurality of data consuming tools or services corresponds to batch-based analytical processing and a derivation of the one or more new metrics for network selection and centralized alarming and reporting correspond to real-time stream processing based on at least the heartbeat event.

12 . The content distribution and optimization system according to claim 1 , wherein each data consuming tool or service of the plurality of data consuming tools or services corresponds to at least one of a QoS delivery tool, a reporting tool, a customer service tool, an internal fraud tool, a content insights tool, or a subscription reporting tool.

13 . A content distribution and optimization method, comprising:

ingesting, by one or more processors, raw event data from a client computing device at an entry point of a data pipeline service in accordance with a defined schema, wherein:

(i) the raw event data corresponds to a base event comprising a plurality of contextual payloads and a plurality of base event metrics,

(ii) a contextual payload of the plurality of contextual payloads comprises a first set of dimensional properties provided by the client computing device or a second set of dimensional properties added at the entry point, and

(iii) the first set of dimensional properties and the second set of dimensional properties correspond to one or more logically grouped attributes and one or more data values corresponding to the one or more logically grouped attributes;

providing the raw event data to a message bus pipeline for enrichment, wherein:

(i) one or more transformations are applied on enriched raw event data comprising the plurality of base event metrics to derive, at a same time instant, a distinct use case for each data consuming tool or service of a plurality of data consuming tools or services, wherein each use case is in a respective format configured for direct access by each respective data consuming tool or service of the plurality data consuming tools or services, wherein multiple distinct use cases are associated with a same base event and the one or more transformations comprises one or more of a depersonalization, a marketing transformation, a customer service transformation, a device information transformation, or a performance transformation, and a transformation of the one or more transformations for a respective use case is based on one or more contextual aspects of a respective data consuming tool or service for the respective use case, and

(ii) the distinct use cases correspond to one or more contextual payloads of the plurality of contextual payloads; and

providing one or more contextual payloads from the plurality of contextual payloads to a stream-based messaging bus as raw video events, wherein one or more new metrics are derived based on the raw video events for network selection and centralized alarming and reporting.

14 . A non-transitory computer readable medium, having stored thereon, computer executable code, which when executed by one or more processors, cause the one or more processors to execute operations, the operations comprising:

ingesting raw event data from a client computing device at an entry point of a data pipeline service in accordance with a defined schema, wherein:

(i) the raw event data corresponds to a base event comprising a plurality of contextual payloads and a plurality of base event metrics,

(ii) a contextual payload of the plurality of contextual payloads comprises a first set of dimensional properties provided by the client computing device or a second set of dimensional properties added at the entry point, and

(iii) the first set of dimensional properties and the second set of dimensional properties correspond to one or more logically grouped attributes and one or more data values corresponding to the one or more logically grouped attributes;

providing the raw event data to a message bus pipeline for enrichment, wherein:

(i) one or more transformations are applied on enriched raw event data comprising the plurality of base event metrics to derive, at a same time instant, a distinct use case for each data consuming tool or service of a plurality of data consuming tools or services, which each use case is in a respective format configured for direct access by each respective data consuming tool or service of the plurality of data consuming tools or services, wherein multiple distinct use cases are associated with a same base event and the one or more transformations comprises one or more of a depersonalization, a marketing transformation, a customer service transformation, a device information transformation, or a performance transformation, and a transformation of the one or more transformations for a respective use case is based on one or more contextual aspects of a respective data consuming tool or service for the respective use case, and

(ii) the distinct use cases correspond to one or more contextual payloads of the plurality of contextual payloads; and

providing one or more contextual payloads from the plurality of contextual payloads to a stream-based messaging bus as raw video events, wherein one or more new metrics are derived based on the raw video events for network selection and centralized alarming and reporting.

15 . The content distribution and optimization system according to claim 1 , wherein the one or more processors are further configured to enrich the raw event data with at least one of information about a content delivery network (CDN) associated with the raw event data, or information about a network connection associated with the raw event data, wherein the enriched raw event data is provided to a CDN scoring database, the CDN scoring database is accessed to select a CDN for routing traffic.

16 . The content distribution and optimization system according to claim 1 , wherein the respective data consuming tool or service comprises a marketing platform, the transformation of the one or more transformations comprises the marketing transformation, and the marketing transformation comprises aggregating heartbeat metrics associated with user interactions at a client computing device.

17 . The content distribution and optimization system according to claim 1 , wherein the respective data consuming tool or service comprises a customer service tool, the transformation of the one or more transformations comprises the customer service transformation, and the customer service transformation comprises aggregating customer service information associated with at least one of successful video playback or failed video playback.

18 . The content distribution and optimization system according to claim 1 , wherein the respective transformation comprises at least the device information transformation, and the device information transformation comprises aggregating details associated with the client computing device, comprising one or more characteristics, a category, a code, a location, an operating system version, a serial number, a manufacturer, a rendering agent, or a client computing device identifier for a respective client computing device.

19 . The content distribution and optimization system according to claim 1 , wherein the respective data consuming tool or service comprises an analytics and monitoring application, the transformation of the one or more transformations comprise at least the performance transformation, and the performance transformation comprises aggregating one or more of an application version, a platform tenant code, a product code, a bootstrap version, an application performance index score, an average response time, an error rate, a request rate, a computer processing unit usage metric, uptime for service level agreements (SLAs), or a garbage collection metric.

20 . The content distribution and optimization system according to claim 1 , wherein the one or more transformations comprises a depersonalization.